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Victoria Transport Policy Institute
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Updated 6 September 2019
This chapter describes transportation evaluation methods and how they can be used to evaluate the value of TDM programs. Transportation Demand Management evaluation requires more comprehensive analysis than is often used for transportation planning. This chapter discusses the travel changes caused by different types of TDM strategies, the impacts (benefits, costs and equity effects) that result, and how information in this Encyclopedia can help rate TDM strategies in terms of their ability to achieve various objectives.
General Steps in Economic Evaluation
Transportation Improvement Objectives
Road and Parking Facility Cost Savings
Evaluating Transportation System Quality
Conventional Versus Comprehensive Evaluation
Cumulative and Synergistic Impacts
Determining Incremental Impacts
Analysis Perspective and Scale
Resource Costs and Economic Transfers
Common Errors When Comparing Capacity Expansion and TDM Options
References And Resources For More Information
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You Too Can Be A Policy Analyst or Planner!
When evaluating a public policy or project, most people ask, “How does it directly affect me?” A policy analyst or planner takes a broader perspective. They consider different perspectives, groups and geographic scales. They consider indirect and long-term impacts. They consider how a particular short-term action relates to a community’s overall strategic objectives.
A policy analyst or planner is a professional worrier, always thinking about what could go wrong, and the worst possible conditions that could result.
Good policy analysis and planning help communities avoid problems. Unfortunately, this tends to be a thankless job because beneficiaries never experience the problems they would otherwise suffer. A doctor who encourages patients to stop smoking, eat a healthier diet and exercise more is considered bothersome, while a surgeon who performs a heart transplant after a patient becomes ill is considered a hero, although a preventive medical approach usually provides far greater overall benefits. Similarly, good public policies provide tremendous benefits, but little glory.
It’s often a difficult job, but somebody must do it. And the more knowledge, skill, respect for others and community spirit you can bring, the better for everybody involved. |
Life is full of tradeoffs. There are only so many hours in a day or dollars in a budget. Economics is the discipline concerned with such trade-offs, that is, how resources can be used to provide the greatest possible benefit.
Economic Evaluation (also called Appraisal or Analysis) refers to methods to determine the value of a planning option to support decision making. Economic evaluation is often applied to transportation decision-making (Small 1999; Litman 2001; USDOT 2003; CUTR 2007). Specific evaluation methods are described below:
· Cost-Effectiveness compares the costs of different options for achieving a specific objective, such as building a particular road or delivering a particular amount of freight. The quantity of outputs (benefits) are held constant, so there is only one variable, the cost of inputs.
· Benefit-Cost Analysis compares total incremental benefits with total incremental costs of each option. It is not limited to a single objective or benefit. For example, potential highway routes may differ in construction costs and the quality of service (speed and safety) they provide.
· Lifecycle Cost Analysis is Benefit-Cost Analysis that incorporates the time value of money. Lifecycle Cost Analysis allows programs or projects to be compared that have benefits and costs occurring at different times. For example, one option may be quicker to implement but has greater costs or lesser benefits than an alternative. Lifecycle cost analysis is important for determining the best long-term infrastructure maintenance program (FCM, 2002).
· Least Cost Planning is a type of Benefit-Cost Analysis that considers demand management on equal terms with capacity expansion. Least Cost Planning allows TDM to be implemented when it is cost effective.
· Multiple Accounts Evaluation is an analysis method that incorporates both quantitative and qualitative criteria, and can be used when some impacts cannot be monetized. Each option is rated for each criterion.
These methods evaluate the economic impacts (costs and benefits) of a policy or project to determine net benefits or net value (incremental benefits minus incremental costs). Economic analysis is not limited to market (monetary) impacts; it can also incorporate non-market impacts such as travel time, crash risk, environmental impacts and equity objectives. Various techniques are used to determine the monetized value (i.e., how much people would be willing to pay) for these non-market goods (Litman, 2009a; EDRG, 2007). See GDRC (2000) and Bhasin (2005) for other evaluation methods that also take into account factors such as health, quality of life and development.
Transportation decisions often have various levels of impacts. For example, increasing roadway capacity has direct impacts of reducing traffic congestion and increasing vehicle traffic speeds. A second-level impact is that this increased speed and convenience may attract additional travel from other routes and times (Rebound Effects), and it may create barriers to walking and cycling (Nonmotorized Evaluation). A third level impact may be that over the long run, land use patterns change as people and businesses respond to more convenient driving and less convenient nonmotorized travel (Land Use Impacts).
When evaluating transportation management strategies it is helpful to differentiate between their travel impacts (the change per affected person or business) and take up (also called penetration), which reflects how broadly the strategy is applied. For example, Parking Cash Out typically reduces automobile use by 15-20% among commuters where it is applied, but it is not widely applied, so its effects on total travel been small. Critics sometimes complain that TDM is ineffective, citing continued transportation problems such as congestion and pollution in cities that claim to have TDM programs. However, this does not reflect a lack of impacts where TDM is implemented, rather it is a lack of take up of the strategies: few motorists actually face TDM strategies such as Parking Cash Out, Parking Pricing or Road Pricing.
In most planning situations, evaluation concerns incremental impacts, such as an improvement or reduction in transportation facilities or services. For example, planners may want to compare the incremental benefits and costs of a new pedestrian bridge, roadway capacity expansion or improved transit services. This is called a marginal analysis. It is seldom necessary to calculate the total value of transportation facilities or services, such as the total benefits from all pedestrian, roadway or transit travel.
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Marginal Analysis Economic evaluation should be based on marginal analysis, that is, the incremental impacts (costs and benefits) of an additional unit of consumption. Marginal analysis means that all costs and benefits are considered, and that impacts are calculated for each mode, vehicle, location and time (although as a practical matter these are often grouped into a few major categories). Marginal analysis means that the costs of increasing system are assigned only to peak-period travelers, since those are the users that require it. Marginal impacts often differ significantly from average impacts. Highway costs may average just 5¢ per vehicle-mile, but the marginal cost of additional urban-peak vehicle trips may be ten or twenty times higher because it requires increasing roadway capacity. |
Under certain circumstances, modest changes in vehicle travel can provide large benefits. For example, once roadways approach their capacity, small reductions in traffic volumes can substantially reduce congestion impacts, providing large benefits to all travelers. Reducing peak period parking demand, for example, if stores encourage employees to use alternative commute modes during busy shopping days, or downtowns offer special bus services during special events, can substantially reduce the number of parking spaces that would otherwise be needed. Even small reductions in high-risk driving, for example, by adolescent males and inebriated drivers, can provide relatively large crash reductions. Since motor vehicles have high fuel consumption and emission rates during short trips, shifting from automobile to non-motorized modes for short trips can provide proportionately large energy savings and emission reductions.
As a result, mobility management benefits are often proportionately larger: for example, a relatively small mode shift can provide large reductions in traffic congestion and parking costs if it involves peak-period trips on major corridors, and shifting a relatively small portion of total travel from motorized to non-motorized modes can provide large reductions in energy consumption, pollution emissions and consumer costs.
An evaluation framework specifies the basic structure of the analysis for clear and consistent evaluation and comparison. A framework usually identifies:
· Evaluation method, such as cost-effectiveness, benefit-cost, lifecycle cost analysis, etc.
· Evaluation criteria, which are the factors and impacts to be considered in the analysis, including indirect and long-term impacts. Impacts can be defined in terms of objectives or their opposite, problems (for example, congestion reduction is an objective because congestion is considered a problem), or they can be defined in terms of costs and benefits (for example, congestion reduction benefits can be measured based on reductions in congestion costs). Planners tend to use the terms objectives and problems (which are more qualitative), while economists tend to use the terms benefits and costs (which are more quantitative), all of which can be considered different approaches for evaluating the same impacts, as illustrated in the table below.
Table 1 Ways to Describe An Impact
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Positive |
Negative |
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Qualitative |
Objective |
Problem |
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Quantitative |
Benefit |
Cost |
Objective, Problem, Benefit and Cost are different ways to describe an impact.
· Modeling techniques, which predict how a policy change or program will affect travel behavior and land use patterns.
· The Base Case, meaning what would happen without the policy or program.
· Comparison units, such as costs per lane-mile, vehicle-mile, passenger-mile, incremental peak-period trip, etc.
· Base year and discount rate, which indicates how costs are adjusted to reflect the time value of money.
· Perspective and scope, such as the geographic range of impacts to consider.
· Dealing with uncertainty, such as whether sensitivity analysis or other statistical tests will be used.
· How results are presented, so that the results of different evaluations are easy to compare.
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Solving Transportation Problems Transport problems and solutions can be viewed in two different ways. One is as individual problems with technical solutions: traffic and parking congestion require building more roads and parking facilities; crash risk requires roads and vehicles that offer greater crash protection; energy problems require alternative fuels and efficiency standards; mobility for non-drivers in automobile-oriented areas requires paratransit services. The motto is, “adjust roads and vehicles, not driver behavior.” This can be considered a reductionist model, which considers just one problem at a time.
But this approach has a fundamental flaw. Solutions to one problem often exacerbate other problems, particularly if they increase total vehicle travel. For example, over the long run, increasing roadway capacity tends to increase crashes, energy consumption and pollution, due to Induced Vehicle Travel; crash protection requires heavier vehicles that consume more energy; Fuel Efficiency Standards reduce the per-mile cost of driving, stimulating more traffic congestion and crashes; Paratransit vehicles add traffic congestion, crash risk and pollution. As a result, a reductionist approach does not usually solve problems overall, because the more one solution achieves its objectives, the more it exacerbates other problems.
The other perspective is that many transportation problems share a common root: market distortions that result in excessive automobile use. From this perspective, solving transport problems requires planning reforms that increase transport options, and market reforms that give consumers suitable incentives to choose the best option for each individual trip. The motto is, “increase transportation system diversity and efficiency.” Transportation Demand Management or TDM is the general term for this approach.
Although most individual TDM strategies only affect a small portion of total travel, and so their benefits appear modest with respect any particular problem, their impacts are cumulative and synergistic. When all benefits and costs are considered, TDM programs are often the most cost effective way to improve transportation.
Conventional evaluation practices tend to overestimate the overall benefits of technical solutions because they ignore indirect costs (such as the problems resulting from induced vehicle travel), and they tend to underestimate the full benefits of TDM strategies (such as helping to improve mobility for non-drivers, or support for strategic land use objectives). More comprehensive Evaluation and Planning practices are needed for TDM to receive the recognition and support that is justified. |
A typical economic evaluation involves the following general steps (ECONorthwest and PBQD 2002; Sallman, et al. 2012). This is a hybrid approach that includes lifecycle cost analysis of impacts that are suitable for monetization, plus a rating system for impacts that are unsuited to monetization.
1. Describe each option, including a base-case and one or more alternatives.
2. Define the analysis framework (described above), which identifies all impacts (costs and benefits) and objectives to be considered in the analysis. Classify impacts to avoid double-counting.
3. Model and monetize (measure in monetary value) impacts, such as changes in congestion, crashes, road and parking facility costs, consumer costs, mobility options for disadvantaged travelers, pollution emissions, etc.
4. Calculate the total monetized benefits and costs for each year that is being considered (typically 10-20 years for a major investment project), and apply a discount value to future impacts. Sum the present value of benefits and costs to determine the Net Present Value.
5. Describe, and measure as much as possible, impacts that are unsuited for monetization (such as equity and effects on strategic community development objectives). Rate each alternative according to how much it supports or contradicts the objectives.
6. Conduct sensitivity analysis to determine how changes in key assumptions affect outcomes.
7. Report result. Develop various ways to illustrate important differences between the options and describe their implications. For example:
· Produce graphs that illustrate differences in key impacts.
· Produce a table or matrix that compares each alternative in terms of its costs, benefits and rating in terms of objectives (such as whether it supports or contradicts equity and strategic community development objectives).
· Identify the distribution of impacts (which individual or group bears costs or gains benefits).
· Produce short summaries that describe key differences, and factors that may affect these differences.
Of course, these steps can be adjusted and repeated as needed. For example, stakeholders may sometimes request that additional options, impacts or objectives be considered, or that additional analysis be performed to determine the distribution of impacts.
Transportation economic evaluation often involves comparing different types of activities, and investments that have very different cost and benefit profiles. For example, highway investments typically consist primarily of a large capital expense, while TDM programs typically consist of ongoing operating expenses. Highway capacity expansion tends to provide large short-term congestion reduction benefits, but these decline over time due to generated traffic, while TDM programs tend to provide smaller short-term benefits, but these often increase over time as programs develop.
It is therefore important to choose appropriate reference units for comparison. Reference units are measurement units normalized to help people understand and compare impacts. Common reference units include per capita, per mile, per trip, per vehicle and per dollar. Reference units for transportation program economic evaluation should allow costs and benefits that occur at different times to be compared. Lifecycle Cost Analysis and Net Present Value do this, but often result in very large numbers that are difficult for most people to comprehend. For example, the lifecycle costs of a private home (total capital and operating expenses its operating life) may total millions of dollars, and the lifecycle costs of a roadway project or transit service improvement may total tens or hundreds of millions of dollars. It is therefore useful to convert these numbers into annualized costs or annualized costs per capita, or other reference units specific to transportation.
For example, a transportation project costs might be measured per capita, to compare them with other expenditure categories, other years, and other communities. The costs of highway capacity expansion may be measured per lane-mile, to compare with other highway projects, or per additional peak-period person trip, to compare with other ways to accommodate increased travel demand. Which reference units are used can affect how problems are defined and which solutions are considered, as described below.
· Annualized Cost Per Capita is a useful reference unit to help decision-makers and consumers compare projects and programs with other common expenses, such as the cost of owning and operating an automobile.
· Vehicle-mile units reflect a traffic perspective that gives high value to automobile travel.
· Passenger-mile units reflect a mobility perspective that values automobile and transit travel, but gives less value to nonmotorized modes because they tend to be used for short trips.
· Per-trip units reflect an access perspective which gives equal value to automobile, transit, cycling, walking and telecommuting.
· Travel time units reflect an access perspective that gives higher priority to walking, cycling and transit travel, because they tend to represent a relatively large portion of travel time.
· Exposure time reflects the amount of time that a particular person or groups uses a particular facility or is exposed to a particular impact. Slower modes and people who stay along a street have greater exposure time than motor vehicle passengers.
TDM programs can be evaluated in various ways and at various levels. Finke and Schreffler (2004) describe the following possible levels of assessment:
Not all TDM strategies affect travel directly. Some provide a foundation for other strategies that change travel behavior, which in turn have various economic, social and environmental impacts. These relationships are illustrated below.
Policies
(planning and investment practices, land use practices, tax policies, etc.)
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Programs and Projects
(Commute Trip Reduction, Transportation Management Associations, Nonmotorized Transport Planning, Parking Management, school and campus trip management, etc.)
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Strategies That Directly Affect Travel Behavior
(Parking Cash Out, congestion pricing, transit improvements, improved walking and cycling conditions, flextime, Location Efficient Mortgages, higher parking fees, etc.)
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Travel Impacts
(mode shifts, shifts in trip scheduling, shorter trip distances, reduced driving, increased load factors, etc.)
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Benefits
(improved mobility and access, cleaner air, road safety, road and parking facility cost savings, consumer savings, etc.)
