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Updated 25 August 2016

This chapter describes different ways to measure transportation system performance, discusses their different perspectives and assumptions and how they affect planning decisions, and identifies best practices for more objective and comprehensive analysis.

Index

Introduction.. 2

Transportation Performance Indicators. 3

Perspective: Traffic, Mobility and Accessibility. 5

Traffic. 5

Mobility. 6

Accessibility. 7

The Role of Different Modes. 9

Land Use Accessibility. 11

Trade-offs Between Different Types of Accessibility. 12

Reference Units. 15

Additional Considerations. 18

The Function of the Streets. 18

Geographic Scale. 18

Planning and Investment Decisions. 19

Basic Access. 20

Modeling. 20

Examples. 21

Road Safety Analysis (Safety Evaluation) 22

Unit Costs of Incremental Peak-Period Vehicle Trips (Transportation Costs) 23

Road Pricing Objectives. 23

Equity Analysis. 23

Best Practices. 24

Related Chapters. 25

Examples and Case Studies. 25

Florida Multi-Modal Quality-Of-Service Standards (FDOT, 2002) 25

San Francisco Multi-Modal Level-Of-Service (Hiatt, 2006) 25

The Human Capacity Manual (www.walksf.org/essays/pedCountEssay.html) 25

References And Resources For More Information.. 27

Introduction

Management experts often say that, “you can’t manage what you can’t measure.” What is measured, how it is measured, and how data are presented often affect how problems are defined and solutions selected. A particular solution may appear best when measured one way, but undesirable when measured another way.

For example, a baseball player’s performance can be evaluated based on batting averages, base hits, runs batted in, and ratio of wins to losses, plus various defense statistics that depend on the player’s position. Performance statistics can be calculated per at-bat, per inning, per game, per season, or for a career. A player can be considered outstanding according to one set of statistics but inferior according to another.

Similarly, people’s economic status can be evaluated based on hourly, monthly or annual wages; income per worker, per adult or per household; gross, net or disposable income; wealth (income plus assets minus debts); or purchasing power (which takes into account relative wages and living costs). Independent contractors are paid high hourly rates, but often only work part-time and must cover their own overhead expenses, so their net income is lower then colleagues with a steady salary. A multi-worker family will be considered poorer if income is measured per capita or per worker than per household. Residents in some communities have high wages, but their purchasing power is low due to relatively high living costs. Some households that own expensive homes and vehicles have negative wealth because their debts outweigh their assets. A person can be considered rich by one set of statistics, but poor by another.

These are just two examples of how different measurement methods and units can affect how things are evaluated. Often, no single unit conveys all the information needed for evaluation. Different measurement units represent different perspectives and highlight different features. Decision-makers may need to consider a variety of different statistics. A coach needs to consider several different statistics when evaluating how a particular player fits into a team. Policy makers need to consider various measures of income and wealth to determine which households should be considered economically disadvantaged. It is important that people using such information understand the different perspectives and assumption implicit in the units they use.

As Ken Alder explains, “Measures are more than a creation of society, they create society,” and fundamentally affect the relationships between people. Scientists and planners have long realized that how objects and activities are measured can affect how we think about and solve certain problems. This is an important factor in transportation planning. When transportation system quality is measured in one way, conditions may seem unsatisfactory, justifying certain improvements, but when the same conditions are measured in another way, the same improvements may appear unjustified and harmful.

This chapter discusses different methods used to measure transportation, the different perspectives they represent, how the selection of one or another method can affect transportation and land use planning decisions, and best practices for evaluating transportation activities and systems.

Transportation Performance Indicators

Performance Indicators are practical ways to Evaluate progress toward objectives. Per capita travel statistics, traffic counts, Level-of-Service (LOS) ratings, cost per mile, and customer satisfaction survey results are examples of performance indicators used for transport planning.

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. For example, if a community values nonmotorized transport it is important to include suitable indicators of pedestrian and cycling conditions in transportation planning.

Transportation Demand Management Performance Indicators

Below are common Performance Indicators used to Evaluate TDM programs. 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.

· Response – the number of people who respond to an outreach effort, such as asking for information on alternative travel modes in response to a promotion campaign.

· Participation – the number of people who use a service or alternative mode.

· Utilization – the number or portion of trips that use a travel 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, 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). A variety of methods can be used to collect the data needed for performance evaluation, including general travel Statistics, participant Surveys, parking lot counts, traffic counts, and focus groups. Before-and-after and with-and-with comparisons require the collection of good baseline data or the use of readily-available statistics.

Perspective: Traffic, Mobility and Accessibility

A paradigm shift (a fundamental change in the way problems are defined and solutions evaluated) is occurring in transport planning which involves changing from mobility-based to accessibility-based analysis. Mobility refers to physical movement. Accessibility refers to people’s ability to reach desired services and activities, and is the ultimate objective of most transport activity (excluding mobility that is an end in itself, with no destination, such as jogging and cruising), so accessibility-based analysis more accurately reflects ultimate planning goals.

Accessibility-based planning expands the range of solutions that can be applied to transportation problems. Conventional planning often assumes that transportation means mobility, so improving transport requires increasing mobility. Accessibility-based planning allows other transport improvement options to be considered, for example, by improving walking conditions and transit service, creating more accessible land use, and providing mobility substitutes such as telecommunications and delivery services.

In other words, mobility-based planning cannot recognize savings and benefits that result if the need to travel is reduced. Accessibility-based planning recognizes that reducing travel is sometimes the most efficient solution to transport problems.

Different Performance Indicators reflect different perspectives about traffic, mobility and accessibility. These are described and compared below in terms of how they view users, modes, land use, transport problems and solution, and how they are measured.

Traffic

Definition

Traffic refers to vehicle movement. This perspective assumes that “travel” means vehicle travel and “trip” means vehicle-trip. It assumes that increased vehicle mileage and speed benefits society.

Users

From this perspective, transportation users are primarily motorists (including drivers, passengers and businesses that rely on commercial deliveries). Non-motorists are considered a relatively small and unimportant minority, defined as members of households that do not own an automobile.

Modes

This perspective focuses on automobile travel. It places little value on transit and cycling, since they represent a small portion of vehicle-mileage. It considers walking primarily as a way for motorist to access parking facilities or as a form of recreation, and so devotes little transportation funds to nonmotorized facilities.

Land Use

This perspective evaluates land use primarily in terms of proximity to highways and parking supply. The best location for a public facility is along a major arterial or freeway intersection, in an area with abundant parking supply. Downtown locations are undesirable due to excessive roadway congestion and parking costs.

Transport Problems and Solutions

This perspective defines transportation problems in terms of costs, barriers and risks to motorists. It favors solutions that increase road and parking capacity, roadway traffic speeds, vehicle ownership, and the affordability of driving. From this perspective, the best way to benefit non-drivers is to help them become motorists, by making automobile and taxi travel convenient and inexpensive.

Measurement

Vehicle traffic is relatively easy to measure. Most jurisdictions have data on motor vehicle registrations, drivers licenses, and vehicle mileage. Performance Indicators include traffic volumes, average traffic speeds, roadway Level of Service (LOS), congestion delay, parking supply, vehicle costs and crash rates.

Table 1 Roadway Levels of Service (TRB 1994)

LOS	Maximum Flow Cars/lane/hour	Average Speed Km/hour	Maximum Density Cars/land/km
A	720	96.5	7.5
B	1,200	96.5	12.4
C	1,650	94.9	17.4
D	1,940	91.7	21.1
E	2,200	88.5	24.9

This table shows Level of Serve (LOS) values used to evaluate traffic conditions.

