Share Your Ideas for Evaluating Transport System Performance

Moving Ahead for Progress in the 21st Century (MAP-21), the new U.S. federal transportation law, has the following main goals:

1. Safety
2. Infrastructure condition
3. Congestion reduction
4. System reliability
5. Freight movement and economic vitality
6. Environmental sustainability
7. Reduced project delivery delays

 

These goals are limited and could lead to planning decisions that reduce overall transport system efficiency, depending on how they are interpreted and measured. For example, there are no references to social equity objectives such as improved mobility for non-drivers or increased affordability (i.e., costs as a share of budgets for lower-income households), nor public fitness and health objectives (i.e., increasing walking and cycling activity); congestion reduction is triple counted (congestion reduction, system reliability, and freight movement); and if impacts are measured using conventional metrics, such as roadway level-of-service and crash rates per vehicle-mile, the additional economic, social and environmental costs caused by induced vehicle travel and sprawl will be overlooked, as will many of the benefits of transportation demand management and smart growth policies.

MAP-21 emphasizes performance-based planning. This is good if done correctly. It means that transport planning decisions are based on their ability to achieve specific objectives such as congestion reduction and improved safety, and so tends to support innovative strategies such as transportation demand management, that do not fit into traditional funding categories. For example, congestion pricing, complete streets, smart growth development policies, and parking management strategies can all help increase transport system efficiency, but are poorly supported by conventional transport planning practices.

The effectiveness of this type of planning depends on the specific methods used to measure transport system performance. Conventional transport planning tends to use mobility-based indicators such as roadway level-of-service and the Travel Time Index. As discussed in my recent blog, Toward More Comprehensive Understanding of Traffic Congestion, these are inadequate for evaluating overall transport system performance because:

• They assume that transportation primarily means automobile travel, ignoring the important roles that other modes play in an efficient and equitable transport system. This tends to create a self-fulfilling prophecy in which automobile travel is favored over other modes, which increases its use and degrades alternatives.

• They assume that mobility (physical movement) is an end in itself, rather than a way to achieve accessibility (people's ability to reach desired services and activities) and so ignore other factors that affect accessibility such as the geographic distribution of destinations, roadway connectivity, the quality of alternative transport modes, and mobility substitutes such as telecommunications and delivery services. They therefore overlook ways that planning decisions intended to increase mobility can reduce other forms of accessibility. For example, conventional congestion evaluation can justify roadway expansions even if the wider roads and heavier traffic create barriers to pedestrian travel and stimulate sprawl development. 

• They ignore other important transport planning impacts and objectives, including consumer affordability, parking costs, the quality of mobility options for non-drivers, and land use impacts, to name a few. Since planning decisions often involve trade-offs between different objectives, these omissions can have significant impacts. More comprehensive evaluation is reqired to determine which planning decisions are most cost effective and beneficial overall.

• They measure congestion intensity rather than total congestion costs. For example, a current congestion indicators ignore the congestion costs reduces when travelers shift to alternative modes, and the travel time savings from more accessible land use development which reduces motorists' travel distances. In fact, the Travel Time Index actually implies that congestion is reduced if sprawl increases uncongested vehicle travel because congestion delays are divided into more total mileage.

• They are mono-modal. They generally do not consider the efficiency and comfort of other modes, such as bus crowding or pedestrian delays, or the congestion avoided if walking, cycling, ridesharing or public transport attract people out of their automobiles and so reduce their congestion delays.

• Conventional traffic models often underestimate generated traffic impacts. This tends to exaggerate roadway expansion benefits and undervalue negative impacts such as increased accidents, energy consumption, pollution emissions and sprawl-related costs.

 

This is not to deny that traffic congestion imposes significant costs on society by imposing travel delay and increasing fuel consumption and pollution emissions. But even using the relatively high estimates published by the Texas Transportation Institute, which I believe are exaggerated, congestion costs are moderate overall, less than some other transportation costs such as vehicle ownership, vehicle operation, roadway costs, parking facility costs and accident damages. As a result, it would not be cost effective to implement congestion reduction strategies that significantly increase those costs, for example, by requiring motorists to purchase special vehicles for urban commuting or if they increase accident risks, but congestion reduction strategies become much more cost effective if they help achieve other planning objectives such as parking cost savings, consumer savings or improved mobility of non-drivers.