TDM strategies use a variety of mechanisms to change travel patterns, including facility design, improved transport options, pricing, and land use changes. These affect travel behavior in various ways, including changes in trip scheduling, route, mode, destination, and frequency, plus traffic speed, mode choice and land use patterns. The table below summarizes the travel changes that result from various TDM strategies.
Models are now available which can predict the travel impacts of a specific Commute Trip Reduction program, taking into account the type of program and worksite. These include the TRIMMS (Trip Reduction Impacts of Mobility Management Strategies) Model (www.nctr.usf.edu/abstracts/abs77704.htm), the CUTR_AVR Model (www.cutr.usf.edu/tdm/download.htm), the Business Benefits Calculator (BBC) (www.commuterchoice.gov) and the Commuter Choice Decision Support Tool (www.ops.fhwa.dot.gov/PrimerDSS/index.htm). CUTR (2009), describes TRIMMS Model Enhancements to better calculate benefits for transportation investments. Mustel (2004) surveyed Vancouver, BC regional motorists to determine what type of travel shifts they consider most feasible. DKS Associates (2003) illustrates an example of impact analysis on a specific corridor. The Operations Benefit/Cost Analysis Desk Reference (Sallman, et al. 2012) is a guidebook and spreadsheet model for applying economic evaluation to various transportation management programs. See Transportation Elasticities for information on the travel impacts that result from various price changes. IFS (2001) is an excellent example of an interactive Internet tool that can help public officials and citizens predict the travel impacts of various TDM strategies.
Table 2 Examples of TDM Travel Impacts
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TDM Strategies |
Mechanism |
Travel Changes |
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Traffic Calming |
Roadway redesign. |
Reduces traffic speeds, improves pedestrian conditions. |
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Flextime |
Improved transport choice. |
Shifts travel time (when trips occurs). |
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Road/Congestion Pricing |
Pricing |
Shifts travel time, reduces vehicle travel on a particular roadway. |
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Distance-based charges |
Pricing |
Reduces overall vehicle travel. |
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Transit improvements |
Improved transport choice. |
Shifts mode, increases transit use. |
|
Rideshare promotion |
Improved transport choice. |
Increases vehicle occupancy, reduces vehicle trips. |
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Pedestrian and bicycle improvements |
Improved transport choice, facility improvements. |
Shifts mode, increases walking and cycling. |
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Carsharing |
Improved transport choice. |
Reduces vehicle ownership and trips. |
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Smart Growth, New Urbanism |
More efficient land use, improved travel choices. |
Shifts mode, reduces vehicle ownership and trip distances. |
Different types of TDM strategies cause different types of travel changes.
Different types of travel changes provide different types of impacts. For example, a strategy that shifts travel from peak to off-peak periods has different benefits and costs than a strategy that shifts travel modes or encourages more efficient land use. A shift from driving to nonmotorized travel has different impacts than a shift to public transit. Table 3 shows how different travel behavior changes are rated according to the TDM objectives used in this Encyclopedia (described in the next section of this chapter).
Table 3 Benefits of Different Travel Impacts
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Reduced Traffic Speeds |
Shift Trip Time |
Shorter Trips |
Shift Mode |
Reduced Veh. Trips |
Reduced Veh. Ownership |
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Congestion Reduction |
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3 |
2 |
2 |
3 |
3 |
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Road Savings |
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1 |
2 |
2 |
3 |
3 |
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Parking Savings |
|
|
|
3 |
3 |
3 |
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Consumer Savings |
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|
1 |
2 |
2 |
3 |
|
Transport Choice |
|
1 |
|
3 |
2 |
3 |
|
Road Safety |
3 |
|
2 |
2 |
3 |
3 |
|
Environmental Protection |
1 |
|
1 |
2 |
2 |
3 |
|
Efficient Land Use |
1 |
|
2 |
1 |
2 |
3 |
|
Community Livability |
2 |
|
1 |
1 |
2 |
3 |
Rating from 3 (very beneficial) to –3 (very harmful).
Performance evaluation refers to a process of monitoring and analysis used to determine how well policies, programs and projects perform with regard to their intended goals and objectives (TRB, 2001). This can help identify potential problems and provide guidance for policy, planning and management decisions. This tends to be particularly important for innovative solutions, such as TDM. The US Department of Transportation’s Performance Plan and Performance Report (www.dot.gov/performance), is a good example of an organizational-level evaluation. It includes tables showing whether various objectives and targets have been met during each year.
Performance indicators (also called measures of effectiveness) are specific measurable outcomes used to evaluate progress toward established goals and objectives. A number of performance indicators can be used to evaluate transportation system quality and the effectiveness of a TDM program (Kittleson & Associates, 2003). These usually include both quantitative measures of Mobility and Access, and qualitative measures of user acceptance and satisfaction (Surveys). In most cases, no single indicator is adequate, so a set of indicators that reflect various objectives and perspectives are used. Which indicators are selected and how they are weighted and presented implicitly defines the value placed on different objectives.
Successful Performance Evaluation:
· Comprises a balanced set of a limited vital few measures.
· Produces timely and useful reports at a reasonable cost.
· Displays and makes readily available information that is shared, understood, and used by an organization.
· Supports the organization's values and the relationship the organization has with customers, suppliers, and stakeholders.
A good performance indicator:
· Is accepted by and meaningful to the customer.
· Tells how well goals and objectives are being met.
· Is simple, understandable, logical, and repeatable.
· Shows a trend.
· Is unambiguously defined.
· Allows for economical data collection.
· Is timely.
· Is sensitive.
Below are Performance Indicators suitable for evaluating TDM programs (Schreffler, 2000). These indicators can be defined for a particular time (such as peak-hour) and geographic location (such as a particular destination, district or region).
· Awareness – the portion of potential users who are aware of a program or service.
· Participation – the number of people who respond to an outreach effort or request to participate in a program.
· Utilization – the number of people who use a service or alternative mode.
· Mode split – the portion of travelers who use each transportation mode.
· Mode shift – the number or portion of automobile trips shifted to other modes.
· Average Vehicle Occupancy (AVO): Number of people traveling in private vehicles divided by the number of private vehicle trips. This excludes transit vehicle users and walkers.
· Average Vehicle Ridership (AVR): All person trips divided by the number of private vehicle trips. This includes transit vehicle users and walkers.
· Vehicle Trips or Peak Period Vehicle Trips: The total number of private vehicles arriving at a destination (often called “trip generation” by engineers).
· Vehicle Trip Reduction – the number or percentage of automobiles removed from traffic.
· Vehicle Miles of Travel (VTM) Reduced – the number of trips reduced times average trip length.
· Energy and emission reductions – these are calculated by multiplying VMT reductions times average vehicle energy consumption and emission rates.
· Cost Per Unit of Reduction – these measures of cost-effectiveness are calculated by dividing program costs by a unit of change. For example, the cost effectiveness of various TDM programs could be compared based on cents per trip reduced, or ton of air pollution emission reductions. However, as described later, cost-effectiveness analysis that only considers direct impacts and a single objective may overlook additional costs and benefits to participants and society. For example, two TDM programs may have the same direct costs per unit of emission reduction, but differ significantly in terms of consumer costs, consumer travel options, traffic congestion, parking costs, crash risk and land use impacts.
Evaluation studies can compare performance indicator values before-and-after, over time (for example, over months or years), with-and-without (for example, comparing performance indicators at a worksite or area that has a TDM program with otherwise comparable sites that do not have such programs, or with regional averages).
This Encyclopedia evaluates each TDM strategy according to the eight transportation improvement objectives described below. It uses a 7-point rating system that ranges from 3 (strongly benefits that objective) to –3 (very harmful to that objective). For example, a TDM strategy that encourages motorists to shift some of their trips from peak to off-peak time periods may rate a 3 in terms of congestion reduction, but only a 1 in terms of environmental protection. Of course, actual impacts vary depending on circumstances, and so ratings should be adjusted to reflect specific conditions when they are applied to a particular project evaluation.
Reduced urban-peak vehicle travel tends to reduce traffic congestion (in this case, “urban” includes suburbs, small towns and resort communities during tourist season). Traffic congestion is a non-linear function, meaning that a small reduction in urban-peak traffic volume can cause a proportionally larger reduction in delay. For example, a 5% reduction in traffic volumes on a congested highway may cause a 10% or even greater reduction in congestion delays. As a result, even relatively small traffic reductions can provide relatively large travel time savings benefits.
Traffic congestion is usually defined and measured only in terms of the delays that motor vehicle traffic imposes on other motor vehicles. Traffic impacts on cyclists and pedestrians are usually ignored, although in some areas they represent a major share of travel delay (Evaluating Nonmotorized Transport). Incorporating impacts on nonmotorized travel tends to increase the predicted benefits of TDM strategies that reduce vehicle traffic volumes, and reduce the benefits of congestion reduction strategies that involve roadway widening which creates barriers to nonmotorized travel.
Generated Traffic tends to reduce the congestion reduction benefits of highway capacity expansion and some types of TDM strategies, particularly over the long-term. Generated Traffic consists of additional vehicle travel that occurs when urban highway capacity is increased or when TDM strategies reduce peak-period vehicle trips (Rebound Effect). Put another way, urban traffic congestion tends to maintain a self-limiting equilibrium by constraining growth in peak-period trips. Some TDM strategies produce little or no generated traffic and so tend to be particularly effective at reducing traffic congestion delays.
· Grade separated Transit Improvements and HOV facilities can reduce traffic congestion on parallel highways (Evaluating Public Transit)
· Pricing strategies such as Road Pricing, Distance-Based Fees and Comprehensive Market Reforms tend to shift the demand curve, reducing the overall point of congestion equilibrium.
· Land use management strategies such as New Urbanism and Smart Growth that result in more Clustering may increase local traffic congestion (within the clustered area), but reduce per capita vehicle travel, and reductions in regional traffic congestion, resulting in overall reductions in congestion costs. For more discussion see Land Use Impacts on Transportation.
Reduced vehicle travel can reduce the need to add roadway capacity, reduce some roadway operations and maintenance costs, and reduce some traffic service costs, such as policing and emergency response. Shifts from automobile to bus transport may increase some road maintenance costs (heavy vehicles tend to cause high levels of road wear). Reductions in automobile trips may provide little parking cost savings in the short-run if there is abundant parking supply. However, over the long term, the excess parking spaces or their land can be used for other purposes. Parking Management can help capture these benefits.
Many TDM strategies can provide consumer savings by improving Transportation Options, reducing Vehicle Costs, or providing direct financial benefits. Savings can be especially large if a TDM program allows a household to reduce the number of vehicles it owns or to defer the replacement of an older vehicle. Some TDM strategies, such as commuter financial benefits and transit fare reductions, provide direct payments or savings to consumers. Conversely, some TDM strategies increase consumers cost by increasing fees for parking, road or vehicle use. Some TDM strategies affect non-monetary consumer costs, such as travel time and comfort. The value of these impacts can be calculated based on Consumer Surplus analysis, as described later in this chapter.
Many TDM strategies improve Transportation Options by improving alternative modes, providing new pricing options, or increasing land use Accessibility. This provides various types of benefits to consumers and society, including improved access and opportunity, consumer cost savings, increased Equity, improved community Livability, and reductions in various external costs. Adequate Transportation Options are a key Market Principle for economic efficiency and equity. Multi-Modal Level-of-Service Indicators can be used to evaluate the quality of various transport modes from a users perspective, including factors such as comfort, convenience, affordability and security.
Some TDM strategies increase consumer options in ways that increase mobility. For example, Carsharing and Pay-As-You-Drive Insurance makes vehicle use more affordable for lower-income drivers, and Transit Improvements may increase personal travel (not every additional transit trip represents an automobile trip reduced). TDM evaluation that only considers traffic congestion or emission reduction objectives will overlook these mobility benefits (Evaluating Public Transit).
Many TDM strategies provide Traffic Safety, Resilience, Security and Public Health benefits (Safety Impacts of TDM). Strategies that reduce total vehicle mileage, reduce traffic speeds, or provide an incentive for safer driving tend to be particularly effective at reducing crashes. Strategies that reduce traffic congestion without reducing mileage, by shifting travel times and routes, have mixed safety benefits: although crashes tend to decline, collisions that do take place tend to be more severe because they occur at higher speeds (Shefer and Rietvald 1997).
TDM strategies that reduce vehicle mileage, optimize vehicle speeds and reduce traffic congestion provide Energy Conservation and Emission Reductions. Strategies that encourage motorists to use more efficient, less polluting vehicles, or which reduce total vehicle ownership and trips, tend to be particularly effective at energy and emission reductions. Some strategies encourage more efficient land use patterns that reduce per capita impervious surface coverage (the amount of land paved for roads, paths and parking facilities, or covered by buildings), which helps preserve greenspace and reduce stormwater management costs. Special techniques are needed to evaluate indirect and cumulative impacts (MacDonald and Lidov, 2005).
Strategies that encourage more Clustered, multi-modal, mixed land use patterns can improve Accessibility and reduce per capita impervious surface coverage and land consumption (Land Use Evaluation). This can provide a number of economic, social and environmental benefits compared with more dispersed, automobile-dependent land use patterns (Burchell, 1998). Smart Growth, New Urbanism, Transit Oriented Development, Location Efficient Development, Clustered Land Use, Parking Management, Pedestrian and Cycling Improvements and Traffic Calming are particularly effective at increasing land use efficiency.
The study Business Benefits of TDM (Winters and Hendricks 2001) identified the following potential benefits to employers from Commute Trip Reduction programs:
· Reduced Overhead Costs. Increased competition and need to build shareholder value place more pressure on businesses to lower their cost of doing business as well as increase revenues and/or margins. Strategies such as telecommuting and parking management can make a difference. Telecommuting can reduce office space requirements. Parking management can eliminate the need to build additional parking.
· Enhanced Employee Recruitment and Retention. A shrinking labor force has increased competition for qualified applicants. Similarly, the cost of replacing an employee in productivity and direct costs can be very expensive.
· Expanded Employee Benefits at Low/No Cost. Employers can take advantage of changes in the federal tax treatment of commute-to-work fringe benefits to benefit employees and reduce costs. Employers can now provide employees with a tax-free benefit and/or offer to subtract the cost of transit, vanpool, or parking as a pre-tax payroll deduction option.
· Enhanced Corporate Image. Employers with environmental image problems and/or difficulties with their neighbors often seek to mitigate the problems using a combination of trip reduction strategies.
· Reduced Localized Transportation Problems. Employers are well-aware of the value of banding together to address common problems. More employers are joining transportation management associations (TMAs) to address access and mobility problems in their immediate area.
· Expanded service hours. Work hour schedules such as flextime, staggered work hour programs, compressed work week programs enable organizations to provide additional coverage with the same total number of employers
· Lower absenteeism and tardiness. Employees may earlier time commitments to their carpool partner or to meet the bus. Telework may allow work to be accomplished when travel to the office isn’t possible.
· Increased employment opportunities for the disabled and others unable to meet traditional work hours. Telework provides an alternative to having to physical transport.
· Reduced employee stress. Employee health is significantly related to the distance and duration of the trip. People who are exposed to high levels of traffic congestion arrive at work with higher blood pressure than people who are not exposed. The more sensitive long distance commuters are to the effects of commuting on family life, the greater the inclination to try alternatives to solo driving.