Mobility

Definition

Mobility refers to the movement of people or goods. It assumes that “travel” means person- or ton-miles, “trip” means person- or freight-vehicle trip. It assumes that any increase in travel mileage or speed benefits society.

Users

From this perspective, transport users are mainly motorists, since most person- and ton-miles are by motor vehicle, but recognizes that some people rely on non-automobile modes, and some areas have large numbers of transit, rideshare and cycling trips. It recognizes that a significant portion of people use non-automobile modes at least occasionally.

Modes

This perspective considers motor vehicles most important, but also values transit and ridesharing on congested corridors, and recognizes that walking and cycling may be important in areas such as college towns and resort communities. It supports an integrated view of the transportation system, with attention to connections between different modes. For example, it recognizes that most transit trips involve at least one walking link, and so walking and transit are complementary travel modes. It justifies devoting a modest portion of transport funding to transit, HOV and cycling.

Land Use

From this perspective, convenient highway access and parking is most important, but transit and HOV access are also desirable in areas where density and demographics concentrate enough riders. The best location for public facilities has a combination of convenient roadway access, adequate parking, transit service, and cycling routes.

Transport Problems and Solutions

A mobility perspective defines transportation problems in terms of constraints on physical movement, and so favors solutions that increase motor vehicle system capacity and speed, including road and parking facility improvements, transit and ridesharing improvements, high-speed train, aviation and intermodal connections. It gives little consideration to walking and cycling except where they provide access to motorized modes, since they represent a small portion of person-miles. From this perspective, the best way to benefit non-drivers is to improve motorized transport, including automobile, transit and taxi modes, with more modest consideration of walking and cycling.

Measurement

Mobility is measured in person-miles, ton-miles, and travel speeds. Mobility is sometimes measured door-to-door, taking into account each link of a trip, including walking to a parking lot or transit stop. Current travel data tends to underrepresent non-motorized travel, short trips, travel by children and lower-income people, and recreational travel, but newer travel surveys can help overcome these constraints (Stopher and Greaves, 2007). In recent years improved techniques have been developed to evaluate Transportation Diversity, Transit and Nonmotorized travel. Transportation engineers now have standardized methods for calculating pedestrian, cycling and transit Level of Service, just as they do for automobile traffic (IHT, 2000; FDOT, 2002; Mitchell and Milam, 2006), although these are not yet widely used.

Accessibility

Definition

Accessibility (or just access) refers to the ability to reach desired goods, services, activities and destinations (collectively called opportunities). Access is the ultimate goal of most transportation, except a small portion of travel in which movement is an end in itself (jogging, horseback riding, pleasure drives), with no destination. This perspective assumes that improved access benefits society, and mobility is one way to achieve this goal. This perspective considers vehicle traffic a subset of mobility, and mobility a subset of accessibility.

Other Meanings of “Access”

The word “access” can have other specific meanings in transportation planning. In pedestrian planning it refers to Accessible Design or Universal Design, which refers to facilities designed to accommodate people with special needs, including those with disabilities. For example, a pathway designed to accommodate people in wheelchairs may be called “accessible.” In roadway engineering “access” refers to connections to adjacent properties, such as driveways and private roads. A “limited access” highway has minimal connections to adjacent properties, while a local road provides direct access. Access Management refers to programs to limit the number of driveways and intersections on highways to improve traffic flow and safety.

Users

From this perspective, transportation users consist of any person or businesses that wants to reach a good, service, activity or destination. It recognizes that most people use a variety of access options.

Modes

This perspective considers all access options as being potentially important, including travel options such as Transit, Ridesharing and Nonmotorized Modes; mobility substitutes such as Telework and Delivery Services; and strategies to increase land use Accessibility such as Smart Growth and Location Efficient Development. It supports an integrated view of transportation and land use systems, with attention to connections among modes and between transport and land use patterns. It values modes according to their ability to meet users’ needs, and does not necessarily favor longer trips or faster modes if shorter trips and slower modes provide adequate access. It considers Walkability to be a particularly important mode, because walking provides Basic Access, including connections between modes and to destinations. It supports the broadest use of transport funding, including mobility management and land use management strategies if they increase accessibility.

Land Use

From this perspective, land use is as important as mobility in the quality of transportation, and different land use patterns favor different types of accessibility. The distribution of destinations, land use mix, network connectivity and walking conditions all affect transportation system performance. The best location for public facilities has a combination of convenient proximity, roadway access, transit service and walkability.

Transport Problems and Solutions

Accessibility-based planning expands the range of transport problems and potential solutions that can be considered. From this perspective, transport problems include any cost, barrier or risk that prevents people from reaching desired opportunities. Solutions can include traffic improvements, mobility improvements, mobility substitutes and more accessible land use.

Measurement

Accessibility is evaluated based on the time, money, discomfort and risk (the generalized cost) required to reach opportunities. Individuals often think of it in terms of convenience, that is, the ease with which they can reach what they want. Accessibility is relatively difficult to measure because it is affected by a variety of transportation, economic and geographic factors. For example, access to employment is affected by an individual’s physical and economic abilities, the quality and cost of travel options that reach worksites, the feasibility of telework (which may allow employment for a firm that is physically difficult to reach), and the geographic location of suitable jobs. Activity-based travel Models and integrated transportation/land use models using detailed travel survey data are most suitable for quantifying accessibility. Although access is a well-recognized concept in the disciplines of geography and urban economics, it is a new concept for many transportation practitioners. In recent years transportation professionals have started exploring the implications of basing transport planning on access rather than traffic or mobility (BTS, 2001). Improved techniques are being developed to better evaluate Transportation Diversity, Transit and Nonmotorized travel, as well as Land Use Factors that affect transport. The Accessibility chapter describes how to calculate an Accessibility Index.

Table 2 summarizes differences between these three ways to measure transportation.

Table 2 Comparing Transportation Measurements

	Traffic	Mobility	Access
Definition of Transportation	Vehicle travel.	Person and goods movement.	Ability to obtain goods, services and activities.
Unit of measure	Vehicle-miles and vehicle-trips	Person-miles, person-trips and ton-miles.	Trips.
Modes considered	Automobile and truck.	Automobile, truck and public transit.	All modes, including mobility substitutes such as telecommuting.
Common Performance Indicators	Vehicle traffic volumes and speeds, roadway Level of Service, costs per vehicle-mile, parking convenience.	Person-trip volumes and speeds, road and transit Level of Service, cost per person-trip, travel convenience.	Multi-modal Level of Service, land use accessibility, generalized cost to reach activities.
Assumptions concerning what benefits consumers.	Maximum vehicle mileage and speed, convenient parking, low vehicle costs.	Maximum personal travel and goods movement.	Maximum transport options, convenience, land use accessibility, cost efficiency.
Consideration of land use.	Favors low-density, urban fringe development patterns.	Favors some land use clustering, to accommodate transit.	Favors land use clustering, mix and connectivity.
Favored transportation improvement strategies	Increased road and parking capacity, speed and safety.	Increased transport system capacity, speeds and safety.	Various strategies to increase transport and land use system capacity, efficiency and safety.
Implications for TDM	Considers vehicle travel reductions undesirable, except where congestion is extreme.	Supports TDM strategies that improve personal and freight mobility.	Supports TDM whenever it is cost effective.

