Predicting Travel Time Variability for Cost-Benefit Analysis
AbstractUnreliable travel times cause substantial costs to travelers. Nevertheless, they are not taken into account in many cost-benefit-analyses (CBA), or only in very rough ways. This paper aims at providing simple rules on how variability can be predicted, based on travel time data from Dutch highways. The paper uses two different concepts of travel time variability. They differ in their assumptions on information availability to drivers. The first measure is based on the assumption that, for a given road link and given time of the day, the expected travel time is constant across all working days (rough information: RI). In the second case, expected travel times are assumed to reflect day-specific factors such as weather conditions or weekdays (fine information: FI). For both definitions of variability, we find that the mean travel time is a good predictor of variability. On average, longer delays are associated with higher variability. However, the derivative of travel time variability with respect to delays is decreasing in delays. It can be shown that this result relates to differences in the relative shares of observed traffic 'regimes' (free-flow, congested, hyper-congested) in the mean delay. For most CBAs, no information on the relative shares of the traffic regimes is available. A non-linear model based on mean travel times can be used as an approximation.
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Bibliographic InfoPaper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 10-071/3.
Date of creation: 19 Jul 2010
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Travel time variability; Cost-benefit analysis; Mean-variance approach;
Find related papers by JEL classification:
- R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General
- R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion
- R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning
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- Bergström, Anna & Krüger, Niclas, 2013.
"Modeling Passenger Train Delay Distributions - Evidence and Implications,"
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10, Department of Economics, Karlstad University.
- Bergström, Anna & Krüger, Niclas A., 2013. "Modeling passenger train delay distributions: evidence and implications," Working papers in Transport Economics 2013:3, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
- Paul Koster & Hans Koster, 2013. "Analysing Heterogeneity in the Value of Travel Time and Reliability: A Semiparametric Estimation Approach," ERSA conference papers ersa13p1032, European Regional Science Association.
- Paul Koster & Hans Koster, 2013. "Commuters' Preferences for Fast and Reliable Travel," Tinbergen Institute Discussion Papers 13-075/VIII, Tinbergen Institute, revised 24 Jun 2013.
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