· Enhanced employee productivity. One of the oft-cited benefits of telework is productivity increase.
Community Livability refers to the environmental and social quality of an area as perceived by residents, employees, customers and visitors. This includes crash risk, noise, local pollutants (e.g., dust), preservation of unique cultural and environmental resources (e.g., historic structures, mature trees, traditional architectural styles), attractiveness of streets, opportunities for recreation and entertainment, and the quality of social interactions, particularly among neighbors. A livable community directly benefits people who live in, work in or visit the neighborhood, increases property values and business activity, and it can improve public health and safety.
Many TDM strategies improve community livability by helping to create more attractive pedestrian conditions, creating more accessible land use patterns, and reduce total vehicle traffic on local streets. In particular, New Urbanism, Nonmotorized Transportation Improvements, Street Reclaiming, Traffic Calming, School Trip Management, Address Security Concerns, Car-Free Planning and Vehicle Restrictions can directly improve local environmental conditions, improving community livability.
TDM strategies can impose various costs. These are described below.
Many TDM programs have direct resource costs, including financial expenses, road space and traffic management priorities, and staff time.
Some TDM programs increase motorist financial costs or reduce their travel time. In response to these higher costs, some consumers forego travel or shift to less desirable travel modes.
Some TDM strategies increase transaction costs. For example, charging motorists directly for parking or road use requires systems to collect money and enforce payment. They also inconvenience motorists. (Newer electronic pricing mechanisms can significantly reduce transaction costs.)
TDM strategies that involve pricing result in economic transfers, that is, money is transferred from one group or economic sector to another (Evaluating Pricing). These are not true resource costs, but they represent costs to the consumers and businesses that pay additional charges.
Some TDM strategies have spillover impacts that should be considered in evaluation. For example:
· Road Pricing may shift vehicle travel and congestion problems to untolled roads.
· Traffic Calming may shift traffic impacts to other roads.
Parking Pricing in one area may increase parking problems in nearby areas, and may shift economic activity to areas that offer free parking.
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Consumer Costs of Reduced Mobility Critics of TDM sometime argue that strategies which reduce automobile travel impose significant but difficult to measure reductions in consumer mobility benefits. This is not quite true. The following guidelines can be used to evaluate consumer mobility costs from TDM: 1. TDM strategies that are optional to consumers and rely on positive incentives (such as improvements in alternative modes and positive financial incentives such as Parking Cash Out) directly benefit consumers, or they would not accept them. 2. The consumer surplus impacts of pricing incentives can be measured using the rule of half. 3. Most TDM incentives allow consumers to choose which trips to forego, resulting in reductions in the least-beneficial vehicle travel, so reductions in consumer surplus tend to be small. 4. Road and Parking pricing are economic transfers (money shifted) and so their overall impacts depend on how revenues are used. For example, Road Pricing costs may be offset by reductions in taxes or public service improvements financed by the additional revenue. |
Equity analysis reflects the distribution of costs and benefits. These issues are discussed in the chapter Evaluating TDM Equity. The Encyclopedia evaluates TDM strategies in terms of the five Equity objectives described below.
· Treats everybody equally. This reflects whether a strategy treats each group or individually equally.
· Individuals bear the costs they impose. This reflects whether a strategy makes individual consumers bear the costs they impose, meaning that subsidies are less than they would be with automobile travel.
· Progressive with respect to income. This reflects whether a strategy increases Transportation Affordability and makes lower-income households better or worse off.
· Benefits transportation disadvantaged. This reflects whether a strategy makes people who are transportation disadvantaged better off by increasing their travel options or providing financial savings.
· Improves Basic Access. This reflects whether a strategy favors more important transport (emergency response, commuting, essential shopping) over less important transport.
Although some TDM programs require subsidies, these are only considered unfair if they are greater than subsidies for comparable automobile travel. Expenditures on alternative modes may simply represent an alternative way for non-drivers to receive their share of transportation resources. Even if alternative modes have a greater subsidy per mile than automobile travel, non-drivers tend to travel much less per year than motorists, and so per capita subsidies may be much small (Transit Evaluation).
Equity analysis of TDM programs should also take into account any indirect benefits to motorists. For example, transit improvements benefit transit riders directly, and motorists may benefit indirectly if more attractive transit services reduces traffic congestion or competition for parking.
How transportation is Measured can have a major impact on the evaluation of a particular policy or program. For example, measuring transportation systems in terms of motor vehicle traffic capacity (e.g., roadway Level of Service ratings and volume to capacity ratios) favors strategies that expand road and parking facility capacity, and gives relatively little value to strategies that improve transportation alternatives (transit and walking conditions) or land use accessibility (increased land use clustering and mix). In recent years methods have been developed to better measure the quality of Accessibility, Nonmotorized Transportation and Transit Service, similar to existing tools for evaluating motor vehicle traffic conditions (FDOT, 2002).
TDM evaluation often involves comparing service quality of different modes, such as:
This information can be used to help identify problems and solutions. For example, increased automobile mode split can often be explained by factors such as the increased travel speeds and affordability of automobile travel relative to alternative modes, and efforts to shift travel to other modes can be evaluated by setting targets for improving their relative quality and affordability.
Transportation system quality can be evaluated by surveying users concerning their views of how well various components meet their needs, their evaluation of attributes such as convenience, comfort, safety and affordability, and descriptions of the problems and barriers they perceive. For example, the 1995 National Personal Transportation Survey includes questions that rate highway, transit, sidewalks, bicycle facilities and air travel on a scale from “excellent” to “poor” (NPTS, 1997).
Conventional transportation planning Models evaluate transportation projects by comparing direct project costs with travel time, vehicle operating cost, and crash cost savings. These may be adequate for comparing alternatives that are similar in terms of the type and amount of travel that will occur, but a more Comprehensive Transportation Planning framework is needed when comparing investments in different modes or evaluating a TDM program. Table 4 compares conventional and comprehensive transportation evaluation.
Table 4 Comparing Conventional and Comprehensive Planning (Comprehensive Planning)
|
|
Description |
Conventional |
Comprehensive |
|
Selection of Options |
The range of solutions that are considered, including capacity expansion and TDM programs. |
Often ignores TDM options |
Includes TDM options |
|
Investment Practices |
How funding is allocated, and the flexibility with which it can be used for the best overall option. |
Favors large capital investments |
Applies least-cost planning |
|
Underpricing |
Degree to which vehicle use is underpriced, resulting in excessive travel demand. |
Ignored |
Considered when determining travel demand and solutions. |
|
Modeling Practices |
Whether transport modeling uses current best practices to predict travel and economic impacts. |
Limited analysis capability |
More comprehensive capability |
|
Measuring Transportation |
Methods and perspectives used to measure travel (vehicle traffic, mobility or accessibility) |
Measures vehicle traffic |
Measures accessibility |
|
Uncoordinated Decisions |
Whether transport and land use decisions are coordinated to support strategic regional objectives. |
Not considered a problem |
Considered a problem, and addressed when possible. |
|
Generated Traffic |
Whether modeling and planning take into account the full impacts of generated traffic and induced travel. |
Ignores many components |
Includes all components |
|
Downstream Congestion |
Additional congestion on surface streets that results from increased highway capacity. |
Ignores when evaluating individual projects |
Includes |
|
Consumer Impacts |
Techniques used to evaluate the consumer impacts of changes in the transport system (e.g., improved travel options, mode shifts, pricing). |
Travel time changes |
Consumer surplus analysis |
|
Vehicle Costs |
Whether all vehicle costs and savings are considered when evaluating options that affect automobile mileage, including long-term costs. |
Only considers short-term operating costs |
Includes all affected vehicle costs |
|
Parking Costs |
Whether parking costs are considered, including costs borne by motorists, businesses and governments. |
Only if paid by motorist |
Includes |
|
Construction Impacts |
Whether increased congestion delays during construction periods are considered in evaluation. |
Ignores |
Includes |
|
Impacts on Nonmotorized Travel |
Whether impacts on the accessibility, convenience, safety, comfort and cost off walking and cycling are considered. |
Ignores |
Includes |
|
Impacts on Transportation Diversity |
Whether impacts on the quantity and quality of travel options (particularly those used by non-drivers) are considered. |
Limited analysis |
Comprehensive analysis |
|
Environmental Impacts |
Impacts on air, noise and water pollution; greenspace preservation and community livability. |
Limited analysis |
Comprehensive analysis |
|
Impacts on Land Use |
The degree to which each option supports or contradicts strategic land use objectives. |
Ignores |
Includes |
|
Equity Impacts |
The degree to which each option supports or contradicts community equity objectives. |
Limited analysis |
Comprehensive analysis |
|
Safety and Health Impacts |
Impacts on traffic safety, personal security and public health. |
Per vehicle-mile crash risks |
Per-capita health risks |
This table summarizes differences between conventional and comprehensive transportation planning.
Conventional transportation evaluation tends to undervalue TDM programs because it ignores or understates some costs of automobile travel, and some benefits of a more efficient and diversified transportation system. A conventional analysis framework will often indicate that highway capacity expansion is the best solution to traffic problems, while a more comprehensive framework will favor a TDM solution.
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Optimization Optimization refers to solutions that provide the best balance between multiple, conflicting objectives. Transport planning is sometimes reductionist (evaluation that considers just one or two objectives), which can result in non-optimal solutions that may make society worse overall. For example, decision-makers overwhelmed by the perceived complexity of considering multiple planning objectives sometimes ask planners to focus on just one or two problems. This can result in decisions that address certain problems (such as congestion or pollution) which exacerbate other problems (such as accidents and inadequate mobility for non-drivers), and tends to undervalue solutions that provide multiple benefits. More comprehensive optimization tends to be best for society overall. |
This section describes several special issues to consider when evaluating TDM.
TDM evaluation is affected by the scope of analysis. For example, Tal (2008) describes how less sophisticated analysis exaggerated the potential VMT reduction impacts of Telework. Earlier analysis simply asked, “What portion of employees can telecommute?”, but over time the analysis became more sophisticated, taking into account more variables that affect the total vehicle travel reductions, as illustrated below:
|
Who Can? |
Who Wants To? |
Who Will? |
How Often? |
How Long? |
How Far? |
Will it stimulate travel? |
Will it stimulate sprawl? |
More comprehensive analysis, which takes into account more of these factors, tends to provide more accurate predictions of travel impacts, and therefore benefits.
The most effective TDM programs usually include a combination of positive incentives (sometimes called “carrots” or “sweeteners”) and negative incentives (called “sticks” or “levelers”). When implemented together they tend to have synergetic impacts (their total impacts are greater than the sum of their individual impacts), so it is important to evaluate a TDM program as a package, rather than each strategy individually. For example, Parking Cash Out and a Rideshare program at a worksite might individually only reduce commute trips by 5%, but if implemented together as part of a Commute Trip Reduction program, they may reduce 20% of trips. The entire program should be evaluated rather than the individual strategies.
Use care when calculating the cumulative impacts of several strategies. Total impacts are multiplicative not additive, because each additional factor applies to a smaller base. For example, if one strategy (e.g., parking pricing) reduces automobile trips by 20%, and a second strategy (e.g., improved transit service) reduces driving by an additional 15%, their combined effect is calculated 80% x 85% = 68%, a 32-point reduction, rather than adding 20% + 15% = 35%. This occurs because the 15% reduction applies to a base that is already reduced 20%. If a third strategy (e.g., an aggressive marketing program) reduces demand by another 10%, the total reduction provided by the three factors together is 38.8% (calculated as 100% - [80% x 85% x 90%] = 100% - 61.2% = 38.8%), not 45% (20% + 15% + 10%).
Conventional transportation planning and investment Models often evaluate economic impacts by assigning standard values to travel time, which assumes that any increase in travel time represents a cost to consumers, and any reduction in travel time represents a benefit. They assume that consumers must be worse off whenever they travel slower. This ignores consumer preferences, that is, the possibility that travelers may sometimes prefer slower modes.
For example, many people enjoy walking and cycling and will chose them for some trips, despite their slower speed. Consumers sometimes consider time spent walking and cycling a benefit rather than a cost, as indicated by the popularity of recreational walking and cycling. Similarly, some people prefer ridesharing or transit because they find it less stressful than driving. Yet, many transportation models assume that such shifts harm consumers, because of their slower speed.
The assumption that any mode shift increases consumer costs is clearly incorrect for strategies that rely on positive incentives, such as Transit Improvements, Walking and Cycling Improvements and Parking Cash Out. These strategies give consumers better transport options or financial rewards for using alternative modes, but those who continue driving are no worse off. As a result, travelers only change mode if they are directly better off overall.
Evaluation practices that treat any increase in travel time as a consumer cost tend to favor transportation improvements that increase vehicle mobility, and undervalue TDM strategies that improve transportation options or reward to people who shift mode.
Accurate TDM evaluation requires a consumer surplus based evaluation model, which is a method of measuring the value that consumers place on a change in the price or quality of the goods they consume (in this case travel is considered a good). The basic technique for evaluating consumer impacts of price changes is to use the incremental cost to consumers who don’t change their travel, plus half the change in price times the number of trips that increase or decrease, known as the rule of half, which represents the midpoint between the old price and the new price (EEB, 1994; Small, 1999).
For example, if a $1 highway toll increase causes annual vehicle trips to decline from 3 million to 2 million, the reduction in consumer surplus (the total net cost to consumers) is $2,500,000 ($1 x 2 million for existing trips, plus $1 x 1 million x ½ for vehicle trips foregone). Similarly, if a 50¢ per trip transit fare reduction results in an increase from 10 million to 12 million annual transit trips, this can be considered to provide $6 million in consumer surplus benefits (50¢ x 10 million for existing trips, plus 50¢ x 2,000,000 x ½ for added trips). Consumer surplus impacts of transportation changes that do not involve pricing are more difficult to measure, but can be evaluated using market surveys and other techniques that reveal consumer preferences.
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Explanation of the “Rule of Half” Economic theory suggests that when consumers change their travel in response to a financial incentive, the net consumer surplus is half of their price change (called the rule of half). This takes into account total changes in financial costs, travel time, convenience and mobility as they are perceived by consumers.
Let’s say that the price of driving (that is, the perceived variable costs, or vehicle operating costs) increased by 10¢ per mile, either because of an additional fee (e.g., paid parking) or a financial reward, and as a result you reduced your annual vehicle use by 1,000 miles. You would not give up highly valuable vehicle travel, but there are probably some vehicle-miles that you would reduce, either by shifting to other modes, choosing closer destinations, or because the trip itself does not seem particularly important.
These vehicle-miles foregone have an incremental value to you, the consumer, between 0¢ and 10¢. If you consider the additional mile worth less than 0¢ (i.e., it has no value), you would not have taken it in the first place. If it is worth between 1-9¢ per mile, a 10¢ per mile incentive will convince you to give it up – you’d rather have the money. If the additional mile is worth more than 10¢ per mile, a 10¢ per mile incentive is inadequate to convenience you to give it up – you’ll keep driving. Of the 1,000 miles foregone, we can assume that the average net benefit to consumers (called the consumer surplus) is the mid-point of this range, that is, 5¢ per vehicle mile. Thus, we can calculate that miles foregone by a 10¢ per mile financial incentive have an average consumer surplus value of 5¢. A $100 increase in vehicle operating costs that reduces automobile travel by 1,000 miles imposes a net cost to consumers of $50, while a $100 financial reward that convinces motorists to drive 1,000 miles less provides a net benefit to consumers of $50.
