There has been an on-going debate on the ITE website concerning whether our profession should shift from evaluating transport system performance based on roadway level-of-service toward more comprehensive and multi-modal indicators. Its an interesting and important debate. I just posted what I consider a good summary of the arguments in favor of reform. Im not sure whether access to the website is limited to ITE members, so Ill copy my posting below. Sorry, its a little long and it responds to a previous posting which I didnt include here, but I think you can guess what it said. Please let me know what you think. It will be interesting to see if anybody accepts my challenge. ============================================= From: Mr. Todd A. Litman To: All Member Forum Posted: Sep 26, 2014 4:13 PM Subject: RE: Has SB 743 Diminished the value of PTOE in California? Thank you for your comments, Richard. I agree that transportation policy debates often suffer from vagueness and confirmation bias: people define the issue to suit their perspective and select evidence that supports their position. So, let me try to focus this discussion and see what objective evidence exists concerning these issues. The key to a good debate is a well-defined problem statement. Here what I propose: That transportation professionals shift from evaluating urban transportation system performance based primarily on traffic congestion indicators (such as roadway level-of-service, the Travel Time Index, and similar indices) to using more comprehensive (considering impacts other than traffic congestion) and other modes (besides automobile travel). You are welcome to propose an alternative, but let me work with it for now. Let me identify some justifications for this shift, with credible evidence. 1. Changing travel demands. In most developed countries, automobile travel demand is peaking, while demand for alternative modes is growing, due to various demographic and economic trends including vehicle saturation, aging population, rising fuel prices, increasing urbanization, changing consumer preference, and growing concerns about affordability, health and environmental concerns. This is not to suggest that everybody wants to give up automobile travel completely, but there is good research indicating at the margin (compared with their current travel patterns) many people want to drive less and rely more on walking, cycling, public transit and telework, and live in more accessible and multi-modal communities, provided that those alternatives are convenient, comfortable, integrated and affordable. For evidence, see: Todd Litman (2013), The Future Isnt What It Used To Be: Changing Trends And Their Implications For Transport Planning, Victoria Transport Policy Institute (vtpi.org); at vtpi.org/future.pdf; originally published as Changing Travel Demand: Implications for Transport Planning, ITE Journal, Vol. 76, No. 9, (ite.org), September 2006, pp. 27-33. NAR (2013), National Community Preference Survey, National Association of Realtors (realtor.org); at realtor.org/sites/default/files/reports/2013/2013-community-preference-analysis-slides.pdf. Steven E. Polzin, Xuehao Chu and Nancy McGuckin (2011), Exploring Changing Travel Trends, presented at Using National Household Travel Survey Data for Transportation Decision Making: A Workshop, Transportation Research Board (trb.org); at onlinepubs.trb.org/onlinepubs/conferences/2011/NHTS1/Polzin2.pdf. Michael Sivak (2013), Has Motorization in the U.S. Peaked?, University of Michigan, Transportation Research Institute (umich.edu/~umtriswt); at deepblue.lib.umich.edu/bitstream/handle/2027.42/98098/102947.pdf. Clark Williams-Derry (2011), Dude, Where Are My Cars? Sightline Institute (sightline.org); at daily.sightline.org/blog_series/dude-where-are-my-cars. To the degree that this is true, transportation professionals have a responsibility to change our planning and evaluation practices to better reflect transport system user demands. More comprehensive travel data, multi-modal LOS, complete streets policies, multi-modal funding reforms, transportation demand management, smart growth development policies (particularly parking policy reforms) are practical ways that we do this. 2. Better congestion solutions. Roadway LOS only measures congestion intensity, the degree that vehicle travel speeds decline during peak periods. It is incomplete because it fails to reflect congestion exposure, that is, the amount that residents must drive during peak periods, and therefore residents total congestion costs. As I mentioned in a previous posting, compact, multi-modal cities tend to have more intense congestion (they rate worse measured by roadway LOS or the Travel Time Index) but residents experience less per capita congestion costs because they rely more on alternative modes and their trips are shorter (see evidence in, Smart Congestion Relief at vtpi.org ). This has important implications for evaluating potential congestion reduction strategies. If evaluated using roadway LOS, bus-lanes, more connected roadways, and smart growth strategies look bad, but if evaluated using multi-modal LOS or per capita congestion costs (which recognize travel time savings to bus passengers and shorter trip distances), they look relatively effective because they reduce congestion. For this reason, I believe it is wrong to conclude that investing in transit, applying complete streets policies or encouraging infill development necessarily increases congestion. For example, Kuzmyak (2012) found that residents of urban neighborhoods with good travel options, connected streets and more nearby services drive a third fewer daily miles and experience less congestion delays than otherwise similar residents in automobile-dependent communities. Similarly, Ewing and Hamidi (2014) indicate that sprawl significantly increases the total time and money residents spend in transport: each 10% increase in their Sprawl Index increases