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Toward More Comprehensive Understanding of Traffic Congestion

Conventional planning tends to consider traffic congestion asignificant cost and roadway expansion the preferred solution. It evaluates transport system performance based on indicators such as roadway Level of Service (LOS) and peak-period traffic
Todd Litman | September 13, 2012, 5am PDT
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Conventional planning tends to consider traffic congestion a significant cost and roadway expansion the preferred solution. It evaluates transport system performance based on indicators such as roadway Level of Service (LOS) and peak-period traffic speeds, and dedicates most transportation resources (road space and money) to roads and parking facilities. This results in predict and provide planning in which roadways are expanded to accommodate anticipated traffic, which creates a self-fulfilling prophecy by inducing additional vehicle use. Current congestion evaluation methods are crude and biased, resulting in excessive roadway capacity and a less diverse transportation system than is economically and socially optimal. My new report, Smart Congestion Relief: Comprehensive Analysis Of Traffic Congestion Costs and Congestion Reduction Benefits discusses these issues. Let me share highlights.

This is a timely issue. Motor vehicle travel grew steadily during the Twentieth Century so it made sense to devote significant resources to roadway expansion. During that period there was little risk of overbuilding since any additional road capacity would eventually fill. However, vehicle travel has peaked (see graph) and demand for alternatives is increasing due to demographic and economic trends including aging population, rising fuel prices, urbanization, health and environmental concerns, and changing consumer preferences. This requires more comprehensive evaluation that considers more impacts and options. 

Conventional congestion evaluation tend to be biased in various ways, as summarized in the following table. For example, conventional evaluation recognizes that wider roads improve automobile access but ignore their tendency to reduce walking and cycling access (called the barrier effect), and it favors a hierarchical road system that has higher-speed arterials over a more connected road system that has lower travel speeds but shorter travel distances. As a result, mobility-based planning can result in congestion reduction strategies that reduce overall accessibility by creating sprawled, automobile-dependent communities where activities are widely dispersed and alternatives to driving are inferior.

Congestion Costing Biases, Impacts and Corrections

Type of Bias

Planning Impacts


Mobility-based planning measures congestion intensity rather than total congestion costs

Favors roadway expansion over other transport improvements

Measure overall accessibility, including per capita congestion costs

Assumes that compact development increases congestion

Encourage automobile-dependent sprawl over more compact, multi-modal infill development

Recognize that smart growth policies can increase accessibility and reduce congestion costs

Only considers impacts on motorists

Favors driving over other modes

Use multi-modal transport system performance indicators

Estimates delay relative to free flow conditions (LOS A)

Results in excessively high estimates of congestion costs

Use realistic baselines (e.g., LOS C) when calculating congestion costs

Applies relatively high travel time cost values

Favors roadway expansion beyond what is really optimal

Test willingness-to-pay for congestion reductions with road tolls

Uses outdated fuel and emission models that exaggerate fuel savings and emission reductions

Exaggerates roadway expansion economic and environmental benefits

Use more accurate models

Ignores congestion equilibrium and the additional costs of induced travel

Exaggerates future congestion problems and roadway expansion benefits

Recognize congestion equilibrium, and account for generated traffic and induced travel costs

Funding and planning biases such as dedicated road funding and minimum parking requirements

Makes road and parking improvements easier to implement than  other types of transport improvements

Apply least-cost planning, so transport funds can be used for the most cost-effective solution. Reform minimum parking requirements.

Exaggerated roadway expansion economic productivity gains

Encourages roadway expansion over other transport improvements

Use critical analysis of congestion reduction economic benefits

Considers congestion costs and congestion reduction objectives in isolation

Favors roadway expansion over other congestion reduction strategies

Use a comprehensive evaluation framework that considers all objectives and impacts

This table summarizes common congestion costing biases, their impacts on planning decisions, and corrections for more comprehensive and objective congestion costs.


In recent years transportation professionals have started to develop better tools for evaluating overall accessibility, and multi-modal performance indicators, which allow more comprehensive evaluation of transportation problems and improvement strategies.

Conventional urban transport planning tends to consider traffic congestion the dominant planning problem, but more comprehensive and objective analysis indicates that traffic congestion is actually a moderate cost overall – larger than some but smaller than others – and roadway expansion is generally less effective and beneficial overall than other congestion reduction strategies.



Studies such as the Texas Transportation Institute's Urban Mobility Report conclude that traffic congestion is a major economic cost and roadway expansion can increase economic productivity but these are probably exaggerations. As Professor Eric Dumbaugh pointed out in a recent Atlantic Cities magazine article, Rethinking the Economics of Traffic Congestion, economic productivity tends to increase with congestion. This does not actually indicate that increasing congestion causes economic development, but it shows that traffic congestion is overall a minor cost that is usually offset by the economic efficiency gains of the increased accessibility provided by more compact and multi-modal development. For example, a business located in a city center has far more potential employees, partners and customers available within a half-hour trip, despite traffic congestion. 

Some congestion reduction strategies provide significant co-benefits. Improving alternative modes (particularly high quality public transit), improved roadway connectivity, pricing reforms and smart growth development polices reduce traffic congestion and help achieve other planning objectives. These strategies do not necessarily eliminate congestion, in fact, they may increase congestion intensity, but they can improve overall accessibility and reduce per capita congestion costs.

Despite frequent complaints about traffic congestion there appears to be insufficient willingness-to-pay for major urban roadway expansion, nor sufficient political support for congestion pricing, indicating that motorists do not really consider it a major problem. Financing highway expansion using other funding sources is economically inefficient and unfair because it forces people who don't use the added capacity to subsidize people who do. Excessive estimates of congestion costs and congestion reduction benefits tend to contradict transport equity objectives: they favor motorists over non-motorists and reduce the quality of transport options available to people who are physically, economically and socially disadvantaged.

This is not to suggest that driving is bad or that roadways should never be improved. However, when all impacts and options are considered, highway expansion is significantly more costly and less beneficial, and alternative congestion reduction strategies are often better, than indicated by conventional project economic evaluations. It is important that decision makers and the general public understand these issues when evaluating solutions to congestion problems.


For More Information 

Md Aftabuzzaman, Graham Currie and Majid Sarvi (2011), "Exploring The Underlying Dimensions Of Elements Affecting Traffic Congestion Relief Impact Of Transit," Cities, Vol. 28, Is. 1, February, Pages 36-44.

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.

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

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

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 (, July 2007, pp. 20-22.

Todd Litman (2011), "Smart Traffic Congestion Reductions: Comprehensive Analysis of Congestion Costs and Congestion Reduction Benefits," Traffic Infra Tech, Oct-Nov 2011, Vol. 2, No. 2, pp. 42-46 (

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

Nelson\Nygaard (2006), Traffic Reduction Strategies Study, for the City of Pasadena.

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