Some people complicate this analysis by trying to track changes in consumer travel time, convenience and vehicle operating costs, but that is unnecessary information. All we need to know to determine net consumer benefits and costs is the perceived change in price, either positive or negative, and the resulting change in consumption. All of the complex trade-offs that consumers make between money, time, convenience and the value off mobility are incorporated. |
Evaluation should be based on incremental (also called marginal) impacts. For example, the congestion reduction benefit of a shift from driving to bus transit is the difference in congestion impacts for automobile travel and bus travel. The parking cost savings of Park & Ride is the difference in cost between a parking space at the worksite and at the urban fringe.
Determining incremental costs requires defining the Base Case, meaning what would happen without the policy or program. For example, when evaluating an HOV Lane, the Base Case could either be no additional lane, or an additional general-use lane. Similarly, when evaluating Road Pricing, the Base Case could either the same road capacity provided with a different funding source, less road capacity, or something in between. It is important that the Base Case be explicitly described in any analysis, and all incremental savings or costs be identified.
Net benefits of a shift from driving to alternative modes (ridesharing, transit, cycling or walking) include the savings from reduced car travel minus any incremental costs from the alternative mode. Conventional transportation evaluation often overlooks some categories of Vehicle Costs, such as mileage-based depreciation, which understates the consumer savings that result from reduced automobile use. Some TDM strategies such as Transit Improvements and Carsharing allow some households to reduce their vehicle ownership, providing additional savings. As a result, actual consumer savings from reduced vehicle use are two or three times greater than typically recognized in conventional transportation economic evaluation.
Incremental costs depend on whether or not a particular trip requires additional system capacity, such as additional road space, parking space, or additional vehicles. This often depends on whether that trip occurs during peak periods (when there is no additional capacity) or off-peak periods (when additional capacity is available).
The marginal cost of Ridesharing is nearly zero if a vehicle has an extra seat that would otherwise travel empty (there is a small increase in fuel consumption and emissions). The incremental cost increases if the rideshare vehicle must driver out of its way to pick of riders, or if a larger vehicle (e.g. a van) is purchased just to carry passengers. Similarly, if a Transit system has excess capacity, shifts from driving to transit may have minimal incremental cost. However, if increased ridership requires additional vehicle capacity or results in uncomfortably crowded transit vehicles, the incremental costs are greater.
Similarly, if a traveler already has a suitable bicycle, the marginal cost of a shift from driving to cycling will be small, consisting of just a couple cents per kilometer for tire replacement and maintenance. However, if consumers must purchase or refit a bicycle, the costs are higher.
The costs of projects intended primarily to increase capacity and reduce congestion should be allocated to peak-period users, because additional capacity is not needed during off-peak periods. If roadway projects also improve off-peak traffic speeds, safety or convenience, then that portion of project costs can be charged to off-peak users.
Incremental costs can also take into account the impacts of alternative uses of consumers’ time and money. For example, the net savings of Telework are reduced if telecommuters take additional mid-day vehicle trips to run errands and socialize, or if they consume additional energy to heat and cool their homes during the day. Similarly, if automobile cost savings allow consumers to spend more money on other socially and environmentally harmful goods or services, net benefits may be smaller than predicted. However, since urban-peak automobile travel tends to have greater costs than most other consumer activities, mobility management usually provides net benefits overall.
TDM strategies, like most economic programs, will eventually have diminishing marginal benefit. There is an optimal level of implementation, beyond which incremental costs exceed incremental benefits. TDM programs need to track these incremental impacts and limit such programs. For example, Ridesharing programs may be extremely cost effective when properly implemented, but once the potential rideshare market is satisfied there will be little additional benefit from simply expanding a rideshare program, for example, by sending out more promotional material. Instead, further expansion may require implementation of additional TDM strategies, such as Commuter Financial Incentives, to expand the size of the market. Similarly, Cycling improvements can be cost effective where there is latent demand for this mode, but that does not mean that it is unnecessary to carefully evaluate investments in bikepaths to insure that they are cost effective; there may be better ways to support cycling, such as Education and Encouragement programs.
The apparent value of a TDM program or strategy can be affected by the perspective and scale of analysis. For example, a comprehensive Commute Trip Reduction program might reduce vehicle trips at participating worksites by 20%, representing 50% of downtown employees, where 10% of regional employees are located. Commute trips usually represent the majority of peak-period highway travel, but only about a third of total automobile travel. As a result, this program could be described as reducing 20% of trips a participating worksites, 10% of downtown commute trips, 2% of regional peak-period highway travel, or less than 1% of total regional travel. From a regional perspective the program may seem of little significance, although a major investment to increase highway capacity typically affects a similar portion of trips. As a result, it could be considered equal in value to multi-billion dollar expenditures on new roads and parking facilities, and it may be the most cost effective regional transport investment available.
When evaluating transportation policies and programs it is usually best to consider all impacts, regardless of where they occur. Impacts within a particular area or analysis period may be highlighted, but costs and benefits that occur outside the jurisdiction should not be ignored. For example, a community’s TDM program may help alleviate traffic congestion and parking demand in an adjacent town. These additional benefits should be mentioned even if they are not the primary consideration in decision making, since such benefits may justify support from other levels of government.
It is important to present analysis results in units that are easy to understand and compare. For example, costs and benefits can be measured in annualized dollars per capita, per vehicle, per additional passenger-trip, per vehicle-mile, per passenger-mile or per ton-mile of freight. This is easier for most people to interpret than the extremely large numbers that often result from economic analysis. For example, a road or transit project might be predicted to cost $376.8 million, and provide $124 million in Net Present Value. These numbers are beyond most people’s comprehension. It is better to convert them to dollars per resident, per passenger-trip or per passenger-mile.
Since some TDM strategies reduce average trip distances or reduce the total need to travel, the best unit to use for evaluating TDM is usually the passenger-trip. This reflects an emphasis on access, rather than treating mobility as an end in itself (Measuring Transportation). For example, Smart Growth and Telework reduce the amount of travel needed for errands and commuting, providing savings per passenger-trip, although travel costs per passenger-mile may stay the same or even increase. Units often used in conventional transportation evaluation that emphasize vehicle mobility (e.g., roadway level of service, vehicle traffic volumes and speeds) tend to undervalue alternative modes and demand management solutions to transportation problems.
The units used for evaluation should reflect marginal costs and benefits. For example, roadway capacity expansion project should be evaluated in terms of costs per additional peak-period unit of travel (vehicle-trip, passenger-trip, vehicle-mile) rather than assigning the cost to all road users, including off-peak travelers who do not directly benefit (although improved safety or other benefits to off-peak travelers should be assigned to those users).
People involved in economic analysis should understand the difference between accuracy and precision (Shoup 2003). Accuracy refers to the correctness of information. Precision refers to the level of detail in measurements. A measurement can be very precise but inaccurate. With modern computers it is possible to calculate analysis at a far greater degree of precision that is justified by the source data accuracy.
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“Not everything that can be counted counts, and not everything that counts can be counted.” -Albert Einstein |
The effects of TDM programs and strategies tend to change over time. Some TDM programs have immediate impacts while others may take years to have significant effects. In general, strategies that incorporate financial incentives, improve transportation choice or involve land use management tend to become more effective over time as consumers incorporate them into long-term decisions. On the other hand, the effects of programs that attempt to change travel behavior by appealing to people’s good intentions (or guilt) tend to decline over time as promoters and participants lose interest.
It is important to differentiate between resource costs and economic transfers. Resource costs reduce the total supply of a scarce resource. Economic transfers shift resources from one person or group to another. For example, traffic crashes cause economic costs (i.e., damage to vehicles and people). Parking Pricing is primarily an economic transfer, since payments by motorists are revenue to the parking facility owner.
Conversely, when an employer provides financial incentives to commuters who use alternative modes, this cost to employers is offset by the economic benefit to the commuters who receive additional money. The true resource costs of such programs are any transaction and enforcement costs, such as administrative and policing expenses, and any additional inconvenience to users, such as the time required to make a payment. When evaluating TDM programs that involve pricing it is important to take into account both the costs (payments) and the benefits (revenue) of these economic transfers. Of course, such costs and benefits are very real and important to the individuals who pay or receive them, and have important equity impacts that must be considered, as described later.
Conventional traffic Models often use simplified travel time cost functions which assumes that any shift from driving to an alternative mode increases travel time costs. This is wrong for two reasons. First, alternative modes are sometimes as fast as driving. Cycling is often as fast as driving for short trips, door-to-door. Ridesharing and transit are sometimes faster than driving with grade separated systems or HOV Priority.
Second, consumers do not always consider additional travel time a cost. The value that people assign to travel time is highly variable, depending on factors such as comfort and enjoyment. For example, some people prefer transit or rideshare travel to be less stressful than driving in traffic. Other people enjoy walking or bicycling for recreation and exercise, and will choose these modes even if the trips take longer. In other words, consumers sometimes consider time spent travel by alternative modes to have a lower cost per minute than driving.
If a positive incentive (such as a Transit Improvements, Pedestrians and Cycle Improvements or Parking Cash Out) induces consumers to shift from driving to an alternative mode, they must be directly better off or they would not make the change.
For this reason, newer transport cost Models use consumer surplus analysis to measure the incremental costs and benefits of travel changes. This techniques estimates net benefits and costs to consumer based on their willingness-to-pay (Small, 1999). This is a far more accurate way to measure economic impacts than traffic models that use general assumptions about travel time costs.
Transportation Demand Management tends to support economic development by increasing transportation system efficiency and shifting consumer expenditures to goods that provide more local employment and business activity (TDM and Economic Development). Many TDM strategies can increase economic efficiency and productivity because they reflect Market Principles. This is not to say that all TDM programs increase economic development, but choosing TDM policies and strategies that reflect market principles can provide additional economic benefits that are not usually reflected in conventional economic analysis.
For example, funding road and parking facilities with user charges tends to be more efficient and fair than indirect funding, and variable fees that increase during congested periods are more efficient and equitable than flat fees. Similarly, strategies that improve transport choice (particularly improvements to Basic Mobility) can provide broad economic benefits that may be difficult to measure. Economic analysis should indicate how a proposed policy or program impacts market principles and economic development objectives.
Various techniques can be used to Model the economic impacts of a particular transportation policy or project, including transportation-land use models, benefit-cost analysis, input-output models, economic forecasting models, econometric models, case studies, surveys, real estate market analysis and fiscal impact analysis (Weisbrod 2000; O’Fallon 2003).
The transportation improvement objectives used in the Encyclopedia were selected to reflect different perspectives and priorities. For example, one planning process or stakeholder group may be most interested in congestion reduction and safety benefits, while another may be most concerned with consumer choice and environmental protection. As a result, the categories that are used are not mutually exclusive: they may overlap. For example, traffic congestion reduction is an objective in itself and can also affect environmental protection, road safety and community livability. If a benefit-cost analysis is used it is important to take such overlaps into account to avoid double-counting.
Transportation planning frequently involves a choice between highway or parking facility capacity expansion, and a TDM solution. Below are some common errors that made when evaluating and comparing such options.
· Ignoring parking costs. Economic analysis of highways often ignores parking cost savings when calculating the benefits of reduced driving (Parking Pricing). This underestimates the financial benefits to consumers of using alternative modes.
· Ignoring vehicle ownership and distance-based depreciation costs. Transportation economic Models often consider only out-of-pocket costs such as fuel, tolls and parking fees when calculating the cost of driving (Transportation Costs & Benefits). This underestimates the financial benefits to consumers of using alternative modes.
· Ignoring safety benefits. Economic analysis often ignores potential reductions in crash costs that result from reduced driving (Safety Impacts of TDM). This underestimates the benefits to society of using alternative modes.
· Comparing average rather than marginal costs. When comparing automobile and transit investments to address urban transportation problems, some analysts use overall average costs. But automobile costs are much higher than average in urban conditions, while public transit service tends to be most cost effective in these conditions due to economies of scale.
· Ignoring generated traffic impacts. Failure to consider the effects of generated traffic tends to overstate the benefits of highway capacity expansion and understate the benefits of TDM solutions, particularly pricing strategies (Rebound Effects).
· Ignoring impacts on non-drivers. Transportation planning is often made primarily from a motorist’s perspective, with little consideration of impacts on non-drivers. The negative impacts of increased vehicle traffic and automobile-oriented land use are often ignored (see Evaluating Nonmotorized Transport).
· Ignoring transportation choice benefits. There are several benefits to having a diverse and balanced transportation system, some of which are difficult to measure (Evaluating Transportation Options). Conventional transportation evaluation tends to undervalue such benefits. TDM evaluation that has the sole objective of reducing vehicle travel will also undervalue these mobility benefits (Evaluating Public Transit).
· Ignoring strategic land use objectives. Transportation decisions can have significant impacts on land use (Land Use Impacts on Transportation). Increased road and parking capacity tends to create lower-density, automobile-dependent land use patterns. Transportation planners often ignore strategic land use objectives when evaluating options.
· Treating travel demand as an uncontrollable. Transportation planners often treat demand as a point value rather than a function. For example, they say that vehicle travel is projected to increase by X% over the next decade. Yet, travel demand is affected by prices, land use patterns and other incentives. Expanding roadway system capacity to accommodate projected growth, without considering demand management options, can create a self-fulfilling prophecy of increased Automobile Dependency (Newman and Kenworthy, 1999).
· Ignoring synergistic effects of TDM. A transit option that does not appear justified under current conditions may become cost effective if implemented as part of a coordinated TDM program. For example, a transit service may become more cost effective if implemented with Commute Trip Reduction programs, Congestion Pricing, Parking Management and Location Efficient Development.
· Ignoring congestion impacts. Expanding highway capacity tends to increase downstream traffic Congestion (congestion on surface streets and other highways), which is avoided when travel is shifted to alternative modes. Construction projects often impose significant traffic delay (“Construction Disbenefits” Transport Economics). Increased transit speeds tend to reduce traffic congestion on parallel highways. These impacts are often ignored in transportation project evaluation.
· Mixing equity and efficiency objectives. Alternative modes are subsidized for both equity and efficiency objectives (Evaluating Public Transit). As a result, some improvements to alternative modes may appear inefficient (e.g., off-peak service, accommodating people with disabilities), while others may appear to be inequitable (e.g., premium rail service designed to attract commuters out of their cars).
Logic models are an evaluation framework commonly used in the social sciences (Israel 2001). They use diagrams that show the major components of a program, with arrows illustrating relationships between input, outputs and outcomes. Logic models also include a narrative that explains the relationships between these components and identifies external factors that can affect the program's effectiveness. A Logic Model helps answer questions such as, “What is this program trying to achieve and why is it important?” and “How will we measure effectiveness?” The answers can help meet accountability requirements and identify ways to improve the program.
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Inputs What we invest |
==> |
Outputs What we do; Who we reach |
==> |
Outcomes What difference it makes |
The steps involved in creating such a framework are described below.
