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Travel time unreliability on freeways: Why measures based on variance tell only half the story

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  • van Lint, J.W.C.
  • van Zuylen, Henk J.
  • Tu, H.

Abstract

In recent years, travel time reliability has become one of the key performance indicators of transportation networks and corridors around the globe. Travel time reliability indicators are mostly related to properties of the day-to-day travel time distribution on for example a freeway corridor. On the basis of empirical data a number of key characteristics of this day-to-day distribution can be identified. Most importantly, this distribution is not only very wide but also heavily skewed. The (economic) consequences of this skew are substantial. For example, it is shown that in some peak periods the 5% most "unlucky drivers" incur almost five times as much delay as the 50% most fortunate travelers. We argue this implies first of all that (besides the variance of travel times) skew must be considered an important contributing factor to travel time unreliability. Secondly, it suggests that most of currently used unreliability measures (which are predominantly based on travel time variance), should be used and interpreted with some reservations, since they only account for a part of the costs (that is, delays) of unreliability. This is further substantiated by a comparison on the basis of empirical data from a densely used freeway in the Netherlands between a new travel time reliability measure based on both width and skew, and a number of travel time reliability measures commonly used in practice. The analysis clearly illustrates the inconsistency between all measures, both old and new. In illustration, in cases where the commonly used misery index dubs a particular departure period very unreliable, another common measure (buffer time) considers these periods relatively reliable. Although without objective and quantitative criteria (e.g. economic or societal costs) a choice for any of these measures in road network performance analyses will remain subject to debate, this article provides empirically underpinned arguments to prefer measures incorporating the skew of the travel time distribution.

Suggested Citation

  • van Lint, J.W.C. & van Zuylen, Henk J. & Tu, H., 2008. "Travel time unreliability on freeways: Why measures based on variance tell only half the story," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(1), pages 258-277, January.
  • Handle: RePEc:eee:transa:v:42:y:2008:i:1:p:258-277
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    References listed on IDEAS

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    1. Brownstone, David & Small, Kenneth A., 2005. "Valuing time and reliability: assessing the evidence from road pricing demonstrations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(4), pages 279-293, May.
    2. Yang, Hai & Bell, Michael G. H. & Meng, Qiang, 2000. "Modeling the capacity and level of service of urban transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(4), pages 255-275, May.
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    1. repec:eee:transa:v:103:y:2017:i:c:p:250-263 is not listed on IDEAS
    2. Chen, Anthony & Zhou, Zhong & Lam, William H.K., 2011. "Modeling stochastic perception error in the mean-excess traffic equilibrium model," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1619-1640.
    3. Oliveira, Eduardo Leal de & Portugal, Licínio da Silva & Porto Junior, Walter, 2016. "Indicators of reliability and vulnerability: Similarities and differences in ranking links of a complex road system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 195-208.
    4. Matthias Sweet & Mengke Chen, 2011. "Does regional travel time unreliability influence mode choice?," Transportation, Springer, vol. 38(4), pages 625-642, July.
    5. Raux, Charles & Souche, Stéphanie & Pons, Damien, 2012. "The efficiency of congestion charging: Some lessons from cost–benefit analyses," Research in Transportation Economics, Elsevier, vol. 36(1), pages 85-92.
    6. Xiangdong Xu & Anthony Chen & Lin Cheng, 2013. "Assessing the effects of stochastic perception error under travel time variability," Transportation, Springer, vol. 40(3), pages 525-548, May.
    7. Durán-Hormazábal, Elsa & Tirachini, Alejandro, 2016. "Estimation of travel time variability for cars, buses, metro and door-to-door public transport trips in Santiago, Chile," Research in Transportation Economics, Elsevier, vol. 59(C), pages 26-39.
    8. Koster, Paul & Kroes, Eric & Verhoef, Erik, 2011. "Travel time variability and airport accessibility," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1545-1559.
    9. Soriguera, Francesc, 2014. "On the value of highway travel time information systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 70(C), pages 294-310.
    10. Xu, Xiangdong & Chen, Anthony & Cheng, Lin & Yang, Chao, 2017. "A link-based mean-excess traffic equilibrium model under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 53-75.
    11. Srinivasan, Karthik K. & Prakash, A.A. & Seshadri, Ravi, 2014. "Finding most reliable paths on networks with correlated and shifted log–normal travel times," Transportation Research Part B: Methodological, Elsevier, vol. 66(C), pages 110-128.
    12. Tu, Huizhao & Li, Hao & van Lint, Hans & van Zuylen, Henk, 2012. "Modeling travel time reliability of freeways using risk assessment techniques," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1528-1540.
    13. repec:eee:transb:v:107:y:2018:i:c:p:212-228 is not listed on IDEAS
    14. Chen, Anthony & Zhou, Zhong, 2010. "The [alpha]-reliable mean-excess traffic equilibrium model with stochastic travel times," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 493-513, May.
    15. repec:eee:reensy:v:152:y:2016:i:c:p:151-165 is not listed on IDEAS
    16. Engelson, Leonid & Fosgerau, Mogens, 2011. "Additive measures of travel time variability," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1560-1571.
    17. Xu, Xiangdong & Chen, Anthony & Cheng, Lin & Lo, Hong K., 2014. "Modeling distribution tail in network performance assessment: A mean-excess total travel time risk measure and analytical estimation method," Transportation Research Part B: Methodological, Elsevier, vol. 66(C), pages 32-49.
    18. Zhang, Wei & Jenelius, Erik & Ma, Xiaoliang, 2017. "Freight transport platoon coordination and departure time scheduling under travel time uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 98(C), pages 1-23.
    19. Li, Zheng & Hensher, David A. & Rose, John M., 2013. "Accommodating perceptual conditioning in the valuation of expected travel time savings for cars and public transport," Research in Transportation Economics, Elsevier, vol. 39(1), pages 270-276.

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