IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this article

Integrating the mean–variance and scheduling approaches to allow for schedule delay and trip time variability under uncertainty

Listed author(s):
  • Li, Hao
  • Tu, Huizhao
  • Hensher, David A.

Uncertainty of travel times and the impact on travel choice behavior has been recognized as an increasingly important research direction in the past decade. This paper proposes an extension to the popular scheduling approach to model traveler’s departure time choice behavior under uncertainty, with the main focus on a richer representation of uncertainty. This more general approach incorporates a separate term to reflect the risk aversion associated with uncertainty. Recognizing the correlation between expected schedule delay and travel time variability, the schedule delay components in the generalized approach are defined in terms of expected travel time, which differs from the scheduling approach. This approach is developed based on the analytical investigation of the relationship between the expected schedule delay and the mean and standard deviation of travel time. An analytical equivalence was found between the scheduling approach and the general approach given a departure time t. To investigate the empirical performance of the generalized approach, two state preference (SP) data sets are used; one from China with a symmetric travel time distribution and the other from Australia with an asymmetric distribution. Both studies show empirical evidence of an equivalence in respect of statistical fit between the generalized and the scheduling approaches, as found from analytical investigations. The Chinese study gives support in the generalized model to including both the mean–variance and the scheduling effects; whereas the Australian study finds only the mean–variance specification has statistical merit. Despite the different travel contexts, it is noteworthy in both empirical settings, that the parameter estimate for arriving earlier than the preferred arrival time (PAT) in the generalized model is positive. This suggests that commuters tend to prefer to arrive earlier in order to guarantee he/she will not be late. This paper contributes to a better understanding of performances of different reliability measures and their relationships. The practical value of the various unreliability measures is provided showing that these indicators are easy to obtain for inclusion in project appraisal.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.sciencedirect.com/science/article/pii/S0965856416303834
Download Restriction: Full text for ScienceDirect subscribers only

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

Volume (Year): 89 (2016)
Issue (Month): C ()
Pages: 151-163

as
in new window

Handle: RePEc:eee:transa:v:89:y:2016:i:c:p:151-163
DOI: 10.1016/j.tra.2016.05.014
Contact details of provider: Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description

Order Information: Postal: http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
Web: https://shop.elsevier.com/order?id=547&ref=547_01_ooc_1&version=01

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as
in new window


  1. Fosgerau, Mogens, 2010. "On the relation between the mean and variance of delay in dynamic queues with random capacity and demand," Journal of Economic Dynamics and Control, Elsevier, vol. 34(4), pages 598-603, April.
  2. Rose, John M. & Bliemer, Michiel C.J. & Hensher, David A. & Collins, Andrew T., 2008. "Designing efficient stated choice experiments in the presence of reference alternatives," Transportation Research Part B: Methodological, Elsevier, vol. 42(4), pages 395-406, May.
  3. Li, Zheng & Hensher, David A. & Rose, John M., 2010. "Willingness to pay for travel time reliability in passenger transport: A review and some new empirical evidence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(3), pages 384-403, May.
  4. de Palma, André & Picard, Nathalie, 2005. "Route choice decision under travel time uncertainty," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(4), pages 295-324, May.
  5. Noland, Robert B. & Small, Kenneth A. & Koskenoja, Pia Maria & Chu, Xuehao, 1998. "Simulating travel reliability," Regional Science and Urban Economics, Elsevier, vol. 28(5), pages 535-564, September.
  6. Batley, Richard, 2007. "Marginal valuations of travel time and scheduling, and the reliability premium," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(4), pages 387-408, July.
  7. Hensher,David A. & Rose,John M. & Greene,William H., 2015. "Applied Choice Analysis," Cambridge Books, Cambridge University Press, number 9781107465923, August.
  8. David A. Hensher & Zheng Li, 2012. "Valuing Travel Time Variability within a Rank-Dependent Utility Framework and an Investigation of Unobserved Taste Heterogeneity," Journal of Transport Economics and Policy, University of Bath, vol. 46(2), pages 293-312, May.
  9. Hollander, Yaron, 2006. "Direct versus indirect models for the effects of unreliability," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(9), pages 699-711, November.
  10. de Jong, Gerard C. & Bliemer, Michiel C.J., 2015. "On including travel time reliability of road traffic in appraisal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 73(C), pages 80-95.
  11. Erel Avineri & Joseph Prashker, 2006. "The Impact of Travel Time Information on Travelers’ Learning under Uncertainty," Transportation, Springer, vol. 33(4), pages 393-408, 07.
  12. Hensher, David A. & Greene, William H. & Li, Zheng, 2011. "Embedding risk attitude and decision weights in non-linear logit to accommodate time variability in the value of expected travel time savings," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 954-972, August.
  13. 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.
  14. Fosgerau, Mogens & Karlström, Anders, 2010. "The value of reliability," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 38-49, January.
  15. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
  16. Small, Kenneth A, 1982. "The Scheduling of Consumer Activities: Work Trips," American Economic Review, American Economic Association, vol. 72(3), pages 467-479, June.
  17. Robert B. Noland & John W. Polak, 2002. "Travel time variability: A review of theoretical and empirical issues," Transport Reviews, Taylor & Francis Journals, vol. 22(1), pages 39-54, January.
  18. Dirk van Amelsfort & Piet Bovy & Michiel Bliemer & Barry Ubbels, 2008. "Travellers’ Responses to Road Pricing: Value of Time, Schedule Delay and Unreliability," Chapters,in: Pricing in Road Transport, chapter 4 Edward Elgar Publishing.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:89:y:2016:i:c:p:151-163. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.