The U.S. Department of Transportation is currently developing performance indicators, and is soliciting public comments through "listening sessions," including one scheduled for this coming Thursday, 25 October 2012, from 1:00 PM to 3:30 PM EDT. This is an opportunity for practitioners to contribute to policy decisions that will have major impacts on our future planning activities.

Here are my suggestions for more comprehensive transport system performance evaluation.

1. Consider the following impacts:

• Congestion (including traffic delays and public transit crowding)
• Roadway costs
• Parking costs and subsidies
• Consumer costs (vehicle ownership, vehicle operations, fares) and affordability (costs relative to budgets for lower-income households)
• Quality of mobility options for non-drivers
• Traffic crashes, measured per captia
• Energy consumption, measured per captia
• Pollution emissions, measured per captia
• Land use impacts (consistency with strategic development goals)
• Public fitness and health (amount that people walk and bicycle)

 

2. Evaluate impacts based on per capita annual costs rather than impacts per unit of travel. For example, evaluate congestion based on per capita annual congestion costs rather than roadway level-of-service, the Travel Time Index, or congestion costs per motorist so this cost can be compared with other impacts such as per capita consumer costs, road and parking facility costs, accident costs, and pollution costs.

3. Consider generated and induced travel effects when evaluating roadway expansion impacts. This recognzies that roadway expansion often provides little long-term reductions in traffic congestion, and by inducing additional vehicle travel and stimulating sprawl can increase other costs such as downstream traffic congestion, parking costs, accidents, consumer costs, energy consumption, pollution emissions, and reduced accessibility for non-drivers.

 

What do you think? Are these criticisms and suggestions appropriate? What impacts and indicators do you recommend transportation agencies use to evaluate transport system performance?

 

For more information

Philip Barham, Samantha Jones and Maja van der Voet (2012), State Of The Art Of Urban Mobility Assessment, Quality management tool for Urban Energy efficient Sustainable Transport (QUEST), Executive Agency for Competitiveness and Innovation, European Commission.

Robert L. Bertini (2005), You Are the Traffic Jam: An Examination of Congestion Measures, Department of Civil & Environmental Engineering, Portland State University, presented at the Transportation Research Board Annual Meeting.

Daniel Bongardt, Dominik Schmid, Cornie Huizenga and Todd Litman (2011), Sustainable Transport Evaluation: Developing Practical Tools for Evaluation in the Context of the CSD Process, Commission on Sustainable Development, United Nations Department Of Economic And Social Affairs.

Joe Cortright (2010), Driven Apart: How Sprawl is Lengthening Our Commutes and Why Misleading Mobility Measures are Making Things Worse, CEOs for Cities (www.ceosforcities.org).

DfT (2006), Transport Analysis Guidance, Integrated Transport Economics and Appraisal, Department for Transport.

Richard Dowling, et al. (2008), Multimodal Level Of Service Analysis For Urban Streets, NCHRP Report 616, Transportation Research Board.

Eric Dumbaugh (2012), Rethinking the Economics of Traffic Congestion, Atlantic Cities, 1 June 2012.

FHWA (2012), Performance Management Overview, U.S. Federal Highway Administration.

J. Richard Kuzmyak (2012), Land Use and Traffic Congestion, Report 618, Arizona Department of Transportation.

John N. LaPlante (2007), "Strategies for Addressing Congestion," ITE Journal, Vol. 77, No. 7, pp. 20-22.

Todd Litman (2003), "Measuring Transportation: Traffic, Mobility and Accessibility," ITE Journal, Vol. 73, No. 10, October, pp. 28-32. 

Todd Litman (2005), Well Measured: Developing Indicators for Comprehensive and Sustainable Transport Planning, Victoria Transport Policy Institute; summarized in "Developing Indicators For Comprehensive And Sustainable Transport Planning," Transportation Research Record 2017, TRB, 2007, pp. 10-15.

Todd Litman (2012), Smart Congestion Relief: Comprehensive Analysis Of Traffic Congestion Costs and Congestion Reduction Benefits, presented at the Transportation Research Board Annual Meeting.

WSDOT (2008), Performance Measurement Library, Washington State Department of Transportation.