This table compares the three major approaches to measuring transportation.

For example, from a traffic perspective, the best location for a public school (or other major public facility) is adjacent to a major roadway at the urban fringe where land is available for abundant parking, and most school transportation resources will be devoted to accommodating the needs of parents who chauffeur their children to school. This assumes that most staff and students will arrive by private automobile. From a mobility perspective, the best location is on a major urban street with adequate parking, frequent public transit service, and perhaps a bike lane, and school transportation resources can be devoted to accommodating both private automobile trips and school bus services. This assumes that most staff and students will arrive by automobile, but some will bicycle or use transit. From an accessibility perspective, the best location for a school may be within a residential neighborhood, even if driving is inconvenient there, because most students and some staff will walk or bicycle, and school transportation resources can be devoted to School Trip Management.

The Role of Different Modes

Different transport modes play different roles in providing mobility and accessibility. For example, nonmotorized modes serve shorter-distance trips and motorized modes serve longer-distance mobility. Some modes are more suitable for people with physical disabilities or low incomes. Some modes are particularly important for certain industries.

Standard transport statistics indicate that motor vehicles are by far the most important form of transport, implying that other modes do little to provide accessibility. Travel surveys indicate that in most North American communities more than 90% of households own an automobile, and that more than 90% of trips are made by automobile, while only about 5% of trips are made by nonmotorized modes and less than 2% are made by transit. This suggests that the only way to significantly improve transport is to improve automobile travel, and that 90% or more of transport funding should be devoted to automobile-oriented improvements.

But the high priority given automobiles and the low priority given other modes is partly an artifact of how data are collected and presented. Most travel surveys only count the primary mode used between relatively large Transportation Analysis Zones (TAZs), and some only count peak-period travel or commute trips. Most travel surveys are biased in ways that undercount shorter trips and travel by lower-income people (Stopher and Greaves, 2007). As a result, they undercount shorter trips (those occurring within a TAZ), nonmotorized links of motorized trips, off-peak trips, non-work trips, travel by children, and recreational travel. Although only about 5% of trips are made exclusively by nonmotorized modes, about four times as many involve at least some walking or cycling on public right-of-way. For example, most surveys would not count a walk from a parking space to a destination, or a walk from work to a nearby diner for lunch. If a traveler cycles 10 minutes to a bus stop, rides a bus for five minutes, and takes another 5-minute walk to their destination, this bike-transit-walk trip is usually coded simply as a transit trip, even though the nonmotorized links take more time than the motorized link.

Although most households own an automobile, many members of automobile-owning households cannot drive or must share a vehicles with other drivers. Motorists often use alternative modes when their automobile is unavailable due to a mechanical failure or other problems, and an increasing portion of travelers are choosing to walk, bicycle or use transit for personal or financial reasons, even if they have the option of driving. Although only about 2% of total trips are made by public transit, about 5% of US adults report that they rely primarily on public transit for transport, and 12% used public transit at least once during the previous two months. On busy urban corridors where traffic problems are greatest, transit often carries a significant portion of urban-peak travel.

In most communities, driving is relatively convenient and inexpensive except under urban-peak conditions, or for circulation within neighborhoods and commercial centers. These are exactly the situations in which transit and nonmotorized modes can be most effective. As a result, transit and nonmotorized improvements are often the best way to reduce current transport problems.

Glossary

Linked/Unlinked Trip: An unlinked trip is a passenger trip make on a single vehicle, such as a single automobile or bus ride. A linked trip is a person’s entire trip between an origin and destination, which may involve transferring between vehicles (e.g., Park & Ride or bus and rail transit), or multiple stops, such as stopping at a daycare center or store along a commute trip.

Land Use Accessibility

Land use patterns have important impacts on Accessibility. The location of activities and destinations affects accessibility, and different types of land use patterns are most suitable for different transport modes. Land use accessibility is often described as convenience, that is, the ease with which they can reach activities and destinations. A shop that is relatively accessible to consumers is called a convenience store, and a home near common destinations is said to have a convenient location.

Several land use factors affect accessibility:

· Density (number of people or jobs per unit of land area) increases the proximity of common destinations, and the number of people who use each mode, increasing demand for alternative modes such as walking, cycling and transit.

· Land use mix (locating different types of activities close together, such as shops and schools within or adjacent to residential neighborhoods) reduces the amount of travel required to reach common activities.

· Clustering (commercial districts, shopping malls, recreational centers) allows more destinations to be visited during each trip.

· Network connectivity (more roads or paths that connect one geographic area with another) allows more direct travel. The Interconnectivity Index (Ewing, 1996) can be used to evaluates how well a path or road network connects destinations.

Most people rely on commercial and public services they can reach within 10-minutes, and try to choose jobs that they can reach within a 40-minute commute (of course there are many exceptions, but these are reasonable reference values). This means, for example, that shifting travel from automobile to nonmotorized modes requires that commercial and public services be available within a convenient 10-minute walk or bike ride, and suitable worksites be located within a 40-minute walk or bike commute.

Access can be evaluated at different geographic scales.

· At a very fine-grained scale, accessibility is affected by the quality of the pedestrian conditions and the clustering of activities within a site, mall, campus or small district. For example, strip commercial development tends to be less accessible than a commercial center because customers, clients and employees can walk between businesses rather than needing to drive to each destination.

· At the neighborhood level, accessibility is affected by the quality of sidewalks and bicycle facilities, street connectivity, geographic density and mix. For example, a more accessible neighborhood will tend to have shops and public services (e.g., schools) within or adjacent to residential areas so some errands can be made by walking, cycling, transit, or short car trips.

· At the regional level, accessibility is affected by street connectivity, transit service, geographic density and mix. A more accessible region will have a network of many roads (rather than just a few major arterials) and efficient transit service that makes it convenient to travel within the region by car or transit.

· Interregional accessibility refers to the quality of highways, air service, bus and train service, and shipping services.

Critics of Smart Growth sometimes argue that increased land use density is harmful because it increases traffic congestion. Whether this argument is right or wrong depends on how transportation is measured. Traffic-based measurement units, such as level-of-service or average traffic speed on a particular section of roadway, indicate that increased density reduces transportation system performance. However, accessibility-based measurements, such as the generalized cost required to reach common destinations, indicate that increased density can improve overall accessibility. Increasing population and Clustering business activities may reduce traffic speeds but will also reduce average trip distances, so total transport costs (time and money) may decline.

GIS technologies make it possible to quantify land use accessibility by measuring average distances between various types of activities, such as between homes and commercial services or employment opportunities. Land use accessibility is sometimes measured “as the crow flies,” but that approach may be inaccurate since direct travel is often impossible due to barriers such as unconnected or congested roads, and barriers to walking. More detailed analysis is often required to determine actual travel times by different modes. Micro-scale modeling (i.e., analysis at the individual street or block level) is needed to evaluate pedestrian accessibility.

Trade-offs Between Different Types of Accessibility

There are inherent conflicts between different forms of accessibility. This occurs because a vehicle’s space requirements, risk and noise impacts increase with speed, and because land use patterns optimal for one mode are generally not optimal for other modes. As a result, increased vehicle mobility (travel speed and distance) tends to reduce other forms of accessibility, while improving accessibility by non-automotive modes, and improving land use accessibility, often requires constraining automobile traffic volumes and speeds. These conflicts are manifested in many specific ways.