1. The first step is to describe the problem that the program is intended to address and collect information about it. It is important to understand the problem from clients’ perspective and factors that affect the problem. For example, traffic risk can be evaluated in several different ways which give very different conclusions about the nature of the problem (Safety Evaluation). It can be measured per vehicle-mile, per passenger-mile, per motor vehicle, or per capita. Crash costs can be quantified based only on direct monetary losses, or including indirect and non-market costs. Traffic risk can be viewed from the perspective of vehicle drivers, vehicle passengers, cyclists and pedestrians. It can be viewed in terms of risk borne, risk imposed, or total risk. Many factors affect the degree of traffic risk, including vehicle type, demographics, driver behavior, roadway design and travel conditions, all of which must be understood for effective planning and evaluation.
2. The second step is to identify the major components of the program’s outcomes, including long-, medium- and short-term effects. Long-term outcomes might include changes in social, economic, and environmental conditions. For example, one long-term, social outcome for a traffic safety program is improved public health (fewer injuries) in an area. A long-term, economic outcome might be a reduction in health care costs.
Intermediate outcomes usually include the adoption of best management practices (BMPs) and appropriate technologies, and combinations or sets of practices and technologies. For example, a traffic safety program might include various management strategies to reduce high risk driving behavior and increase the use of safety equipment. Short-term outcomes may be changes in knowledge, attitudes, and skills, such as increased public awareness of the benefits of reducing high-risk behavior (not driving drunk, controlling traffic speeds) and using safety equipment (seatbelts, child restraints and bicycle helmets).
For many programs, some audience segments may have outcomes different from other groups. This is because needs vary: one group of clients need information on one topic, a second group needs information on a related but different topic, and a third group may need information on an array of topics. In this situation, developing a logic model for each group can help focus the program to deliver the needed information to the appropriate group.
3. The third step in creating a logic model is to organize the outcomes in a sequence or chain of events and to identify external factors which can hinder or facilitate the program. This reflects expectations about cause and effect relationships between program activities and short-term, intermediate and long-term outcomes. For some programs, the linkage between program activities and outcomes also may include feedback loops.
4. The fourth step in developing a logic model is to specify the process theory. The process theory has two main components: the program's service utilization plan and its organizational plan. The service utilization plan is a flowchart that shows how clients (or specific groups of clients) become engaged in the program's activities. The key idea is to describe how the program involves the client from his or her perspective. This includes indicating the initial contact with the client to recruit him or her to participate in the program, the set of activities through which the client obtains information, and follow-up activities which reinforce the educational process and encourage adoption of BMPs and technologies. The service utilization plan should answer the question about whether the program engages the client in a way that is sufficient to initiate the sequence of outcomes specified in the impact theory.
The program's organizational plan includes the major components or factors involved in the program. It also indicates how resources (e.g., curriculum, publications, expense money, specialized equipment, and personnel) are obtained and deployed, as well as relationships among key actors. Having adequate resources and an effective organization are important factors in delivering a high quality program to clients. These details should be identified in an accompanying narrative. In sum, the development of the process theory can be used as a blueprint for the plan of action. It identifies which faculty are to conduct specific activities and what sequence of activities should be conducted.
The fourth step is the review and consultation process. Though the initial development of logic models can be quickly completed by a small group of individuals, much can be gained by involving the full membership of design teams, collaborating county and state faculty, interested administrators, and external peers. Broad-based involvement helps to ensure that the model is correctly specified and based on relevant research. More importantly, participants will be more likely to share a commitment to the program's objectives and activities, even if these may lie outside his or her expertise.
For logic models to serve a useful function, it is important to begin by specifying the program's desired outcomes and then work back. Starting with the program's current activities can lead to maintaining the status quo instead of engaging in a careful, research-based discussion of the rationale for the program. Creating a logic model helps faculty to focus the educational program on generating outcomes for clients and including the necessary components for their attainment. With the completion of a detailed logic model, faculty can be confident that their efforts will be effective and their resources well spent. The time spent developing a logic model should be viewed as an investment rather than an expense. Given the public's expectations for performance, faculty can ill afford not to use logic models as a tool for program planning.
Conventional transport planning tends to use a reductionist approach that attempts to identify one or two best solutions to an individual problem, often with little consideration to indirect impacts, as illustrated in Table 5.
Table 5 Conventional Evaluation
|
|
Congestion |
Parking |
Crashes |
Pollution |
|
Conventional Solutions |
|
|
|
|
|
Roadway capacity expansion |
X |
|
|
|
|
Parking capacity expansion |
|
X |
|
|
|
Crash-resistant vehicles |
|
|
X |
|
|
Vehicle emission controls |
|
|
|
X |
|
TDM Strategies |
|
|
|
|
|
Road pricing |
X |
|
|
|
|
Parking management |
|
X |
|
|
|
PAYD insurance |
|
|
X |
|
|
Emission pricing |
|
|
|
X |
Conventional planning tends to evaluate individual problems and solutions. For example, roadway capacity expansion and road pricing are considered solutions to congestion problems, parking capacity expansion and parking management are considered solutions to parking problems, crash-resistant vehicles and PAYD Insurance are considered solutions to crash costs, and vehicle emission controls and emission pricing are considered solutions to pollution problems.
Table 6 illustrates a more comprehensive evaluation approach. It shows that conventional solutions, such as roadway and parking facility capacity expansion, crash-resistant vehicles and emission controls generally only help solve one or two problems at a time. In fact, they sometimes exacerbate other problems by increasing total automobile travel (Litman, 2004). On the other hand, TDM strategies often provide multiple benefits because they reduce total vehicle travel. Although individually their impacts may appear modest, a comprehensive TDM program that includes a variety of complementary strategies can have a significant impact on total travel, providing significant overall benefits.
Table 6 Comprehensive Evaluation
|
|
Congestion |
Parking |
Crashes |
Pollution |
|
Conventional Solutions |
|
|
|
|
|
Roadway capacity expansion |
X |
|
|
|
|
Parking capacity expansion |
|
X |
|
|
|
Crash-proof vehicles |
|
|
X |
|
|
Vehicle emission controls |
|
|
|
X |
|
TDM Strategies |
|
|
|
|
|
Road pricing |
X |
X |
X |
X |
|
Parking management |
X |
X |
X |
X |
|
PAYD insurance |
X |
X |
X |
X |
|
Emission pricing |
X |
X |
X |
X |
Comprehensive evaluation takes into account additional benefits that can result from TDM strategies that reduce total motor vehicle travel. As a result, their total benefits are greater than indicated by conventional planning practices.
For information on how to apply transportation economic evaluation see Schreffler 2000; Litman 2001 and 2006; ACT 2001; ICF Consulting and CUTR 2005; and NZTA 2010. Below is a list of best practices for accurate TDM evaluation.
· Use best current transport Modeling practices.
· Use Accessibility as the ultimate goal of transportation improvements, rather than treating mobility as an end in itself. This allows consideration of the widest possible range of solutions to transportation problems, including mobility substitutes and land use management that reduces the need for physical travel.
· Clearly define the Base Case and alternatives that are used to calculate incremental costs and benefits.
· Carefully define incremental costs. Identify the marginal costs of driving and alternative modes. Assign roadway capacity expansion costs only to peak-period vehicle users.
· Use comprehensive estimates of costs and benefits, including indirect and long-term impacts. This should include all road and parking expenses, downstream congestion, impacts on nonmotorized transport, vehicle ownership costs, environmental impacts, impacts on travel choice and strategic land use objectives.
· Present results in units that are easy to understand and compare. For example, present costs and benefits in annualized dollars per capita, per vehicle, per vehicle-mile, per passenger-mile, or per additional vehicle trip.
· Indicate any impacts that are not quantified in the analysis because they are difficult to measure, and describe their impacts qualitatively. For example, describe how each option impacts equity objectives, economic development, and strategic land use goals.
· Use consumer surplus analysis rather than travel-time cost values to calculate consumer impacts of changes in route, mode and trip frequency. Do not assume that reduced mobility or travel speeds resulting from a voluntary change in travel patterns reflects increased consumer costs.
· Incorporate generated traffic impacts.
· Indicate the distribution of benefits and costs, and evaluate impacts in terms of equity objectives.
· Use sensitivity analysis and other statistical techniques to explicitly incorporate uncertainty and variability in economic analysis.
· Describe how different perspectives and assumptions could effect analysis conclusions.
· Produce reports that are understandable to a general audience and include all relevant technical information.
|
According to Einstein’s theory, our perception of every other object in the universe is relative to our own movement. Motorists demonstrate this every day: An idiot is somebody who drives faster than you. A moron is somebody who drives slower than you. |
The European Transport Innovation Deployment for Europe (TIDE) project aims to create improved conditions for cities and regions to integrate innovations in their urban mobility policies. This should lead to increased acceptance and take–up of new urban transport solutions and technologies. TIDE helps cities and regions to address common challenges in a collaborative and integrated way.
TIDE focuses on increasing awareness, advancing expertise using existing and new tools, through practical work with cities, and by assessing costs and benefits. Focusing on the needs of transport professionals in European cities is a guiding principle. TIDE actively supports 15 committed cities to develop implementation scenarios for innovative urban transport measures, setting the example for an even wider group of take–up candidates. These measures cover the following five TIDE– themes: new pricing measures, non–motorised transport, advanced network and traffic management to support traveller information, electric mobility and public transport organisation.
Table 7 illustrates the types of impacts considered.
Table 7 Evaluation Impacts
|
Impacts |
Comments |
Data Type |
|
Investment costs |
Should be quantified. |
Quantified |
|
Maintenance costs |
Potential for costlier maintenance (e.g. gardening, street furniture maintenance). This is easy to quantify. |
Quantified |
|
Livability |
An important, but difficult to quantify, effect. Experts and stakeholders can estimate the potential effects, or surveys can be carried out. |
Qualified |
|
Land value |
Land prices and rents may be affected; quantification is likely to be difficult ex–ante. Should be assessed qualitatively. Quantitative data may be available ex–post in the long–term. |
Qualified |
|
Retail turnover |
Similar to ‘land value’, but with a more direct impact. |
Qualified |
|
City image |
The cities attractiveness and image for locals and visitors may be improved. |
Qualified |
|
Accidents |
Traffic calming or modal separation can reduce the number and/or severity of accidents. |
Qual./ Quant. |
|
Health |
Positive health effects can be expected due to an increased level of physical activity |
Qualified |
|
Social integration |
Public spaces can improve communication and enhance community life of different socio–cultural groups. |
Qualified |
|
Local air quality |
Greening of an area or water elements like fountains can positively affect the local air quality and climate |
Qualified |
|
Modal shift |
Walking, cycling and public transport use may increase. If considerable effects are expected, other effects might be relevant (e.g. local air pollution, GHG emissions, public transport patronage, etc.) and should be included as separate effects. |
Qual./ Quant. |
|
Side effects |
Potential side effects such as travel–time increase, congestion effects, reduced parking spaces etc. should also be assessed. |
Qual./ Quant. |
Conventional planning tends to evaluate individual problems and solutions. For example, roadway capacity expansion and road pricing are considered solutions to congestion problems, parking capacity expansion and parking management are considered solutions to parking problems, crash-resistant vehicles and PAYD Insurance are considered solutions to crash costs, and vehicle emission controls and emission pricing are considered solutions to pollution problems.
The New Integrated Smart Transport Options (www.nisto-project.eu) is a European Union sponsored project to implement and test innovative transportation demand management strategies. The NISTO Toolkit (www.nistotoolkit.eu) provides a framework for evaluating small-scale mobility management projects using multi-objective analysis.
The Toolkit consists of two online evaluation tools for the assessment of sustainability and stakeholder preferences. In addition to them, guidance documents are provided on the use of these tools, target monitoring and converting data collected by smartphones or other sensors into indicators that can be used for the evaluation. The online evaluation tools and the documentation are accessible on the website www.nistotoolkit.eu.
The Toolkit has been designed for transport planners, local and regional authorities, researchers and non-governmental organisations who want to appraise different options to solve a mobility-related problem in the urban or regional context. It is particularly suited for the early assessment of alternatives when detailed data is not yet available about the impacts of the interventions. The evaluation tools provide a ranking of the alternative solutions based on a set of sustainability criteria and the stakeholders’ preferences using the PROMETHEE1 method. These rankings can guide decision-makers when taking a decision for one of the options. The tools therefore do not take over the responsibility of taking the decision itself. The rankings suggested are not ultimate, since considerations that are not covered by this toolkit (e.g. politics, duration of the implementation, synergies with other projects or plans) may also be relevant for the decision-makers.
Ker (2003) investigated the cost effectiveness of community-based programs that promote travel behavior change. He found that such programs can be highly-effective in increasing public transport use, as well as use of other alternatives to the private car. The majority of these increases have been off-peak, so do not require investment in additional public transit infrastructure or vehicles. However, some system improvement at the same time has been demonstrated to improve the impact of travel behaviour change programs on the level of public transport use.
Community/household-based travel behaviour change interventions have consistently delivered 15 to 40 additional public transport trips per person per year, across the whole target population, irrespective of the current level of public transport usage. In relative terms, the highest proportionate gains in public transport mode share have been where the existing mode share was low. This level of behaviour change will typically generate sufficient additional fare revenue to recover the full cost of the intervention in two to five years. In the specific case of Melbourne, the payback period is estimated to be around 0.8 to 1.0 years, with a range of 0.5 to 2.1 years. The full durability of Individualised Marketing impacts has been demonstrated for up to four years, which gives a very high level of certainty that a positive financial return from fares will be achieved, even if some additional investment in capacity is required. No such cost has been included in the evaluation as it is intended to target the Individualised Marketing program to areas with spare transit capacity and 80% of the increase in use occurs off-peak, when capacity is most readily available.
Even where additional capacity might be required, voluntary travel behaviour change is a highly cost-effective means of achieving progress towards Government strategy targets of reduced dependence on cars and increased use of public transport and other non-car travel options.
There are also substantial financial benefits to government beyond public transport, most particularly through reduced demand for additional road system capacity and lower health service costs. These alone have been estimated to have a value of between 1.6 and 3.2 times the initial investment in travel behaviour change.
Community/household-based travel behaviour change interventions have been very positively regarded by those who participate and have delivered substantial improvements in public perceptions of public transport, including changes that have occurred in recent years. In turn, these improved perceptions have been reflected in higher anticipation of further improvements.
A key step toward more comprehensive and multi-modal transportation planning is the development of practical indicators of walking, cycling and public transit travel conditions, which can be used to identify potential problems and evaluate potential improvements. Below are specific examples of multi-modal performance indicators.
· The Transit Capacity and Quality of Service Manual (www.trb.org/main/blurbs/169437.aspx) provides guidance on Evaluating Public Transit service quality, including factors such as availability, frequency, travel speed, reliability, safety and security, price and affordability, network and system integration, comfort, accessibility, baggage capacity, universal design, user information, courtesy and attractiveness.
· The 2010 Highway Capacity Manual (the main reference guide for evaluating roadway system performance) created urban roadway LOS ratings for various modes, including walking, cycling, public transit and automobile (Dowling, et al. 2008; Elias and Parks 2013).
ú Cycling LOS takes into account the availability of parallel bicycle paths, the number of unsignalized intersections and driveways (because they create conflicts between cyclists and other vehicles), width of outside through lane or bicycle lane (the degree of separation between bicyclists and motor vehicle traffic), motor vehicle traffic volumes and speeds, portion of heavy vehicles (large trucks and buses), the presences of parallel parked cars, grades (hills), and special conflicts such as freeway off-ramps.