average journey-to-work drive time by 0.5%. For evidence see: 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 (sciencedirect/science/journal/02642751), February, Pages 36-44. Michael L. Anderson (2013), Subways, Strikes, and Slowdowns: The Impacts of Public Transit on Traffic Congestion, Working Paper No. 18757, National Bureau of Economic Research (nber.org); at nber.org/papers/w18757. Reid Ewing and Shima Hamidi (2014), Measuring Urban Sprawl and Validating Sprawl Measures, Metropolitan Research Center at the University of Utah for the National Cancer Institute, the Brookings Institution and Smart Growth America (smartgrowthamerica.org); at arch.utah.edu/cgi-bin/wordpress-metroresearch. J. Richard Kuzmyak (2012), Land Use and Traffic Congestion, Report 618, Arizona Department of Transportation (azdot.gov); at azdot.gov/TPD/ATRC/publications/project_reports/PDF/AZ618.pdf. Todd Litman (2012), Smart Congestion Relief: Comprehensive Analysis Of Traffic Congestion Costs and Congestion Reduction Benefits, paper P12-5310, Transportation Research Board Annual Meeting (trb.org); at vtpi.org/cong_relief.pdf. Todd Litman (2014), Congestion Costing Critique: Critical Evaluation of the Urban Mobility Report, VTPI (vtpi.org); at vtpi.org/UMR_critique.pdf. 3. Automobile-oriented planning is inherently inefficient and unfair. An efficient and equitable transportation system must be diverse, with good walking, cycling and public transit, so that users can choose the best mode for each trip, including walking and cycling for neighborhood trips, transit for travel on congested urban corridors, and automobiles for other types of trips. In any community, 20-40% of residents cannot or should not drive due to lack of drivers license, disability, low income, inebriation, or because they want exercise; failing to accommodate these trips deprives non-drivers of independent mobility and results in economically-excessive motor vehicle travel - vehicle miles that would be avoided if there were better travel options. Evaluating transportation system performance based only on roadway LOS biases planning to favor automobile-oriented improvements, such as wider roads with higher design speeds, to the detriment of other modes, creating a self-fulfilling prophecy of increased automoible dependency and reduced travel options. There is good evidence that communities which improve walking, cycling and public transit service experience shifts to those modes, indicating latent demand. See: FHWA (2014), Nonmotorized Transportation Pilot Program: Continued Progress in Developing Walking and Bicycling Networks - May 2014 Report, John A Volpe National Transportation Systems Center, USDOT (fhwa.dot.gov); at fhwa.dot.gov/environment/bicycle_pedestrian/ntpp/2014_report/hep14035.pdf. Jason Cao and Jessica Schoner (2013), Transportation Impact of Transitways: A Case Study of Hiawatha Light Rail Transit in Minneapolis, Report 7, Transitway Impacts Research Program, University of Minnesota (cts.umn.edu); at cts.umn.edu/Publications/ResearchReports/reportdetail.html?id=2266. Reid Ewing, Guang Tian and Allison Spain (2014), Effect of Light-Rail Transit on Traffic in a Travel Corridor, National Institute for Transportation and Communities (otrec.us); at tinyurl/qgvpdkf. 4. Multi-modal transportation increases safety. One unfortunate outcome of excessively automobile-dependent transport planning is high traffic fatality rates. In fact, the U.S. has the highest per capita traffic death rate among OECD countries, which can be explained by high per capita vehicle mileage. Many of the strategies often proposed to reduce traffic congestion, such as wider roads with higher design speeds, tend to increase traffic risks (see Marshall and Garrick 2011). In contrast, communities that improve transport options tend to have significantly lower traffic death rates. Safety is, of course, an important transport planning and engineering goal. Evaluating transportation system performance based on roadway LOS ignores the crash risks that result from roadway expansions, or described in a more positive way, more comprehensive and multi-modal evaluation can help identify the congestion reduction strategies that also help improve traffic safety and increase community health. For information see: Eric Dumbaugh (2005), Safe Streets, Livable Streets, Journal of the American Planning Association (planning.org), Vol. 71, No. 3, pp. 283-300; at naturewithin.info/Roadside/TransSafety_JAPA.pdf. Frank Haight (1994), Problems in Estimating Comparative Costs of Safety and Mobility, Journal of Transport Economics and Policy, January, p. 7-30; at bath.ac.uk/e-journals/jtep/pdf/Volume_XXV111_No_1_7-30.pdf. Todd Litman (2009), Transportation Policy and Injury Control, Injury Prevention, Vol. 15, Issue 6 (injuryprevention.bmj/content/15/6/362.full); at vtpi.org/tpic.pdf. Todd Litman and Steven Fitzroy (2005), Safe Travels: Evaluating Mobility Management Traffic Safety Impacts, VTPI (vtpi.org); at vtpi.org/safetrav.pdf. Wesley E. Marshall and Norman W. Garrick (2011), Evidence on Why Bike-Friendly Cities Are Safer for All Road Users, Environmental Practice, Vol. 13/1, March; at files.meetup/1468133/Evidence%20on%20Why%20Bike-Friendly.pdf. In summary I have offered four good reasons that our profession should shift from the current emphasis on roadway LOS to more comprehensive and multi-modal transport system performance evaluation. To support these, I provided good, peer-reviewed research indicating that more comprehensive and multi-modal evaluation can better serve transport system users. I welcome alternative perspectives: are there good reasons to continue with current practices? Show us evidence. ------------------------------------------- Todd Litman Director Victoria Transport Policy Inst Victoria BC [email protected] -------------------------------------------
Posted on: Fri, 26 Sep 2014 20:20:37 +0000
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