· Limited access highways designed for maximum vehicle mobility have poor accessibility (few offramps, driveways or cross-streets), while road designed for maximum accessibility (many driveways and intersections) cannot safely accommodate higher-speed traffic.

· Land use patterns that maximize automobile access (low density development with activities located along arterials and highway intersections) tend to have poor transit access, while transit-oriented development (clustered development with limited parking and good pedestrian accessibility) tends to have traffic and parking problems.

· Wide roads, and higher traffic speeds tend to create barriers to walking, so vehicle and pedestrian street design objectives often conflict.

Although careful design can mitigate some of the intermodal conflicts, they are to some degree unavoidable. For example, a pedestrian bridge can improve nonmotorized accessibility across a busy highway, but such facilities are too expensive to build at everywhere they might be needed, and they are inconvenient to use (they generally require climbing a ramp or stairs, and may seem unsafe to users). Similarly, structured rather than surface parking can improve walkability by reducing the amount of land devoted to parking around activity centers, but significantly increases facility costs.

Because of these inherent trade-offs, planning decisions that favor one form of access over others can create a self-fulfilling prophecy. For example, if school planners choose a location that maximizes automobile access it probably will have high vehicle trip and parking generation rates. However, if the school is located within the residential neighborhood and designed for nonmotorized accessibility, a much larger portion of students and staff may arrive without a car.

Current transport planning practices tend to rely on traffic- and mobility-based measurements for evaluating transportation system performance and so are biased in favor of automobile access at the expense of other modes. Increased road and parking capacity is often called an “improvement,” while the negative impacts on walking and cycling access are ignored. Objective language uses neutral terms, such as “added capacity,” “additional lanes,” “modifications,” or “changes.”

Biased Transport Planning Language (Lockwood 2004)

Many transport planning terms unintentionally favor motor vehicle travel over other forms of access. For example, increased road and parking capacity is often called an “improvement,” although wider roads and larger parking facilities, and the increased traffic volumes and speeds that result, tend to degrade pedestrian and cycling mobility. Calling such changes “improvements” indicates a bias in favor of one mode over others. Objective language uses neutral terms, such as “added capacity,” “additional lanes,” “modifications,” or “changes.”

The terms “traffic” and “trip” often refer only to motor vehicle travel. Short trips, non-motorized trips, travel by children, and non-commute trips are often undercounted or ignored in transport surveys, models, and analysis. Although automobile and transit trips often begin and end with a pedestrian or cycling link, they are often classified simply as “auto” or “transit” trips.

The term “efficient” is frequently used to mean increased vehicle traffic speeds. This assumes that faster vehicle traffic always increases overall efficiency. This is not necessarily true. High vehicle speeds can reduce total traffic capacity, increase resource consumption, increase costs, reduce transportation choice, create less accessible land use patterns, and increase automobile dependency, reducing overall system efficiency.

Transportation professionals often rate the overall quality of the roadway network based on Level of Service (LOS) ratings that evaluate conditions for automobile traffic, but apply no comparable rating for other travel modes. It is important to indicate which users are considered when level of service values are reported.

Biased Neutral Terms

Traffic Motor vehicle traffic, pedestrian, bike traffic, etc.

Trips Motor vehicle trips, person trips, bike trips, etc.

Improve Change, modify, expand, widen

Enhance Change, increase traffic speeds

Deteriorate Change, reduce traffic speeds

Upgrade Change, expand, widen, replace

Efficient Faster, increased vehicle capacity

Level of service Level of service for…

Examples:

Biased: Level of service at this intersection is rated “D.” The proposed improvement will cost $100,000. This upgrade will make our transportation system more efficient by enhancing capacity, preventing deterioration of traffic conditions.

Neutral: Level of service at this intersection is rated “D” for motorists and “E” for pedestrians. A right turn channel would cost $100,000. This road widening project will increase motor vehicle traffic speeds and capacity but may reduce safety and convenience to pedestrian travel.

Evaluating transportation based on traffic and mobility tends to place little value on travel substitutes and land use management strategies, because they reduce the need for physical travel. From this perspective, higher density, Clustered development is usually considered harmful because it tends to increase congestion and reduce roadway level-of-service, even if this is offset by improved access that reduces per capita vehicle travel and congestion delay (Land Use Impacts on Transportation). Only by measuring transport in terms of access can all impacts and transportation improvement options be considered, as illustrated in Table 3. Measuring transportation in terms of access tends to recognize the full value of Transportation Demand Management and Transportation Choice.

Table 3 Comparing Transportation Improvement Strategies

Transportation Improvement Strategies	Traffic	Mobility	Access
Roadway expansion	X	X	X
Transit improvements		X	X
Ridesharing		X	X
Pedestrian and cycling improvements		X	X
Delivery services			X
Tele-access			X
Location-Efficient Development			X

When transportation is measured in terms of vehicle traffic, the main solution to transportation problems is to expand road capacity. When measured in terms of mobility, transit, ridesharing and nonmotorized transportation improvements are also recognized as potential solutions. When measured in terms of access, the widest possible range of solutions can be considered, including strategies that substitute for physical travel.

To the degree that transport planning relies on traffic- and mobility-based indicators to evaluate transport system performance, and there are conflicts between different forms of access, these practices violate the principle of economic neutrality in planning and investment decisions, and so represent a Market Distortion that reduces Transport Options and increases Automobile Dependency. For example, if transport system performance is evaluated in terms of roadway level-of-service, average vehicle travel speeds and parking convenience, the best location for public facilities such as schools and post offices will appear to be along major arterials or highways, at the urban fringe where land is available for abundant parking, with no consideration to negative impacts on access by walking, cycling and transit, or the fact that such dispersed locations requires longer trips. These planning practices encourage the use of public resources to widen roads and provide parking, even if other approaches, such as improving walking and cycling conditions, improved transit service, telecommunications or delivery services, support for TDM programs, or Smart Growth land use practices would be more cost effective and socially beneficial overall.

This is not to say that every transport and land use planning decision would completely change if accessibility-based measurement techniques were used to evaluate transport system performance, but there would probably be many changes, often in subtle and incremental ways that affect the location and design of public facilities; the distribution of public funding between roads, parking facilities, nonmotorized facilities, transit service and TDM programs; and zoning codes and development practices. The cumulative result would probably be substantial, as can be seen by contrasting transport and land use planning practices in suburban North American communities (where the emphasis is on mobility) and European communities (where the emphasis tends to be more on accessibility).

Reference Units

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. For example, a city’s transport budget 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. Measured one way, a particular program or project may seem costly and inefficient. Measured another way and the same proposal may seem affordable and worthwhile.

For example, a particular project may seem expensive when measured as total lifetime costs, but cheap if measured as “cents per day” per person. Generally, the best approach is to report costs and benefits in real (inflation adjusted) per-capita-annual-dollars, which is relatively easy to understand and compare with other common expenditures. Exactly which costs are included, and the group of people included in the denominator (which can be residents, taxpayers, households, users, etc.) should be clearly defined.

It is also helpful to compare project costs with similar program, such as existing program costs, or with peers. For example, a new transportation program can be compared with current transportation expenditures, or with what other jurisdictions spend on similar services. If possible, estimate incremental costs and benefits. For example, when analyzing a public transit project or mobility management program, estimate the project costs and the value of various savings and benefits to governments, businesses and consumers.