ú Pedestrian LOS takes into account pedestrian facility crowding, the presence of sidewalks and paths, vehicle traffic speeds and volumes, perceived separation between pedestrians and motor vehicle traffic (including barriers such as parked cars and trees), street crossing widths, extra walking required to reach crosswalks, average pedestrian crossing delay (time needed to wait for a gap in traffic or a crosswalk signal), and special conflicts such as multiple free right-turn lanes (which tend to be difficult for pedestrians to cross).
· WalkScore (www.walkscore.com) calculates the walkability of a location based on proximity to public services such as stores, schools and parks. However, it does not consider any other factors, such as the presence or quality of walking and cycling facilities (sidewalks, paths, crosswalks, etc.) or the ease of crossing streets (the presence of crosswalks, road widths, traffic volumes and speeds, etc.), or the quality of the pedestrian environment.
· The Walkability Checklist (www.walkableamerica.org/checklist-walkability.pdf), developed by the Partnership for a Walkable America and the Pedestrian and Bicycle Information Center, provides an easy-to-use form for evaluating neighborhood walkability, taking account factors such as the quality of sidewalks and paths, roadway crossing conditions (crosswalks, and traffic speeds and volumes), the degree of care by motorist, and amenities such as shade trees and street lighting along sidewalks, as perceive by users.
· The Bikeability Checklist (www.walkinginfo.org/cps/checklist.htm) developed by the Pedestrian and Bicycle Information Center includes ratings for road and off-road facilities, driver behavior, cyclist behavior, and barriers, and identifies ways to improve bicycling conditions.
· Neighborhood Bikeability Score (www.ibpi.usp.pdx.edu/neighborhoods.php) is a rating from 0 (worst) to 100 (best) that indicates the number of destinations (stores, schools, parks, etc.) that can be reached within a 20-minute bike ride, taking into account the quality of cycling infrastructure.
Post implementation reviews (PIRs) are conducted every year on a small sample of completed NZTA-funded projects. They allow the agency to compare the planned benefits and costs of a project with the actual outcomes achieved.
Wallis, Wignall and Parker (2012) analyzed the results of PIRs. The research methodology involved:
The results indicate a lack of an overall comprehensive framework to adequately guide pre-implementation appraisal and post-implementation review. New Zealand currently relies on a diverse mixture of individual guidelines, resulting in gaps and inconsistencies in the approach to appraisal and review. This in turn means that a comprehensive understanding of project effects is lacking in many cases. The researchers recommend various modelling, monitoring and evaluation method improvements.
The New Zealand Transport Agency Economic Evaluation Manual includes specific procedures for evaluating a variety of transportation projects, including highways, public transport, non-motorized improvements and demand management strategies. It includes specific values for measuring and monetizing impacts.
The New Jersey Department of Transportation developed an interactive GIS-based tool for calculating network-wide full marginal costs (FMC) of highway transportation in New Jersey. This tool is used to evaluate the short-term impacts of policy implications on the marginal costs of different trips. Application of this model to observe the short-term impacts of capacity investments on several route sections (NJ Route 18, NJ Route 17, NJ Route 3, and the Garden State Parkway) demonstrate that even though capacity investments can reduce the marginal cost of users, the amount of savings mainly depends on the characteristics of that region, the excessive demand that needs to be satisfied, and the reduced congestion delays. This will help planners to estimate the changes in transport costs due to a particular transportation demand management measure or supply change such as adding new lanes or improving existing lanes.
The Rapid Fire Model is a user-friendly spreadsheet-based tool that produces and evaluates statewide, regional, and/or county-level scenarios across a range of metrics. It is intended to be a comprehensive modeling tool to help state, regional, and local agencies and policy makers evaluate climate, land use, and infrastructure investment policies. The model produces results for a range of critical metrics, including:
Results are calculated using empirical data and the latest research. The model constitutes a single framework into which research-based assumptions can be loaded to test the impacts of varying land use patterns. The transparency of the model’s structure of input assumptions makes it readily adaptable to different study areas, as well as responsive to data emerging from ongoing technical analyses by state and regional agencies. The model can be used to create and test scenarios at the national, statewide, and regional scales.
The report, Evaluation Of Transport Interventions In Developing Countries by Robertson, Jägerbrand and Tschan (2015) investigated methods used to evaluate the effects of transport policies and measures on emissions of greenhouse gases in developing countries. The analyses includes a review of different climate mechanisms, the general availability of methods for evaluation of traffic and transportation, evaluation data availability, and institutional conditions in developing countries. The main conclusions are that measuring traffic and transportation is generally a complex and demanding process, and there is a significant risk of rebound effects, especially for transport capacity expansion projects, and short time frames are often applied for evaluation of project-based mechanisms which undervalue transport sector benefits. Other challenges relate to institutional roles and responsibilities, the availability of personal and financial resources, and the knowledge and perspectives applied. Based on these limitations regarding transport project evaluations, further development of transport-related climate mechanisms towards a more sectoral and transformational perspective is suggested.
The report, Sustaining Nature and Community in the Pikes Peak Region: A Sourcebook for Analyzing Regional Cumulative Effects (CDOT 2003) examines past, present and foreseeable environmental impacts and trends in order to provide a framework for project-level assessment of cumulative effects in the region. The guidebook provides detailed analysis of landscape patterns, water quality and quantity, air quality, noise and visual resources, and guidance on evaluating the impacts of specific projects, particularly those that expand highway capacity.
SPECTRUM is a project funded by the EU as part of Fifth Framework Programme. The main objective of the SPECTRUM project is to: “develop a theoretically sound framework for defining combinations of economic instruments, regulatory and physical measures in reaching the broad aims set by transport and other relevant policies” in terms of efficiency and equity. As there is a tension between managing the transport system in such a way as to minimise social costs and simultaneously managing the system to meet increased demand, the work of SPECTRUM will address this problem by looking at the potential effects of using either individual instruments, complementary packages of instruments, or the consequences of substituting instruments, in managing the transport system.
For more information on the concepts and techniques discussed in this chapter see TDM Planning, Why TDM?, Measuring Transportation, Market Principles, Comprehensive Transportation Planning, Evaluating TDM Equity, Parking Evaluation, Evaluating Pricing Strategies, Evaluating Transportation Choice, Transit Evaluation and Data Collection.
Steve Abley, Paul Durdin and Malcolm Douglass (2010), Integrated Transport Assessment Guidelines, Report 422, Land Transport New Zealand (www.nzta.govt.nz); at www.nzta.govt.nz/resources/research/reports/422.
Brian Alstadt and Glen Weisbrod (2008), Generalized Approach for Assessing Direct User Impacts of Multimodal Transport Projects, Transportation Research Board 87th Annual Meeting (www.trb.org); at www.edrgroup.com/attachments/-01_Alstadt%20Weisbrod%20EDRG-WP2008-04.pdf.
Anvita Arora and Geetam Tiwari (2007), A Handbook for Socio-economic Impact Assessment (SEIA) of Future Urban Transport (FUT) Projects, Transportation Research and Injury Prevention Program (TRIPP), Indian Institute of Technology (http://tripp.iitd.ernet.in); at http://tripp.iitd.ernet.in/publications/paper/SEIA_handbook.pdf.
ATC (2006), National Guidelines for Transport System Management in Australia, Bureau of Transport and Regional Economics (BTRE), Australian Transport Council (www.atcouncil.gov.au); at www.atcouncil.gov.au/documents/NGTSM.aspx#4.
Austroads (2005) Guide to Project Evaluation, Austroads (www.onlinepublications.austroads.com.au/items/AGPE); at www.onlinepublications.austroads.com.au/collections/agpe/guides.
A. Bhasin (2005), Multi-Criteria Analysis for Infrastructure Appraisal, Transportation Research Board 84th Annual Meeting (www.trb.org).
Robert Burchell, et al (1998), The Costs of Sprawl – Revisited, TCRP Report 39, Transportation Research Board (www.trb.org).
Sally Cairns, et al (2004), Smarter Choices - Changing the Way We Travel, UK Department for Transport (www.dft.gov.uk); at www.dft.gov.uk/pgr/sustainable/smarterchoices/ctwwt. This comprehensive study provides detailed evaluation of the potential travel impacts and costs of various mobility management strategies. Includes numerous case studies.
Caltrans (2004), Benefit-Cost Analysis Guide, Office of Transportation Economics, California Department of Transportation (www.dot.ca.gov/hq/tpp/offices/ote/benefit_cost/models/calbc.html).
Cambridge Systematics (2009), Performance Measurement Framework for Highway Capacity Decision Making, Strategic Highway Research Program (SHRP) Report S2-C02-RR, TRB (www.trb.org); at http://sites.google.com/site/shrpc01.
CARB (2010-2011), Research on Impacts of Transportation and Land Use-Related Policies, California Air Resources Board (http://arb.ca.gov); at http://arb.ca.gov/cc/sb375/policies/policies.htm.
CDOT (2003), Sustaining Nature and Community in the Pikes Peak Region: A Sourcebook for Analyzing Regional Cumulative Effects, Colorado Department of Transportation (www.dot.state.co.us).
Center for Transportation Excellence (www.cfte.org) provide research materials, strategies and other resources for evaluating public transportation benefits.
Harry Clarke and David Prentice (2009), A Conceptual Framework for the Reform of Taxes Related to Roads and Transport, School of Economics and Finance, La Trobe University, for the Australia Treasury Australia's Future Tax System review; at http://apo.org.au/research/conceptual-framework-reform-taxes-related-roads-and-transport.
Community Impact Assessment Website (www.ciatrans.net), sponsored by the U.S. Federal Highway Administration, provides information on methods for evaluating the impacts of transportation projects and programs on communities.
College Sustainability Report Card (www.greenreportcard.org) provides in-depth sustainability profiles for hundreds of colleges in the U.S. States and Canada.
CTE (Center for Transportation and the Environment) (2008), Improved Methods For Assessing Social, Cultural, And Economic Effects Of Transportation Projects, NCHRP Project 08-36, Task 66, Transportation Research Board (www.trb.org) and the American Association of State Highway and Transportation Officials (AASHTO); at www.statewideplanning.org/_resources/234_NCHRP-8-36-66.pdf.
CUTR (2007), Economics of Travel Demand Management: Comparative Cost Effectiveness and Public Investment, Center for Urban Transportation Research (www.nctr.usf.edu); at www.nctr.usf.edu/pdf/77704.pdf.
CUTR (2009), Quantifying the Net Social Benefits of Vehicle Trip Reductions: Guidance for Customizing the TRIMMS Model, Center for Urban Transportation Research (www.nctr.usf.edu); at www.nctr.usf.edu/abstracts/abs77805.htm.
Mark Delucchi (2005), The Social-Cost Calculator (SCC): Documentation of Methods and Data, and Case Study of Sacramento, Sacramento Area Council of Governments (SACOG) and the Northeast States for Coordinated Air-Use Management (NESCAUM), UCD-ITS-RR-05-37, (www.its.ucdavis.edu/publications/2005/UCD-ITS-RR-05-37.pdf).
Michelle DeRobertis, John Eells, Joseph Kott, and Richard W. Lee (2014), “Changing the Paradigm of Traffic Impact Studies: How Typical Traffic Studies Inhibit Sustainable Transportation,” ITE Journal (www.ite.org), May, pp. 30-35; at http://tinyurl.com/oc3l8h5.
DfT (2006), Transport Analysis Guidance, Integrated Transport Economics and Appraisal, Department for Transport (www.dft.gov.uk/webtag). This website provides comprehensive guidance on how to identify problems, establish objectives, develop potential solutions, create a transport model for the appraisal of the alternative solutions, how to model highway and public transport, and how to conduct economic appraisal studies that meet DoT requirements.
DfT (2010), National Transport Model, Integrated Transport Economics and Appraisal, Department for Transport (www.dft.gov.uk); at www.dft.gov.uk/pgr/economics/ntm.
DKS Associates (2003), Modeling TDM Effectiveness, Washington Department of Transportation (www.wsdot.wa.gov/Mobility/TDM/520casev1/execsummary.pdf).
Richard Dowling, et al. (2008), Multimodal Level Of Service Analysis For Urban Streets, NCHRP Report 616, Transportation Research Board (www.trb.org); at http://trb.org/news/blurb_detail.asp?id=9470; User Guide at http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_w128.pdf.
Economic Development Research Group (www.edrgroup.com) provides extensive information on economic evaluation methods.
EDRG (2007), Monetary Valuation of Hard-to-Quantify Transportation Impacts: Valuing Environmental, Health/Safety & Economic Development Impacts, NCHRP 8-36-61, National Cooperative Highway Research Program (www.trb.org/nchrp); at www.statewideplanning.org/_resources/63_NCHRP8-36-61.pdf.
EDRG (2007), Monetary Valuation Per Dollar Of Investment In Different Performance Measures, American Association of State Highway and Transportation Officials (AASHTO) Standing Committee on Planning (www.transportation.org); at www.dot.state.tx.us/services/transportation_planning_and_programming/la_entrada/files/nchrp.pdf.
ECONorthwest and PBQD (2002), Estimating the Benefits and Costs of Public Transit Projects, TCRP Report 78, TRB (www.trb.org); athttp://gulliver.trb.org/publications/tcrp/tcrp78/index.htm.
Aaron Elias and Kamala Parks (2013), HCM Urban Streets Methodology: Bicyclist, Pedestrian, and Transit Passenger, TRB Webinar; at http://onlinepubs.trb.org/onlinepubs/webinars/131031.pdf.
EPOMM (European Platform on Mobility Management) (www.epomm.org) provides mobility management guidance, evaluation tools and case studies. The MaxSUMO is a standardised mobility management program evaluation tool.
FHWA (2000), Highway Economics Requirement System (HERS), Federal Highway Administration (www.fhwa.dot.gov); at www.fhwa.dot.gov/infrastructure/asstmgmt/hersindex.htm.
FHWA (2000), Transportation Performance Measures Toolbox, Operations Unit, Federal Highway Administration (www.ops.fhwa.dot.gov/travel/deployment_task_force/perf_measures.htm).
FHWA (2001), Economic Analysis Primer, Office of Asset Management, Federal Highway Administration (wwwcf.fhwa.dot.gov/infrastructure/asstmgmt/primer.htm).
FHWA (2005), Highway Economic Requirements System (HERS): Technical Report, Federal Highway Administration (www.fhwa.dot.gov); at www.fhwa.dot.gov/asset/hersst/pubs/tech/tech00.cfm.
FHWA (2012), Integrating Demand Management Into The Transportation Planning Process: A Desk Reference, FHWA-HOP-12-035, Office of Operations (www.ops.fhwa.dot.gov), Federal Highway Administration; at www.ops.fhwa.dot.gov/publications/fhwahop12035/index.htm.
FHWA, Toolbox for Regional Policy Analysis Website (www.fhwa.dot.gov/planning/toolbox/index.htm) by the US Federal Highway Administration, describes analytical methods for evaluating regional economic, social and environmental impacts of various transportation and land use policies.
FHWA and FTA (2002), Transportation & Environmental Justice: Effective Practices, Federal Highway Administration, Federal Transit Administration, FHWA-EP-02-016 (www.fhwa.dot.gov/environment/ej2.htm).
