Tuesday, January 1, 2013

Toward Comprehensive and Multi-Modal Performance Evaluation

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The U.S. Bureau of Transportation Statistic’s recently released National Transportation Statistics Report.... It is old-school, reflecting the assumption that our primary transportation problem is congestion delay. Of the nine tables in the Physical Performance section, four reflect air travel cancellations and delays, one reflects air travel baggage losses, and four are based on the Texas Transportation Institute’s congestion cost estimates.

What’s wrong with the BTS’s current approach? First, assumes that there are only two important modes of personal travel (commercial air and motor vehicle), that our main goal is to travel faster, and our main problem is that we are too often delayed. There is no consideration of other modes, goals or performance indicators such as availability, comfort and affordability. All congestion cost estimates are based on the Texas Transportation Institute’s calculations, without mentioning their weaknesses and biases, as discussed in a previous column, Toward More Comprehensive Understanding of Traffic Congestion.

Congestion is actually a modest cost overall. For example, the TTI’s most recent Urban Mobility Report estimates that in 2010 U.S. congestion caused 4.8 billion person-hours of delay and 1.9 billion gallons of additional fuel consumption, valued at $101 billion, this only averages 15.5 hours, 6.2 gallons and $327 per capita. The TTI methodology uses an unrealistic freeflow baseline speed (it assumes that all roads should always have level-of-service A; most economists argue that level-of-service C or D is actually more optimal under urban-peak conditions) and high travel time unit costs (they assume that congestion delay is worth $16.30/hr, although in practice, few motorists are willing to pay that much for incremental time savings), which bias their estimates upward. Applying more realistic analysis would reduce estimated congestion cost to approximately $110 per capita. This compares with about $4,000 in vehicle costs, $1,500 in crash damages, more than $1,000 in vehicle parking costs, $400 in roadway costs and $357 in environmental costs per capita.

Automobile dependency and sprawl tend to increase transport costs far more than traffic congestion, as discussed in Joe Cortright's report, Driven Apart: How Sprawl is Lengthening Our Commutes and Why Misleading Mobility Measures are Making Things Worse. For example, the TTI indicates that in 2010 Washington D.C. automobile commuters experience 74 average annual hours of congestion delay, but since only 43% of commuter in that region drive, this averages just 32 hours per commuter overall. In contrast, Houston automobile commuters experience 57 annual hours of delay, but since that region has a 88% auto mode share this averages 50 hours per commuter overall, much higher than Washington D.C. Cities with high quality public transit, such as New York, Boston and San Francisco, rate much better when congestion is measured per commuter rather than automobile commuter due to their low auto mode shares.

The TTI estimates that in the largest U.S. cities congestion causes 34 annual hours of delay and 16.5 gallons of additional fuel consumed per commuter. In contrast, according to analysis described in my report, Smart Congestion Relief, residents of automobile-dependent regions, who average more than 30 daily miles of vehicle travel, spend an estimated 104 additional hours and 183 additional gallons of fuel compared with more compact, multi-modal regions where residents average fewer than 20 daily vehicle-miles. This suggests that policies which stimulate sprawl impose more than three times the total cost as traffic congestion.

Fortunately, more comprehensive and multi-modal evaluation tools are now available for evaluating transportation system performance. For example, the Florida Department of Transportation’s new report, Expanded Transportation Performance Measures to Supplement Level of Service (LOS) for Growth Management and Transportation Impact Analysis critically evaluates current transport system performance indicators such as Roadway Level of Service (LOS) and identifies and evaluates more multi-dimensional and multi-modal transport system performance indicators. The report summarizes various examples from Florida cities that apply multi-modal transport system performance evaluation, and provides guidance for selecting and applying them in a particular situation.

Another approach is the National Association of Regional Council’s Livability Literature Review: A Synthesis Of Current Practice recently published by the U.S. Department of Transportation. It examines ways to define and evaluate livability and sustainability, and how they relate to various current planning concepts including smart growth, complete streets, lifelong communities, safe routes to schools, context sensitive solutions/design, new urbanism, transit-oriented development and placemaking. It provides a foundation for applying more comprehensive community planning, including more accessible development and multi-modal transport planning.

The New York City Department of Transportation’s very attractive report, Measuring the Street: New Metrics for 21st Century Streets discusses ways to evaluate urban street performance. It describes various urban street planning goals, strategies (specific ways to achieve goals) and metrics (specific ways to measure progress toward goals)
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I have a few specific concerns about these documents. The Florida and NYC reports refer to sustainability, livability and accessibility without clearly defining the terms. Some goals and objectives (strategies) overlap. For example, some indicator sets tend to overweigh congestion impacts by including congestion reduction, improved freight transport and improved travel reliability objectives, while others overweigh energy consumption impacts by including energy conservation, local emission reductions, global emission reductions, and environmental quality. It is important to recognize how such double-counting can bias evaluation results.

Another concern is the poor way these indicators address social objectives such as affordability, basic mobility for non-drivers, and improved public health. These are all implied as goals, but I don’t think they are as well articulated or measured as economic objectives (congestion reduction, improved freight transport, agency cost efficiency, etc.) and environmental objectives (energy conservation, emission reductions, habitat preservation, etc.). This area needs more research and guidance.
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Todd Litman's Blog at Planetizen http://www.planetizen.com/blog/2394
November 27, 2012

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