It is important to be comprehensive and realistic when comparing different modes. For example, when comparing the cost efficiency of road and transit improvements, it is important to estimate the full incremental costs of each option in a particular situation, such as on a particular corridor. It would be unfair to compare the full cost of providing urban transit services with just the cost of adding a roadway lane, since automobile trips also require parking spaces at destinations, and they require each traveler to pay vehicle ownership and operating costs (see ”Common Errors When Comparing Capacity Expansion and TDM Options” in the Evaluation Chapter).

Below are some examples of common reference units.

· 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.

Example

Consider the daily travel of somebody who commutes by car but walks and bikes for errands, as summarized in Table 4. A traffic perspective, which only counts motor vehicle travel, classifies her as an auto-commuter and measures her car mileage. A mobility perspective also counts walking and cycling travel, but since driving represents 87% of mileage, considers nonmotorized modes of little importance. However, an access perspective indicates that driving represents just 58% of her travel time and only 40% of her trips, suggesting a more important role for alternative modes.

Table 4 Example of Daily Person Trips

Purpose	Mode	Distance (miles)	Time (minutes)
To work	Drive	15	30
From parking to office.	Walk	0.2	4
To restaurant for lunch.	Walk	0.5	10
From restaurant after lunch.	Walk	0.5	10
From office to parking.	Walk	0.2	4
To home.	Drive	15	30
To commercial center.	Bike	1	6
Errands (travel between shops)	Walk	0.5	10
Home from shopping center.	Bike	1	6
Walk dog.	Walk	0.5	10
Drive	2 trips (20%)	30.0 (87%)	60 (50%)
Walk	6 trips (60%)	2.4 (7%)	48 (40%)
Bike	2 trips (20%)	2.0 (6%)	12 (10%)
*Totals*	*10 trips (100%)*	*34.4* *(100%)*	*120 (100%)*

(Assumes Drive = 30 mph, Walk = 3 mph, Bike = 10 mph. Values in parentheses indicate percentage of total travel.)

Different perspectives give different conclusions as to the best way to improve her transport. A pedestrian shortcut that reduces walking distance from her office to nearby restaurants by 0.2 miles provides only a 1% reduction in travel distance, and so appears to have little value if measured by mileage. But this saves 12% of total travel time, the same time savings provided by a major roadway improvement that increases average traffic speeds from 30 to 38 mph for a 15-mile commute.

Similarly, a stretch of road might carry 5,000 cars with 6,000 passengers, 100 transit buses carrying 2,000 passengers, 500 pedestrians, 200 bicycles, and have 100 adjacent homes and businesses. Traffic-based analysis, measured in vehicle-trips, considers motorists the dominant road user group, justifying roads designed to maximize vehicle traffic volumes and speeds. Mobility-based analysis, measured in person-mile, also considers motorists the primary road user group, but gives greater value to transit buses and rideshare vehicles, and so may justify HOV Priority features. Access-based analysis, measured in person-minutes-of-exposure, gives greater value to pedestrians, cyclists and residents, since they spend more time on the roadway. This justifies far greater emphasis on Walking and Cycling Improvements, Traffic Calming, Vehicle Restrictions and New Urbanist design that balances the interests of various road users.

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). For example, marginal analysis means that the costs of expanding road capacity are assigned to peak-period travelers, since those are the trips that require it. Marginal impacts often differ significantly from average impacts. For example, highway costs may average just 5¢ per vehicle-mile, but the marginal cost of urban-peak travel may be ten or twenty times higher if it requires increasing roadway capacity. Analysis based on average costs will often understate the full savings that can result from TDM strategies that manage peak period travel.

Measurement units should reflect marginal impacts, that is, the benefits or costs of an additional increment of consumption. When costs occur during different years their values should be adjusted to reflect inflation and discounting (TDM Evaluation).

Table 5 compares how various measurement units tend to affect transportation planning decisions.

Table 5 Comparing Measurement Units

Unit	Transportation Planning Implications
Roadway LOS, traffic congestion delay.	Favors investments that benefit peak-period vehicle travel and automobile-dependent urban areas (where congestion is worst).
Peak-period vehicle-mile	Favors investments that benefit peak-period vehicle travel.
Lane-mile	Favors investments in areas with maximum public roads, such as rural areas.
Vehicle-mile	Favors investments in automobile-dependent areas.
Vehicle-trip	Favors investments in automobile-dependent urban areas.
Passenger-mile and ton-mile	Equal consideration to automobile, transit, ridesharing improvements.
Passenger-trip	Equal consideration to all transportation modes, including walking and cycling.
Per capita	Equal consideration to all access improvements, including mobility substitutes and land use management strategies.

Are Buses More Polluting Than Automobiles?

Here is an example of how different measurement units can result in very different analysis results.

· If compared per current vehicle-mile, buses tend to be more polluting than automobiles.

· If compared per current vehicle-year, buses tend to be far more polluting than automobiles, because they have greater emissions per vehicle-mile, and tend to be driven more miles per year.

· If compared per current average passenger-mile, buses tend to produce less emissions of most pollutants than an average automobile.

· If compared per future average passenger-mile, buses tend to produce even less emissions of most pollutants than an average automobile due to new emission standards for heavy urban vehicles.

· If compared per shifted future passenger-mile, buses tend to produce even less emissions, since many transit buses have excess capacity, and so accommodating a traveler who shifts from automobile to a transit bus produces minimal incremental emissions of most pollutants.

Which measurement unit to apply depends on the question being considered. For example, since older diesel urban transit buses produce a relatively large amount of pollution emissions per vehicle-year, they may be one of the best targets for a program that subsidizes introduction of cleaner vehicle technologies. On the other hand, when evaluating the net emission reductions from a strategy that encourages commuters to shift from driving to riding public transit, the analysis should be based on the incremental emissions produced per shifted passenger-mile. Average emission rates are only appropriate for analysis if buses are already full and each 1% increase in ridership would require a 1% increase in bus vehicle-miles, an uncommon situation.

Additional Considerations

Measuring transportation based on access raises several issues that are discussed below.

The Function of the Streets

Transportation engineers tend to assume that streets exist for mobility and so they count moving vehicles and, sometimes, moving pedestrians. Transportation engineers have long recognized the value of vehicle parking, but they do not generally have a similar positive value to pedestrians who are stopped, such as people standing or sitting. Although they could assign a positive value to a parent driving a child to play at a park, they do not generally assign a positive value to children playing on a sidewalk or in a street. A person walking to and from a parked car, or to and from a bus stop, is often not counted as a “pedestrian,” even when they walk on public sidewalks. Complete Streets policies recognize the many users and uses of streets, and therefore the need to balance their interests.

Geographic Scale

Access can be evaluated at many different geographic scales.

· Interregional accessibility refers to the quality of highways, air service, bus and train service, and shipping services.

Planning and Investment Decisions

Performance Indicators based on traffic (roadway Level of Service, vehicle delay, traffic speeds, vehicle mileage) assume that improving transportation requires increasing vehicle travel and speed. This inherently favors faster modes, longer-distance trips and more dispersed land use. For example, this perspective assumes that a 50-mile automobile commute provides more value to society than a 10-mile transit commute, which provides more benefit than a 5-mile bicycle or a 1-mile walking trip. Since virtually all transportation activities use public resources (roads, parking facilities, traffic law enforcement and management services) and impose external costs (congestion, crash risk, pollution), this perspective assumes that society should provide more public subsidies for a longer trip and a faster mode than for a shorter trip or a slower mode.

