It is time to find better solutions to congestion problems. This requires more comprehensive evaluation in order to identify win-win solutions: the congestion reduction strategies that help achieve other planning objectives.
Most people consider traffic congestion wasteful and frustrating, but there are contentious debates concerning which solution is best: whether to expand roadways, improve rail or bus transit services, apply road pricing, or implement transportation demand management strategies. These debates is often simplistic, based on incomplete analysis. I hope that in 2014 we can apply smarter evaluation of potential congestion reduction strategies.
This is important because congestion evaluation affects many planning decisions, from how transportation funds are spent and roads are designed, to where development occurs. Despite this importance, many people involved in these decisions have little understanding of how best to evaluate congestion. Most communities continue to use biased and incomplete analysis methods that exaggerate congestion costs and roadway expansion benefits, and undervalue other solutions which are often best overall.
My article, Smarter Congestion Relief In Asian Cities: Win-Win Solutions To Urban Transport Problems, just published in the United Nation’s Transport and Communications Bulletin for Asia and the Pacific, discusses better ways to evaluate congestion and select congestion reduction strategies. The principles apply to any urban areas, not just Asian cities.
Conventional congestion indicators, such as roadway level-of-service, the travel time index, the Gridlock Index and their variations, reflect congestion intensity, the amount that traffic speeds decline during peak periods. Such information is useful for making short-term decisions, such as how to travel across town during rush hour, but is unsuited for strategic planning decisions that affect transport options (the quality of travel modes) or development patterns. Comprehensive evaluation measures total congestion costs, taking into account exposure (the amount that people must drive under urban-peak conditions). A more compact, multi-modal community may have relatively intense congestion but lower congestion costs than more sprawled, automobile-dependent community due to better alternatives to driving, well connected roadway networks, and shorter travel distances which minimize peak period driving. Described differently, congestion evaluation is affected by whether analysis measures mobility (travel speed) or accessibility (the time and financial costs required to reach desired services and activities).
- Use efficiency-optimizing baseline speeds (the speed below which congestion delays are calculated), such as level-of-service C. Efficiency-optimizing speeds maximize roadway capacity and fuel economy, and so are more realistic than freeflow speeds.
- Measure delays to all travelers, not just to motorists. Account for the travel time savings to transit passengers from bus priority systems, and for delays to pedestrians and cyclists caused by wider roads and increased traffic (called the barrier effect).
- Use accurate fuel efficiency functions. Vehicle fuel efficiency generally peaks at about 50 miles per hour, so reducing moderate congestion (for example, from LOS C to freeflow) often increases fuel consumption and emissions, particularly if it induces additional vehicle travel.
- Recognize that congestion tends to maintain self-limiting equilibrium: it increases to the point that delays limit further peak-period vehicle travel. As a result, congestion costs seldom increase as much as predicted by extrapolating past trends.
- Account for generated and induced vehicle travel (additional vehicle travel resulting from reduced congestion) when evaluating roadway expansions. This tends to reduce predicted roadway expansion benefits.
- Account for increased crash costs that result if congestion reductions result in high traffic speeds.
- Account for co-benefits when evaluating potential congestion reduction strategies, such as reduced parking costs, consumer savings and affordability, improved accessibility for non-drivers, increased safety and health, reduced pollution emissions, and support for strategic land use objectives.
- Evaluate impacts on specific corridors. Although alternative modes, such as public transit, may serve a small portion of total regional travel, their mode share is often much higher on major urban corridors, so they can provide significant congestion reductions.
Comprehensive, multi-modal analysis is important because planning decisions often involve trade-offs between various accessibility factors. For example, expanding roadways may improve traffic speeds, but reduces walking and cycling access (and therefore transit access since most transit trips involve walking links), and often leads to more dispersed development which reduces land use accessibility, while other congestion reduction strategies, such as public transit improvements, tend to improve transport options and encourage more accessible land use development. Comprehensive evaluation considers all these impacts.