Timo Finke and Eric N. Schreffler (2004), “Using Multiple Assessment Levels for Evaluating Transportation Demand Management Projects: Monitoring and Evaluation Toolkit,” Transportation Research Record 1864, TRB (www.trb.org), pp. 135-143; at http://trb.metapress.com/content/525641032032l44p.
David J. Forkenbrock and Glen E. Weisbrod (2001), Guidebook for Assessing the Social and Economic Effects of Transportation Projects, NCHRP Report 456, Transportation Research Board, National Academy Press (www.trb.org).
GDRC (2000), Notes on ‘Quality of Life,’ Global Development Research Centre (www.gdrc.org/uem/qol-define.html).
Nevine Labib Georggi, Phil Winters, Sachin Rai and Liren Zhou (2007), “Measuring the Impacts of Employer-based Transportation Demand Management Programs on an Interstate Corridor,” Journal of Public Transportation, Vol. 10, No. 4 (www.nctr.usf.edu/jpt/pdf/JPT%2010-4.pdf), pp. 51-76.
Go Boulder (2007), Transportation Options Tool Kit, Go Boulder Program, City of Boulder, Colorado (www.goboulder.net); at www.ci.boulder.co.us/files/Transportation_Master_Plan/TDM_Toolkit.pdf.
Phil Goodwin (2004), Valuing the Small: Counting the Benefits, Centre for Transport Studies, University College London (http://eprints.ucl.ac.uk/archive/00001263/01/2004_27.pdf).
GPI (2008), The GPI Transportation Accounts: Sustainable Transportation in Halifax Regional Municipality, GPI Atlantic (www.gpiatlantic.org); at www.gpiatlantic.org/pdf/transportation/hrmtransportation.pdf.
GIZ (various years), Sustainable Transportation: A Sourcebook for Policy-Makers in Developing Countries, (www.sutp.org), by the Sustainable Urban Transport Project – Asia (www.sutp-asia.org) and Deutsche Gesellschaft fur Internationale Zusammenarbeit (www.giz.de). Many of these documents are now available in various languages including Spanish, French, Chinese, Indonesian, Romanian, Thai and Vietnamese. The Mobility Management module is at the VTPI website (www.vtpi.org/gtz_module.pdf). Preserving and Expanding the Role of Non-motorized Transport: Sustainable Transportation is at the Institute for Transportation and Development Policy website (www.itdp.org/STe/STe4/readSTe4/NMT.PDF).
Chris A. Hale (2011), “New Approaches to Strategic Urban Transport Assessment,” Australian Planner, Vol. 48/3, 173-182; abstract at http://dx.doi.org/10.1080/07293682.2011.592505.
Sara J. Hendricks and Nevine Labib Georggi (2007), “Documented Impact of Transportation Demand Management Programs Through the Case Study Method,” Journal of Public Transportation, Vol. 10, No. 4 (www.nctr.usf.edu/jpt/pdf/JPT%2010-4.pdf), pp. 79-98.
Shanna Hilfernik (2004), Societal Cost-Benefit Analysis: A Bridge To More Efficient Infrastructure Decision-Making? Universiteit Utrecht (http://econ.geog.uu.nl/thesishilferink.html).
Hanna Hüging, Kain Glensor and Oliver Lah (2014), The TIDE Impact Assessment Method for Urban Transport Innovations: A Handbook for Local Practitioners, TIDE (Transport Innovation Deployment for Europe) Project (www.tide-innovation.eu); at www.tide-innovation.eu/en/upload/Results/TIDE%20D5%202_final-CLEAN.pdf.
ICF Consulting and CUTR (2005), Analyzing the Effectiveness of Commuter Benefits Programs, TCTP Report 107, Transportation Research Board (www.trb.org); at http://gulliver.trb.org/publications/tcrp/tcrp_rpt_107.pdf.
IFS (2001), Virtual Learning Arcade – London Transport (www.bris.ac.uk/news/2002/mets.htm), Institute for Fiscal Studies (www.ifs.org.uk). For technical information on this model see Tackling Traffic Congestion: More about the METS Model, (www.bized.ac.uk/virtual/vla/transport/resource_pack/notes_mets.htm) and (www.bized.ac.uk/virtual/vla/transport/index.htm), and Tony Grayling and Stephen Glaister, A New Fares Contract for London, Institute for Public Policy Research (www.ippr.org.uk), ISBN 1 86030 100 2, 2000.
Glenn D. Israel (2001), Using Logic Models for Program Development, Cooperative Extension Service, University of Florida (http://edis.ifas.ufl.edu/BODY_WC041).
ITDP (2012), The End of a Life Cycle: Urban Highways Offer Cities New Opportunities for Revitalization, Institute for Transportation and Development Policy (www.itdp.org); at www.itdp.org/urbanhighways. Also see, The Life and Death of Urban Highways, at www.itdp.org/documents/LifeandDeathofUrbanHighways_031312.pdf.
Jeffrey Kenworthy (2008), Transport
Heaven and Hell, ITS Magazine; at www.industry.siemens.de/traffic/EN/NEWS/ITSMAGAZINE/HTML/0802/fokus_1.html.
Kaydee Kirk, et al. (2010), Framework for Measuring Sustainable Regional Development for the Twin Cities Region, Center for Urban & Regional Affairs, University of Minnesota
(www.cts.umn.edu); at www.cts.umn.edu/Publications/ResearchReports/pdfdownload.pl?id=1328.
Ian Ker (2003), Travel Demand Management: Public Transport Business Case, AARB Transport Research, RC5051, TravelSmart Program (www.travelsmart.vic.gov.au).
Kittleson & Associates (2003), Guidebook for Developing a Transit Performance-Measurement System, TCRP Web Document 88, Transportation Research Board (www.trb.org); at http://gulliver.trb.org/publications/tcrp/tcrp_report_88/intro.pdf.
Douglass Lee (2002), “Fundamentals of Lifecycle-Cost Analysis,” Transportation Research Record 1812, TRB (www.trb.org), pp. 203-201; at http://trb.metapress.com/content/5432j5474672122q.
Richard Lee, Paul Wack and Eugene Jud (2003), Towards Sustainable Mobility Indicators In California, Mineta Transportation Institute (http://transweb.sjsu.edu/publications/02-05.pdf).
Todd Litman (1995), Evaluating Transportation Land Use Impacts, originally published in World Transport Policy & Practice, Vol. 1, No. 4, pp. 9-16; at www.vtpi.org/landuse.pdf.
Todd Litman (2001), What’s It Worth? Life Cycle and Benefit/Cost Analysis for Evaluating Economic Value, Presented at Internet Symposium on Benefit-Cost Analysis, Transportation Association of Canada (www.tac-atc.ca); at www.vtpi.org/worth.pdf.
Todd Litman (2003), “Measuring Transportation: Traffic, Mobility and Accessibility,” ITE Journal (www.ite.org), Vol. 73, No. 10, October, pp. 28-32; at www.vtpi.org/measure.pdf.
Todd Litman (2004), “Transit Price Elasticities and Cross-Elasticities,” Journal of Public Transportation, Vol. 7, No. 2, (www.nctr.usf.edu/jpt/pdf/JPT 7-2 Litman.pdf), pp. 37-58; at www.vtpi.org/tranelas.pdf.
Todd Litman (2005), “Efficient Vehicles Versus Efficient Transportation: Comparing Transportation Energy Conservation Strategies,” Transport Policy, Volume 12, Issue 2, March 2005, Pages 121-129; at www.vtpi.org/cafe.pdf.
Todd Litman (2006a), “Changing Travel Demand: Implications for Transport Planning,” ITE Journal, Vol. 76, No. 9, (www.ite.org), September, pp. 27-33; at www.vtpi.org/future.pdf.
Todd Litman (2006b), “Transportation Market Distortions,” Berkeley Planning Journal; issue theme Sustainable Transport in the United States: From Rhetoric to Reality? (www-dcrp.ced.berkeley.edu/bpj), Volume 19, 2006, pp. 19-36; at www.vtpi.org/distortions_BPJ.pdf.
Todd Litman (2007a), Community Cohesion as a Transport Planning Objective, VTPI (www.vtpi.org); at www.vtpi.org/cohesion.pdf.
Todd Litman (2007b), Evaluating Public Transit Benefits and Costs, VTPI (www.vtpi.org); at www.vtpi.org/tranben.pdf.
Todd Litman (2007d), Guide to Calculating Mobility Management Benefits, Victoria Transport Policy Institute (www.vtpi.org); at www.vtpi.org/tdmben.pdf.
Todd Litman (2007e), Evaluating Accessibility for Transport Planning, VTPI (www.vtpi.org); at www.vtpi.org/access.pdf.
Todd Litman (2007f), Build for Comfort, Not Just Speed: Valuing Service Quality Impacts In Transport Planning, Victoria Transport Policy Institute (www.vtpi.org); at www.vtpi.org/quality.pdf.
Todd Litman (2008), Transportation Elasticities: How Prices and Other Factors Affect Travel Behavior, Victoria Transport Policy Institute (www.vtpi.org); at www.vtpi.org/elasticities.pdf.
Todd Litman (2008), Land Use Impacts on Transport: How Land Use Factors Affect Travel Behavior, Victoria Transport Policy Institute (www.vtpi.org); at www.vtpi.org/landtravel.pdf.
Todd Litman (2008), Well Measured: Developing Indicators for Comprehensive and Sustainable Transport Planning, VTPI (www.vtpi.org); at www.vtpi.org/wellmeas.pdf.
Todd Litman (2008), Evaluating Research Quality: Guidelines for Scholarship, VTPI (www.vtpi.org), originally prested at the 2006 International Electronic Symposium on Knowledge Communication and Peer Reviewing, International Institute of Informatics and Systemics (www.iiis.org); at www.vtpi.org/resqual.pdf.
Todd Litman (2009a), Transportation Cost and Benefit Analysis; Techniques, Estimates and Implications, Victoria Transport Policy Institute (www.vtpi.org/tca).
Todd Litman (2010), Evaluating Active Transport Benefits and Costs: Guide to Valuing Walking and Cycling Improvements and Encouragement Programs, Victoria Transport Policy Institute (www.vtpi.org); at www.vtpi.org/nmt-tdm.pdf.
Todd Litman (2011), Smart Congestion Relief: Comprehensive Analysis Of Traffic Congestion Costs and Congestion Reduction Benefits, Victoria Transport Policy Institute (www.vtpi.org); at www.vtpi.org/cong_relief.pdf; summary version titled, "Congestion Evaluation Best Practices" (www.vtpi.org/ITED_congestion.pdf) presented at the International Transportation Economic Development Conference (http://tti.tamu.edu/conferences/ited2014), 9-11 April 2014, Dallas, Texas.
Todd Litman (2012), Evaluating Complete Streets: The Value of Designing Roads For Diverse Modes, Users and Activities, Victoria Transport Policy Institute (www.vtpi.org); at www.vtpi.org/compstr.pdf.
Todd Litman, (2013), “Smarter Congestion Relief In Asian Cities: Win-Win Solutions To Urban Transport Problems,” Transport and Communications Bulletin for Asia and the Pacific, United Nation’s Economic and Social Commission for Asia and the Pacific (www.unescap.org), No. 82, pp. 1-18; at www.unescap.org/ttdw/Publications/TPTS_pubs/bulletin82/b82_Chapter1.pdf
Todd Litman (2013), Congestion Costing Critique: Critical Evaluation of the ‘Urban Mobility Report,’ VTPI (www.vtpi.org); at www.vtpi.org/UMR_critique.pdf.
Todd Litman (2013), “The New Transportation Planning Paradigm,” ITE Journal (www.ite.org), Vo. 83, No. 6, pp. 20-28; at http://digitaleditions.sheridan.com/publication/?i=161624.
Todd Litman (2013), Toward More Comprehensive and Multi-modal Transport Evaluation, VTPI (www.vtpi.org); at www.vtpi.org/comp_evaluation.pdf; summarized in JOURNEYS, September 2013, pp. 50-58 (www.ltaacademy.gov.sg/journeys.htm); at http://app.lta.gov.sg/ltaacademy/doc/13Sep050-Litman_ComprehensiveAndMultimodal.pdf.
Todd Litman (2014), Socially Optimal Transport Prices and Markets, Victoria Transport Policy Institute (www.vtpi.org); at www.vtpi.org/sotpm.pdf. A summary version, titled, “Economically Optimal Transport Prices and Markets: What Would Happen If Rational Policies Prevailed?” (www.vtpi.org/ITED_optimal.pdf) was presented at the International Transportation Economic Development Conference (http://tti.tamu.edu/conferences/ited2014), 9-11 April 2014, Dallas, Texas.
Todd Litman (2014), Are Vehicle Travel Reduction Targets Justified? Evaluating Mobility Management Policy Objectives Such As Targets To Reduce VMT And Increase Use Of Alternative Modes, Victoria Transport Policy Institute (www.vtpi.org); at www.vtpi.org/vmt_red.pdf. A summary version, titled, “The Mobility-Productivity Paradox: Exploring The Negative Relationships Between Mobility and Economic Productivity,” (www.vtpi.org/ITED_paradox.pdf) was presented at the International Transportation Economic Development Conference (http://tti.tamu.edu/conferences/ited2014), 9-11 April 2014, Dallas, Texas.
Todd Litman (2014), “A New Transit Safety Narrative,” Journal of Public Transportation, Vol. 17, No. 4, pp. 114-135; at www.nctr.usf.edu/wp-content/uploads/2014/12/JPT17.4_Litman.pdf; more complete report at www.vtpi.org/safer.pdf.
Todd Litman (2014), Analysis of Public Policies That Unintentionally Encourage and Subsidize Urban Sprawl, commissioned by LSE Cities (www.lsecities.net), for the Global Commission on the Economy and Climate (www.newclimateeconomy.net); at http://bit.ly/1EvGtIN.
Todd Litman (2015), Response to "Putting People First: An Alternative Perspective with an Evaluation of the NCE Cities 'Trillion Dollar' Report", Victoria Transport Policy Institute (www.vtpi.org); at http://www.vtpi.org/PPFR.pdf.
Todd Litman (2015), Evaluating Household Chauffeuring Burdens (www.vtpi.org/chauffeuring.pdf), presented at the International Transport Economics Association (ITEA) Annual Conference June 17-19, Oslo, Norway (www.toi.no/ITEA2015).
Todd Litman (2018), Rethinking Malahat Solutions: Or, Why Spend A Billion Dollars If A Five-Million Dollar Solution Is Better Overall? Victoria Transport Policy Institute (www.vtpi.org); at www.vtpi.org/malahat.pdf.
Peter Mackie and Tom Worsley (2013) International Comparisons of Transport Appraisal Practice, Institute for Transport Studies (www.its.leeds.ac.uk) for the UK Department for Transport; at www.gov.uk/government/publications/international-comparisons-of-transport-appraisal-practice.
Tracey MacDonald and Phil Lidov (2005), Strategic Transportation, Environmental and Planning Process for Urbanizing Places (STEP UP); Phase I Report, Colorado Dept. of Transportation, Report, CDOT-DTD-2005-03 (www.dot.state.co.us); at www.dot.state.co.us/publications/PDFFiles/stepup.pdf.
Wesley Marshall, Daniel Piatkowski and Chris McCahill (2019), “[Re]Evaluating How We Value Transportation,” Research in Transportation Business & Management (http://dx.doi.org/10.1016/j.rtbm.2019.01.005); at https://bit.ly/2TPoaSR.