Performance Indicators based on traffic value alternative modes only in terms of direct benefits to motorists (e.g., walking is only of value as a way to access parked cars, transit is only of value if it reduces traffic congestion), and often ignore them altogether. For example, this perspective could favor a road widening project that saves motorists $50 per day in travel time, even if it causes $51 per day of additional delay to pedestrians and cyclists, because congestion impacts are only measured with regard to motorized traffic (TTI, 2001). This can lead to increased Automobile Dependence due to wider roads, increased traffic and more dispersed land use (Levine and Garb, 2000).

Performance Indicators based on access perspective (travel times, cost per trip) is neutral with regard to travel mode, distance or speed. For example, this perspective assumes that telecommuting, a 1-mile walking trip, or a 50-mile automobile trip can be of equal value to society if they each provide access to school or work. This expands the range of solutions that can be considered and allows demand management to be considered equally with capacity expansion (Least Cost Planning).

Allocating federal, state or provincial transportation funds based on traffic performance indicators favors automobile-dependent areas and automobile dependency. It encourages communities to define their transportation problems as vehicle traffic problems, and discourages them from implementing TDM strategies, since doing so reduces the fund they can receive. Allocating funds based on mobility performance indicators (passenger-miles, passenger delay) gives equal consideration to automobile, transit and ridesharing strategies, but still favors longer trips and faster modes. Allocating funds based on passenger-trips or population treats all trips of equal value, and allows mobility substitutes and land use management strategies that reduce the need for physical travel to be considered equally with other transportation improvement options.

Basic Access

Basic Access refers to people’s ability to access goods, services and activities that are considered valuable to society, such as emergency services, medical services, education, employment, basic food and clothing, and freight deliveries. This recognizes that some transport activities are particularly important to society, and so justifies policies that favor certain types of trips (those considered to provide Basic Access) over others (those considered less important). Evaluating Basic Access requires measuring transportation options and costs for specific types of trips that are considered to provide Basic Access.

For example, transport costs as a portion of income, and travel time, required for people who are transportation disadvantaged (i.e., low income, physically disabled, elderly, etc.) to reach medical services, education and employment opportunities can be considered indicators of Basic Access. Similarly, transportation barriers and delay to emergency vehicles, public transit and freight vehicles may be considered indicators of Basic Access.

Modeling

Current transport Models primarily measure vehicle traffic. They often do a poor job measuring mobility and access. Travel surveys and traffic monitors often undercount short trips, non-work travel, travel by children, recreational travel, and nonmotorized links of motorized travel. Trips that are classified as “auto” or “transit” trips are often “walk-auto-walk,” or “walk-bus-walk” trips, but the walking component is not counted (Evaluating Nonmotorized Transport).

The actual number of nonmotorized trips is usually much greater than what conventional surveys indicate. For example, if travel surveys only measure the portion of trips that consist entirely of walking, then walking typically represents about 5% of total trips. But if surveys measure the portion of trips that include a portion of walking, then walking typically represents about 20% of trips, as indicated in the table below. Rietveld (2000) found that the actual number of nonmotorized trips is about six times greater than what conventional surveys indicate.

Table 6 Commute Trips By Mode (Statistics Canada, 1992)

	Car Only	Walking All or Part	Transit All or Part
Winnipeg	73%	16%	15%
Vancouver	72%	20%	12%
Calgary	72%	21%	12%
Canada	69%	22%	10%
Toronto	61%	24%	20%
Ottawa	60%	33%	16%

Similarly, traffic models can predict with precision the impacts that a road improvement may have on vehicle travel, but are generally unable to predict impacts on pedestrian mobility or land use patterns. As a result, data and Models for evaluating traffic tends to be more precise but less accurate than what is available for evaluating mobility or access. Evaluating mobility and access may require sacrificing precision in order to improve overall accuracy.

Accuracy Versus Precision

Statisticians make a distinction between accuracy and precision. “Accurate” means truthful or correct. “Precise” means measured using small units. Data can be very precise, but inaccurate. It would be precise but inaccurate to say that a meter equals 29.378 inches, it is actually more accurate to say that a meter equals “a little over one yard,” although that sounds less impressive.

For example, doctors often measure their patients’ weight to help evaluate their health. But a weight value by itself is an inadequate indicator of health. It would be inaccurate to say that everybody who weighs less than 175 pounds is healthy and everybody who weighs more than 175 pounds is unhealthy. People with different heights and builds have different optimal weights, so medical professionals must use weight-height tables or body-mass indices to interpret the health implications of a particular person’s weight.

A standard medical scale can measure a person’s weight within about 0.5 pound of accuracy. A more expensive scale can provide greater precision, but there is little point in purchasing a super-precise scale simply to track body weight. Knowing that you weigh exactly 168.305 pounds rather than about 170 pounds does little to improve your health assessment. Weight is relatively easy to measure and understand, but focusing too much attention on weight may distract doctors and patients from considering other health factors that are equally important but more difficult to measure, such as whether you eat a balanced diet or get sufficient exercise.

Vehicle traffic and mobility can be measured and evaluated as physical activities. Access is more difficult to measure because it is affected by a variety of factors, including proximity, transportation choice and travel costs. As a result, evaluating access requires integrated transportation/land use Models that incorporate both physical and economic factors and so can calculate and compare the changes in total costs that result from a change in the transportation systems and land use patterns (Abraham, 1998).

Examples

Here are examples of how differences in how transportation is measured can affect planning decisions.

Road Safety Analysis (Safety Evaluation)

Transportation officials often measure traffic crash and fatality rates per million vehicle miles. From this perspective, road risk is declining and current traffic safety efforts are a success and should continue. However, this increase in safety is largely offset by increased mileage. As a result, per capita crash costs have declined little despite massive investments in safer roads and vehicles, tremendous increases in the use of seatbelts and other safety devices, reductions in drunk driving, and improvements in emergency response and trauma care. Taking these factors into account, much greater casualty reductions should have been achieved. Traffic crashes continue to be the greatest single cause of deaths and disabilities for people in the prime of life. From this perspective, traffic safety continues to be a major problem, current safety efforts have failed, and new approaches are needed to really improve road safety. North America continues to have one of the highest per capita traffic fatality rates in the world.

Figure 1 U.S. Traffic Fatalities (Safety Evaluation)

Traffic crashes show a significant decline if measured per vehicle-mile, but not if measured per capita.

When road risk is measured using a mileage-based rate, increased mileage is not considered a risk factor and travel reductions are not considered a safety strategy. From this perspective, an increase in total crashes is not a problem provided that there is a comparable increase in mileage. Increased vehicle travel can even be considered a traffic safety strategy if it occurs under relatively safe conditions (such as on grade-separated highways), because more safe miles reduce per-mile crash and casualty rates.

Mileage-based crash rate analysis favors highway safety projects that encourage increased vehicle travel. Measuring road risk per vehicle-mile tends to ignore TDM as a traffic safety or public health strategy. Per capita crash rate analysis allows TDM strategies that reduce total vehicle travel to be considered as road safety programs. TDM may be one of the most cost effective ways to improve road safety and public health, and safety and health benefits are among the greatest potential benefits of TDM.