Conventional analysis methods are often biased in ways that exaggerate congestion costs and roadway expansion benefits, and undervalue other congestion solutions. For example, the Urban Mobility Report’s widely-cited estimate that U.S. congestion costs total $121 billion annually is based on assumptions that violate recommended practices, including freeflow baseline speeds, higher travel time values than the USDOT recommends, and questionable assumptions about the impacts of congestion on fuel consumption, pollution emission and safety impacts. As a result, it represents an upper-bound cost estimate; more realistic assumptions result in much lower estimates of congestion costs and road expansion benefits.
The old planning paradigm assumes that traffic congestion is the most important urban transport problem and roadway expansion is the preferred solution. But congestion is actually a moderate cost overall, smaller than vehicle costs, accident costs, parking costs, and environmental damages. It would therefore be harmful overall to reduce traffic congestion in ways that increase these other costs, while a congestion reduction strategy is worth far more if it reduces other costs.
Chronic traffic congestion can be considered a symptom of more fundamental transport system problems, including inadequate transport options, underpricing, and sprawled development. Under such conditions, unpriced roadway expansions usually provide only short-term congestion relief and generally exacerbate transport problems. Roadway expansions also tend to be unfair to people who rely on walking, cycling and public transport, and therefore do not directly benefit and are harmed by increased vehicle traffic.
A better approach overall is a combination of improvements to alternative modes, transport pricing reforms, smart growth development policies, and other transportation demand management programs. Though individually these may not be considered the most effective congestion reduction strategies, their impacts tend to be synergistic (total impacts are greater than the sum of their individual impacts) and increase over time. As a result, these win-win strategies are often the most efficient and equitable way to reduce congestion, when all impacts are considered.
This is a timely issue. Current trends are increasing the importance of more comprehensive and multi-modal analysis in order to identify truly optimal solutions to transport problems. It is important that decision makers and the general public understand these issues when choosing congestion reduction strategies.
For More Information
Matthew Barth and Kanok Boriboonsomin (2009), “Traffic Congestion And Greenhouse Gases,”Access 35, University of California Transportation Center, pp. 2-9; at.
Joe Cortright (2010), Driven Apart: How Sprawl is Lengthening Our Commutes and Why Misleading Mobility Measures are Making Things Worse, CEOs for Cities.
Joe Cortright (2011), UMR Remains a Flawed and Misleading Guide to Urban Transportation, CEOs for Cities.
Michael Grant, et al. (2011), Congestion Management Process: A Guidebook, Federal Highway Administration.
Susan Grant-Muller and James Laird (2007), International Literature Review of the Costs of Road Traffic Congestion, Scottish Executive.
Jonathan Levine, Joe Grengs, Qingyun Shen and Qing Shen (2012), “Does Accessibility Require Density or Speed?”Journal of the American Planning Association, Vol. 78, No. 2, pp. 157-172.
Todd Litman (2012), Smart Congestion Relief: Comprehensive Analysis Of Traffic Congestion Costs and Congestion Reduction Benefits, Victoria Transport Policy Institute.
Todd Litman (2013), “Smarter Congestion Relief In Asian Cities: Win-Win Solutions To Urban Transport Problems,” Transport and Communications Bulletin for Asia and the Pacific: Theme Combatting Congestion, No. 82.
Todd Litman (2014), Congestion Costing Critique: Critical Evaluation of the ‘Urban Mobility Report’ Victoria Transport Policy Institue.
Amudapuram Mohan Rao and Kalaga Ramachandra Rao (2012), “Measuring Urban Traffic Congestion – A Review,”International Journal for Traffic and Transport Engineering, Vol. 2, No. 4, pp. 286-305.
TC (2006), The Cost Of Urban Congestion In Canada, Transport Canada.
Ian Wallis and David Lupton (2013), The Costs Of Congestion Reappraised, Report 489, New Zealand Transport Agency.
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