Multimodal Benefit-Cost Analysis Tool (http://tredis.com/mbca) is a free, web-based calculation system for comparing the costs and user benefits of individual transportation projects.
MC ICAM (Implementation of Marginal Cost Pricing in Transport - Integrated Conceptual and Applied Model Analysis) (http://vplno1.vkw.tu-dresden.de/psycho/projekte/mcicam/e_mcicam.html), a program at the Traffic and Transportation Psychology department at the Dresden University of Technology (www.verkehrspsychologie-dresden.de) explores issues related to the problems and opportunities of implementing more efficient transportation pricing.
Measuring Walking (www.measuring-walking.org) describes internationally standardised monitoring methods of walking and public space.
Mustel (2004), Interest in Viable Transportation Options Among Private Vehicle Drivers, TransLink and the British Columbia Automobile Association, (www.translink.bc.ca); at www.translink.bc.ca/files/polls_surveys/cust_satisfaction/Report_BCAA_GVTA_Travel_Choices_Quantitative_Nov2004.pdf.
Peter Newman and Jeff Kenworthy (1999), Sustainability and Cities; Overcoming Automobile Dependency, Island Press (www.islandpress.org).
New Integrated Smart Transport Options Toolkit (www.nistotoolkit.eu) provides a framework for evaluating small-scale mobility management projects using multi-objective analysis.
NJDOT (2007), Cost of Transporting People in New Jersey, New Jersey Department of Transportation and the Region 2 University Transportation Research Center, U.S. Department of Transportation; at www.nj.gov/transportation/refdata/research/reports/FHWA-NJ-2007-003.pdf.
NZTA (2010), Economic Evaluation Manual, Volumes 1 and 2, New Zealand Transport Agency (www.nzta.govt.nz); at www.nzta.govt.nz/resources/economic-evaluation-manual.
New Zealand Transportation Agency Post Implementation Reviews (PIRs) (www.nzta.govt.nz/planning/monitoring/audits/pir.html) are conducted every year on a small sample of completed NZTA-funded projects. They allow the agency to compare the planned benefits and costs of a project with the actual outcomes achieved.
Noxon Associates (2008), The Case for TDM in Canada: Transportation Demand Management Initiatives and Their Benefits – A Handbook for Practitioners, Association for Commuter Transportation of Canada (www.actcanada.com).
Noxon Associates (2009), Canadian Guidelines for the Measurement of Transportation Demand Management Initiatives, Transport Canada (www.tc.gc.ca/urban); at www.tc.gc.ca/media/documents/programs/cgmtdmi.pdf.
Noxon Associates (2011), Transportation Demand Management for Canadian Communities: A Guide to Understanding, Planning and Delivering TDM Programs, Transport Canada (www.tc.gc.ca/urban); at www.noxonassociates.com/guide.html.
Carolyn O’Fallon (2003), Linkages Between Infrastructure and Economic Growth, New Zealand Ministry of Economic Development (www.med.govt.nz); at www.med.govt.nz/templates/MultipageDocumentTOC____9187.aspx.
PCT (2011), Measuring Transportation Investments: The Road to Results, Pew Charitable Trusts and The Rockefeller Foundation (www.pewtrusts.org); at www.pewtrusts.org/uploadedFiles/wwwpewtrustsorg/Reports/State_policy/Transportation_Report_2011.pdf.
Performance Measurement Exchange (http://knowledge.fhwa.dot.gov/cops/pm.nsf/home), is a website supported by the U.S. Federal Highway Administration and the Transportation Research Board to promote better transportation decision-making.
Post Opening Project Evaluation (POPE) of Major Schemes (www.highways.gov.uk/our-road-network/post-opening-project-evaluation-pope/post-opening-project-evaluation-pope-of-major-schemes) is a UK Department for Transport program that evaluates the extent to which major highway projects achieve their intended objectives, and identify lessons learnt which can inform future planning.
Richard H. Pratt (2007), Traveler Response to Transportation System Changes, Third Edition, TCRP Report 95, DOT-FH-11-9579, TRB (www.trb.org); at www.trb.org/TRBNet/ProjectDisplay.asp?ProjectID=1034.
PROSPECTS (2003), Transport Strategy: A Decisionmakers Guidebook, Konsult, Institute for Transport Studies, University of Leeds (www.konsult.leeds.ac.uk); at www.konsult.leeds.ac.uk/public/level1/sec00/index.htm; originally published as, Developing Sustainable Urban Land Use and Transport Strategies: A Methodological Guidebook; at www.infra.kth.se/courses/1H1402/Litteratur/pr_del14mg.pdf.
John Pucher, Jennifer Dill and Susan Handy (2010), “Infrastructure, Programs and Policies to Increase Bicycling: An International Review,” Preventive Medicine, Vol. 48, No. 2, February; prepared for the Active Living By Design Program (www.activelivingbydesign.org); at http://policy.rutgers.edu/faculty/pucher/Pucher_Dill_Handy10.pdf.
John Pucher and Ralph Buehler (2011), Analysis of Bicycle Trends and Policies in Large North American Cities: Lessons for New York, University Transportation Research Center; at www.utrc2.org/research/assets/176/Analysis-Bike-Final1.pdf; summary at www.utrc2.org/research/assets/176/Bicycle-Brief1.pdf.
QUEST (Quality management tool for Urban Energy efficient Sustainable Transport) (www.quest-project.eu) is a European Commission project to assist small and mid-sized cities in improving planning for sustainable urban mobility. QUEST is developing tools for evaluating urban mobility policies based on the concept of Total Quality Management (TQM).
RAND Europe (2005), Analysis and Assessment of Policies: Report on Performance of Policies, European Commission (www.summa-eu.org).
John Luciano Renne (2007), Measuring The Performance Of Transit-Oriented Developments In Western Australia, Planning and Transport Research Centre of Western Australia and the Institute for Sustainability and Technology Policy, Murdoch University; at www.vtpi.org/renne_tod_performance.pdf.
Kerstin Robertson, Annika K. Jägerbrand and Georg F. Tschan (2015), Evaluation Of Transport Interventions In Developing Countries, Report 855A, Swedish Transport Research Institute (www.vti.se); at www.vti.se/en/publications/pdf/evaluation-of-transport-interventions-in-developing-countries.pdf.
Doug Sallman, Erin Flanigan, Krista Jeannotte, Chris Hedden and Dorothy Morallos (2012), Operations Benefit/Cost Analysis Desk Reference, Office of Operations, Federal Highway Administration (www.ops.fhwa.dot.gov); at www.ops.fhwa.dot.gov/publications/fhwahop12028/fhwahop12028.pdf.
SANDAG (2012), Integrating Transportation Demand Management into the Planning and Development Process: A Reference for Cities, iCommute (www.icommutesd.com), San Diego Regional Planning and HNTB; at www.icommutesd.com/documents/TDMStudy_May2012_webversion_000.pdf.
Eric Schreffler (2000), State of the Practice: Mobility Management Monitoring and Evaluation in the United States, MOST: Mobility Management Strategies for the Next Decades; Work Package 3, D3 Report, Appendix C (http://mo.st/public/reports/me_usa.zip).
SFPD (2018), TDM Menu of Options, San Francisco Planning Department (http://sf-planning.org); at http://sf-planning.org/tdm-menu-options.
D. Shefer and P. Rietvald (1997), “Congestion and Safety on Highways: Towards an Analytical Model,” Urban Studies, Vol. 34, No. 4, pp. 679-692.
Donald Shoup (2003), “Truth in Transportation Planning,” Journal of Transportation And Statistics, Vol. 6, No. 1, Bureau of Transportation Statistics (www.bts.gov), pp. 1-12. Also see Donald Shoup, “Roughly Right or Precisely Wrong,” ACCESS 20 (www.uctc.net), Spring 2002, pp. 20-25.
SJCOG (2008), Deficiency And Transportation Demand Management Plans: Guidelines For Document Format And Content Requirements, San Joaquin Council Of Governments (www.sjcog.org); at www.sjcog.org/docs/pdf/FHWA_Cert/CMP_Deficiency_TDM_Plan_Guidelines.pdf.
Kenneth Small (1999), “Project Evaluation,” in Transportation Policy and Economics, Brookings (www.brookings.edu); at www.uctc.net/papers/379.pdf.
Nariida C. Smith, Daniel W. Veryard and Russell P. Kilvington (2009), Relative Costs And Benefits Of Modal Transport Solutions, Research Report 393, NZ Transport Agency (www.nzta.govt.nz); at www.nzta.govt.nz/resources/research/reports/393/docs/393.pdf.
Michael Spackman, Alan Pearman, Larry Phillips (2001), Multi Criteria Analysis: A Manual, National Economic Research Associates, Department of the Environment, Transport and the Regions (www.environment.detr.gov.uk/multicriteria).
SUMMA (2003), Fast Simple Model, SUMMA (Sustainable Mobility, Policy Measures and Assessment) (www.summa-eu.org). This is a model for operationalizing the concept of sustainable transportation by predicting the impacts of various policies and programs.
Sustainable Highways Self-Evaluation Tool (www.sustainablehighways.org) by the U.S. Federal Highway Administration identifies characteristics of sustainable highways and provides procedures and techniques to help organizations apply sustainability best practices to roadway projects and programs.
Gil Tal (2008), Overestimation Reduction in Forecasting Telecommuting as a Transportation Demand Management Policy, Transportation Research Board 87th Annual Meeting (www.trb.org).
TC (2009), Canadian Guidelines for the Measurement of Transportation Demand Management Initiatives User's Guide, Transport Canada (www.tc.gc.ca); at www.tc.gc.ca/eng/programs/environment-urban-guidelines-practitioners-tdmguide2009-menu-1657.htm.
TIDE (2013), Impact Assessment Handbook: Practitioners’ Handbook for Cost Benefit and Impact Analysis of Innovative Urban Transport Measures, Transport Innovation Deployment for Europe; at www.eltis.org/sites/default/files/trainingmaterials/tide-assessment-handbook-lite.pdf.
Transport Analysis Guidance Website (www.webtag.org.uk) sponsored by the UK Department for Transport, provides advice on the modeling and economic evaluation of roadway and public transport programs.
Transport Toolkit (http://ledsgp.org/transport) by the Transport Working Group as part of the Low Emission Development Strategies Global Partnership helps planners and decision-makers access various information resources that can help identify the most effective tools to build and implement low emission transportation strategies.
Transportation and The Economy, Club of Jules Dupuit, University of Montreal (www.ajd.umontreal.ca/Frames/Frametransport/transportation/frametransportation.htm). This website, inspired by the 18th Century engineer/economist Jules Dupuit, provides information on methods of quantifying transportation impacts, particularly economic benefits.
Transportation Benefit-Cost Analysis Website (http://bca.transportationeconomics.org), Transportation Economics Committee, Transportation Research Board (www.trb.org).
Transportation for Communities - Advancing Projects through Partnerships (www.transportationforcommunities.com) is an integrated website that provides guidance for transport planning and investment decisions, particularly within the U.S. transportation development system.
Travel Matters (www.travelmatters.org) is a website with interactive emissions calculators, on-line emissions maps and other information resources to help examine the relationships between transportation decisions and greenhouse gas emissions.
TRB Performance Measurement Community of Practice Website (www.trb-performancemeasurement.org) provides information on resources, events and case studies concerning improving transportation evaluation decision-making, innovation, and improved the quality of service, sponsored by the TRB Performance Measurement Committee.
TRB (2010), Highway Capacity Manual, Transportation Research Board (www.trb.org).
TRB (2013), Transit Capacity and Quality of Service Manual, Third Edition, Transportation Research Board (www.trb.org); at www.trb.org/main/blurbs/169437.aspx.
TREDIS (www.tredis.com), the “Transportation Economic Development Impact System,” is an interactive system of tools for transportation investment economic development impact evaluation and benefit-cost analysis. It can be applied to highway, bus rail, aviation, marine and multi-modal projects.
TRIMMS (Trip Reduction Impacts of Mobility Management Strategies) Model, developed by the University of South Florida (www.nctr.usf.edu) evaluates the travel impacts, benefits and costs of various commute trip reduction programs and other mobility management strategies; at www.nctr.usf.edu/abstracts/abs77704.htm.
USDOT (2003), Economic Analysis Primer, Office of Asset Management, FHWA, USDOT (www.fhwa.dot.gov/infrastructure/asstmgmt/primer.pdf).
USDOT (2010), Advancing Metropolitan Planning for Operations: The Building Blocks of a Model Transportation Plan Incorporating Operations - A Desk Reference, Planning for Operations, US Department of Transportation (www.ops.fhwa.dot.gov); at www.ops.fhwa.dot.gov/publications/fhwahop10027/index.htm.
USDOT (2016), 2016 TIGER Benefit-Cost Analysis Guidance, Office of Infrastructure Finance and Innovation, US Department of Transportation (www.ops.fhwa.dot.gov); at www.transportation.gov/policy-initiatives/tiger/2016-tiger-benefit-cost-analysis-guidance.
Ian Wallis, Don Wignall and Chris Parker (2012), The Implications Of Road Investment, Research Report 507, NZ Transport Agency (www.nzta.govt.nz); at www.nzta.govt.nz/resources/research/reports/507.
Glen Weisbrod (2000), Current Practices for Assessing Economic Development Impacts from Transportation, National Cooperative Highway Research Program, Synthesis 290, TRB (www.trb.org); at www.edrgroup.com/pdf/synth290.pdf.
Phil L. Winters and Sara J. Hendricks (2003), Quantifying The Business Benefits of TDM, Center for Urban Transportation Research, for the Office of Research and Special Programs, USDOT (www.nctr.usf.edu/html/416-11.htm).
Philip L. Winters, Rafael A. Perez, Ajay D. Joshi and Jennifer Perone (2005), “Worksite Trip Reduction Model and Manual,” Transportation Research Record 1924, Transportation Research Board (www.trb.org), pp. 197-206.
WRA (2014), State of the Art Practice for Cost-Effectiveness Analysis (CEA), Cost-Benefit Analysis (CBA) and Resource Allocation, World Road Association (www.piarc.org); at http://tinyurl.com/kvgwpnv.
Lloyd Wright (2009), Environmentally Sustainable Transport for Asian Cities: A Sourcebook, United Nations Centre for Regional Development (www.uncrd.org.jp); at http://unpan1.un.org/intradoc/groups/public/documents/uncrd/unpan031844.pdf.
WSDOT (2014), Handbook for Corridor Capacity Evaluation: WSDOT’s Methods for Comprehensive Analysis of Multimodal State Highway System Performance, Washington State Department of Transportation (http://wsdot.wa.gov); at http://wsdot.wa.gov/publications/fulltext/graynotebook/CCR14_methodology.pdf.
Xin Zhang and Gang-len Chang (2014), “A Transit-Based Evacuation Model for Metropolitan Areas,” Journal of Public Transportation, Vol. 17, No. 3, 129-147; at www.nctr.usf.edu/wp-content/uploads/2014/09/JPT17.3_Zhang.pdf.
This Encyclopedia is produced by the Victoria Transport Policy Institute to help improve understanding of Transportation Demand Management. It is an ongoing project. Please send us your comments and suggestions for improvement.
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