Unit Costs of Incremental Peak-Period Vehicle Trips (Transportation Costs)

Project costs should be measured with respect to incremental benefits. Adding urban highway capacity typically costs $4 million per lane-mile, representing an annualized cost of about $200,000. A typical two-lane highway lane carries 5,000 vehicles during urban peak periods, and 15,000 total vehicles per day. The cost of adding a third traffic lane to reduce congestion should be charged to the peak-period users rather than to all road users, since off-peak travelers do not benefit. The unit cost is therefore 16¢ per peak-period vehicle-mile (assuming 250 annual congested travel days), not the 5¢ per total vehicle-miles. The cost efficiency of a TDM congestion management alternative should be compared with the highway capacity expansion option based on the higher incremental cost rather than the lower average cost.

Road Pricing Objectives

A traffic-oriented perspective considers Road Pricing primarily as a way to fund additional roadway capacity, even if this reduces overall accessibility by encouraging dispersed land use and automobile-dependent transportation systems (Levine and Garb, 2000). An access-oriented perspective considers Road Pricing a strategy to encourage more efficient use of existing road capacity and more accessible land use patterns.

Equity Analysis

How transportation is evaluated and measured affects Transportation Equity. Evaluating transportation based on vehicle traffic tends to favor improvements to automobile travel. Evaluating transportation in terms of mobility gives more support to transit and ridesharing improvements. Evaluating transportation in terms of access also supports nonmotorized modes, mobility substitutes, land use management, and values having a diverse transportation system (Evaluating Transportation Choice). Since people who are transportation disadvantaged tend to rely less on automobile travel and more on alternative modes, and value cost savings that can result from more efficient land use, measuring transportation in terms of access tends to support transportation equity objectives.

Table 7 Implications of Different Transportation Evaluation Criteria

Unit	Description	Equity Implications
Congestion (V/C Ratio, vehicle delay)	Transport investments are evaluated according to which investment provides the greatest congestion reduction at the lowest cost.	Favors motorists, particularly those who want to drive on congested roads.
Vehicle Miles Traveled (VMT)	Transport investments are evaluated according to where vehicle travel demand is greatest.	Favors motor vehicle improvements and higher mileage motorists.
Passenger Miles Traveled (PMT) or Passenger Trips	Transport investments are evaluated according to where mobility can be increased at the lowest costs.	Primarily favors motorists, but can also favor some transit users.
Access	Transport investments are evaluated according to the barriers that people face obtaining goods and reaching activities.	Provides the most egalitarian distribution of transportation resources.
Basic Mobility	Transport investments are evaluated according to whether they improve Basic Mobility.	Favors people who are transportation disadvantaged.

Equity analysis is affected by how transportation is measured.

Best Practices

Since access is the ultimate goal of most transportation activity (except the small amount of travel that has no destination), it is usually the best perspective for transportation planning and evaluation.

Accessibility can be difficult to measure so several Performance Indicators can be used together. These can include:

· Average daily travel times for residents.

· Average door-to-door commute times for residents.

· Average annual transportation expenditures per capita.

· Freight transportation delivery speeds and costs.

· Quality of transportation choices (driving, transit, ridesharing, walking, cycling, etc.).

· Quality of transportation choices for non-drivers and lower-income people.

· Quality of the pedestrian and cycling environments.

· Quality of transportation substitutes (telecommunications and delivery services).

· Land use accessibility (e.g., number of jobs and public services within walking distance of residents).

· Crashes and crash fatalities per capita.

· Transportation energy consumption per capita.

· User satisfaction survey results (for motorists, transit users, pedestrian facility users, etc.).

· Results of user surveys identifying access barriers and problems.

It is important to evaluate accessibility from various perspectives, including those of different modes (driving, transit, walking), and different geographic and demographic groups (children, commuters, parents, elders) groups. A policy or project may improve accessibility for some people but degrade it for others. For example, increasing road and parking capacity, and increasing vehicle traffic volumes and speeds, tends to increase mobility and access for automobile trips, but reduce access for nonmotorized trips (and therefore transit, since most transit trips involve also involve walking).

In many transportation planning situations, access should be evaluated for a particular groups. For example, school planners should consider how different development options affect many students would be able to walk or bicycle to school. Transportation planners should consider what portion of non-drivers in a community live within convenient walking distance of public services (shops, parks, etc.) and transit stops. Social planners should consider the commute time required by unemployed people to access jobs, and how such access can be improved.

Wit and Humor

There are three kinds of mathematicians: those who can count, and those who can’t.

Related Chapters

For more information on the concepts and techniques discussed in this chapter see TDM Evaluation, TDM Planning, Comprehensive Transportation Evaluation, Transportation Elasticities, Multi-Modal Level-of-Service Indicators, Transportation Statistics, Data Collection and Sustainable Transportation.

Examples and Case Studies

Florida Multi-Modal Quality-Of-Service Standards (FDOT, 2002)

The Florida Department of Transportation (FDOT) has developed minimum Level-of-Service standards for state transportation facilities, which indicate specific adequacy standards for automobile, transit, cycling and walking. The FDOT has published the Florida Quality/Level of Service Handbook and supportive software for use by engineers, planners, and decision-makers at planning and preliminary engineering levels. This Handbook primarily provides tools to address multimodal transportation service inside the roadway environment (essentially inside the right-of-way). It is based on the following documents:

Highway Capacity Manual (HCM2000) methodologies for automobiles and trucks.
Transit Capacity and Quality of Service Manual (TCQSM) for buses.
Bicycle LOS Model to evaluate LOS for bicyclists.
Pedestrian LOS Model to evaluate LOS for pedestrians.

San Francisco Multi-Modal Level-Of-Service (Hiatt, 2006)

San Francisco County is pursuing the use of multimodal LOS measures to evaluate network performance and identify network gaps. The County applies LOS standards as flexibly as possible while balancing the goal of simple, clear standards. The more flexible application of LOS standards, such as varying LOS standards by area or roadway type, may be more relevant for less urbanized areas with no significant multimodal transportation infrastructure. Urban, multimodal areas may find that the most effective LOS reform is to replace auto LOS standards with a measure and standard that allows for the short term auto congestion that results from infill development and improvements to transit, walking, and cycling.

The Human Capacity Manual (www.walksf.org/essays/pedCountEssay.html)

By G.Haze. The San Francisco Design Department

Pedestrian counting techniques for pre-automobile urban areas.

During negotiations concerning the 55 Page street development project, The Design Department conducted on-site movement studies, while acting as the Transportation Consultants for the SFBC.

Department observers studied Page Street between Gough and Franklin to present an accurate report of the movements of its public right-of-way. The observers followed standard Human Capacity Manual procedure for appraising and recording a street's activities.

Interestingly enough, some of the Department's observations differed from those of the project's private traffic engineers. We basically saw a different public right-of-way than they did. It was as if we viewed the world through different lenses, as if the two parties were studying a different streetscape all together.

For example, our AM peak hour pedestrian count was more than four times higher than the traffic engineer's count. Using the 1985 Federal Highway Capacity Manual's pedestrian flow count methodology, the traffic engineers counted 33 pedestrians traveling in either direction during the AM peak hour. Using year 2000 Human Capacity Manual methodology, the Design Department counted 130 pedestrians during the AM peak hour.

This rather pronounced disparity has its origins in the way the counts were conducted. The traffic engineers counted all pedestrians that passed a certain point on the street, as if there was an imaginary line that crossed the street. The concept is very similar to the pressure-sensitive wires which are used to count cars. In terms of perception, they viewed the street through a very thin, specific amount of space-the imaginary line-while the Department viewed the entire block. Their pressure sensitive wire was the imaginary line, our pressure sensitive surface was every inch of the street segment.

Since there is currently no legal classification for people who move through the city using wheeled conveyances that do not have drive-trains, such as skateboards and/or in-line skates, we counted users of such modes as pedestrians. The Department is currently developing a classification for these types of movements. (see sec. 92.8 HCM "the shadowland").

The Department also counted static pedestrians or persons sitting, or standing still in the public-right-of way, and/or people that moved in a repetitious, localized way. Under this appraisal system, two persons sitting at a sidewalk table for twenty minutes are counted as four pedestrians. The people are counted repeatedly because they remain in the public-right-of-way. The rationale for this technique is once again linked to the concept of presence.

During every count cycle, these persons are still present on the street and therefore should be represented. Our spatial interpretation of the public-right-of-way is not exclusively based upon constant movement. It is designed to reflect all of the many uses of the street. Static pedestrianism or "hanging out" is one of the most popular of these uses.

Besides the two skateboarders riding the wrong way down the middle of the northbound traffic lane and the people passing the time at the corner deli's outdoor tables, the traffic engineers also missed every person who disembarked at the Page/Franklin Muni stop, and they missed persons who walked to, or from, parked cars or bicycles without crossing the line. We counted all of these people. Pedestrian means "one who travels on foot" When the soles of the Muni patrons shoes touched the pavement, the observers counted them.

Because, if these people are not counted then they do not exist within the transportation study and consequently are not legally represented users of the public-right-of-way. This an excellent example of the deficiencies of the Highway Capacity Manual methodologies. Such problems have led to the creation of the Human Capacity Manual.

Who were these uncounted people moving through the public-right-of way? Were they non-entities? Ghosts, phantoms that the eyes of the "experts" completely overlooked?

When a traffic engineer looks at the street, they only see certain things in certain ways. Many of the public right-of-way's uses are completely invisible, not on the radar, unseen and not represented. These activities exist in the shadowland, in the legal twilight zone behind the blinders.

References And Resources For More Information

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Ken Alder (2002), The Measure of All Things: The Seven-Year Odyssey and Hidden Error That Transformed The World, The Free Press, Simon & Schuster (www.simonandshuster.com).

BTS (2001), Special Issue on Methodological Issues in Accessibility: Journal of Transportation and Statistics, Vol. 4, No. 2/3, Bureau of Transportation Statistics (www.bts.gov).

Susan Chapman and Doug Weir (2008), Accessibility Planning Methods, Research Report 363, New Zealand Transportation Agency (www.landtransport.govt.nz/research/reports/363.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.

Reid Ewing (1993), “Transportation Service Standards – As If People Matter,” Transportation Research Record 1400, TRB (www.trb.org), pp. 10-17.

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FDOT (2002), Quality/Level of Service Handbook, Florida Department of Transportation (www.dot.state.fl.us/Planning/systems/sm/los/default.htm).

FHWA, Performance Measures Website (www.ops.fhwa.dot.gov/Travel/Deployment_Task_Force/perf_measures.htm), Federal Highway Administration.

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 (www.trb.org).

Rachel E.M. Hiatt (2006), An Alternative to Auto LOS for Transportation Impact Analysis, Transportation Research Board Annual Meeting (www.trb.org); at www.mdt.mt.gov/research/docs/trb_cd/Files/06-2306.pdf.

IHT (2000), Monitoring Walking, Department of the Environment, Transport and the Regions (www.roads.dtlr.gov.uk/roadnetwork/ditm/tal/walking/06_00).

Jeffrey Kenworthy (2008), Transport Heaven and Hell, ITS Magazine; at www.industry.siemens.de/traffic/EN/NEWS/ITSMAGAZINE/HTML/0802/fokus_1.html.

Jonathan Levine and Yaakov Garb (2000), Evaluating the Promise and Hazards of Congestion Pricing Proposals; An Access Centered Approach, Floersheimer Institute for Policy Studies (www.fips.org.il).

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.

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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 (2007), Evaluating Accessibility for Transport Planning, VTPI (www.vtpi.org); and www.vtpi.org/access.pdf.

Todd Litman (2007), 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), Well Measured: Developing Indicators for Comprehensive and Sustainable Transport Planning, VTPI (www.vtpi.org); at www.vtpi.org/wellmeas.pdf.

Todd Litman (2008), Multi-Modal Transport Planning, Victoria Transport Policy Institute (www.vtpi.org); at www.vtpi.org/multimodal_planning.pdf.

Ian M. Lockwood (2004), Transportation Prescription For Healthy Cities, Glatting Jackson Transportation Urban Design Studio, for presentation and Common Ground www.glatting.com/PDF/IML_RWJF_Paper2004.pdf.

Michael Meyer and Richard Schuman (2002), “Transportation Performance Measures and Data,” ITE Journal (www.ite.org), November 2002, pp. 48-49; based on Measuring System Performance: The Keys to Establishing Operations as a Core Agency Mission, Office of Operations, Federal Highway Administration (www.ops.fhwa.dot.gov/nat_dialogue.htm).

Chris Mitchell and Ronald Milam (2006), Implementation of Customer-Based Transportation Level of Service Policies, ITE Annual Meeting (www.ite.org).

Terry Moore and Paul Thorsnes (1994), The Transportation/Land Use Connection, Planning Advisory Service Report 448/449, American Planning Association (www.planning.org).

Debbie Neimeier (1997), “Accessibility: An Evaluation Using Consumer Welfare,” Transportation, Vol. 24, No. 4, Klewer (www.wkap.nl/prod/j/0049-4488), Nov. 1997, pp. 377-396.

Richard H. Pratt (2003), Traveler Response to Transportation System Changes, Interim Handbook, TCRP Web Document 12 (http://www.trb.org/TRBNet/ProjectDisplay.asp?ProjectID=1034), DOT-FH-11-9579.

John Pucher, Charles Komanoff, and Paul Schimek (1999), “Bicycling Renaissance in North America? Recent Trends and Alternative Policies to Promote Bicycling,” originally published in Transportation Research A, Vol. 33, No. 7/8, 1999, pp. 625-654; at www.vtpi.org/puchertq2.pdf.

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.

Piet Rietveld (2000), “Nonmotorized Modes in Transport Systems: A Multimodal Chain Perspective for The Netherlands,” Transportation Research D, Vo. 5, No. 1, Jan. 2000, pp. 31-36.

Statistics Canada (1994), General Social Survey on Time Use, 1992, reported in “Getting There” by Katherine Marshall, in Perspectives on Labour and Income, Statistics Canada.

Peter R. Stopher and Stephen P. Greaves (2007), “Household Travel Surveys: Where Are We Going?,” Transportation Research A, Vol. 41, Issue 5 (www.elsevier.com/locate/tra), June 2007, pp. 367-381.

TRB (1994), Highway Capacity Manual, Special Report 209, Transportation Research Board (www.trb.org).

Gerald Wilde (1984), “On the Choice of the Denominator in the Calculation of Crash Rates,” in S. Yager (ed.), Transport Risk Assessment, University of Waterloo Press (Waterloo).

WRDC (2004), Measuring What Matters, Western Rural Development Center (www.extension.usu.edu/wrdc/resources/research/index.htm).

Michael Wright (1996), “Transportation Language Policy Memo,” City of West Palm Beach, Florida, 14 November 1996.

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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