Advertisement

Transportation

, Volume 45, Issue 3, pp 945–969 | Cite as

Accuracy and bias of subjective travel time estimates

  • Einat Tenenboim
  • Yoram Shiftan
Article
  • 382 Downloads

Abstract

Travel time is the main factor affecting individuals’ travel-related decisions. Understanding the way people experience and estimate travel time is critical for a better insight regarding travel behavior and consequently for planning transport projects and guiding new policies. Whereas most travel-demand models employ objective time data, the use of subjective time data was proposed to improve model estimation. This study draws on fundamental as well as on recent psychological theories, investigating the discrepancy between subjective and objective travel times. According to one of these theories, the return trip effect, travelers tend to report shorter travel times for return trips compared to outbound trips. In a questionnaire, 174 respondents provided pre-trip time estimates. One group estimated travel times from home to local shopping areas, whereas a second group estimated times of the reverse trips. For comparison, objective times were obtained from Waze, a navigation application providing real-time information. Whereas 48% of time estimates were found accurate, over-estimates were 2.5 times more frequent than under-estimates. A return trip effect was found only for trips to/from poorly familiar shopping areas, highlighting the role of destination familiarity. Interestingly, respondents accurately estimated toll-trips but over-estimated non-toll trips. Presumably, merely thinking about paying the toll led individuals to form expectations of travel time savings in exchange. Linear and non-linear regression models for predicting subjective estimates revealed significant effects for trip frequency, trip direction, destination familiarity, toll-road and gender, amongst other variables. The results offer a fertile basis for incorporating subjective time in demand models.

Keywords

Travel time estimates Subjective time Return trip effect Toll-road Travel behavior Shopping trips 

References

  1. Adiv, A.: Commuter’s versus analyst’s perception of automobile travel cost. Transp. Res. Rec. 890, 18–24 (1982)Google Scholar
  2. Abou-Zeid, M., Ben-Akiva, M.: Well-being and activity-based models. Transportation 39(6), 1189–1207 (2012). doi: 10.1007/s11116-012-9387-8 CrossRefGoogle Scholar
  3. Ashiabor, S., Baik, H., Trani, A.: Logit models for forecasting nationwide intercity travel demand in the United States. Transp. Res. Rec. 2007(1), 1–12 (2007). doi: 10.3141/2007-01 CrossRefGoogle Scholar
  4. Bar-Gera, H., Toledo, G., & Feldman, I.: Level of service measures of the main roads in Israel—Final report (in Hebrew). Ministry of transport and road safety, Israel (2015)Google Scholar
  5. Ben-Elia, E., Erev, I., Shiftan, Y.: The combined effect of information and experience on drivers’ route-choice behavior. Transportation 35(2), 165–177 (2008). doi: 10.1007/s11116-007-9143-7 CrossRefGoogle Scholar
  6. Ben-Elia, E., Shiftan, Y.: Which road do I take? A learning-based model of route- choice behavior with real-time information. Transp. Res. Part A 44, 249–264 (2010)Google Scholar
  7. Block, R.A., Hancock, P.A., Zakay, D.: Sex differences in duration judgments: a meta-analytic review. Mem. Cognit. 28(8), 1333–1346 (2000). doi: 10.3758/BF03211834 CrossRefGoogle Scholar
  8. Buehler, R., Griffin, D., Ross, M.: Exploring the “planning fallacy”: why people underestimate their task completion times. J. Pers. Soc. Psychol. 67(3), 366–381 (1994). doi: 10.1037/0022-3514.67.3.366 CrossRefGoogle Scholar
  9. Burnett, P.: Time cognition and urban travel behavior. Geogr. Ann. 60(2), 107–115 (1978)CrossRefGoogle Scholar
  10. Campbell, J.F.: Selecting routes to minimize urban travel time. Transp. Res. Part B Methodol. 26(4), 261–274 (1992)CrossRefGoogle Scholar
  11. Cantillo, V., Heydecker, B., Ortu´zar, J.D.D.: A discrete choice model incorporating thresholds for perception in attribute values. Transp. Res. Part B 40, 807–825 (2006)CrossRefGoogle Scholar
  12. Carrion, C., Levinson, D.: Route choice dynamics after a link restoration. Transportation Research Board Annual Meeting. January, (2013)Google Scholar
  13. Cervero, R.: Built environment and mode choice: towards a normative framework. Transp. Res. Part D 7, 265–284 (2002)CrossRefGoogle Scholar
  14. Clark, J.E.: Modeling travelers’ perceptions of travel time. Transp. Res. Rec. 890, 7–11 (1982)Google Scholar
  15. Curl, A., Nelson, J.D., Anable, J.: Same question, different answer: a comparison of GIS-based journey time accessibility with self-reported measures from the National Travel Survey in England. Comput. Environ. Urban Syst. 49, 86–97 (2015). doi: 10.1016/j.compenvurbsys.2013.10.006 CrossRefGoogle Scholar
  16. De Maio, M.L., Vitetta, A., Watling, D.: Influence of experience on users’ behaviour: a day-to-day model for route choice updating. Proc. Soc. Behav. Sci. 87, 60–74 (2013). doi: 10.1016/j.sbspro.2013.10.594 CrossRefGoogle Scholar
  17. Devarasetty, P.C., Burris, M., Chao, H.: Comparing perceived and actual travel time savings on freeways with managed lanes. J. Transp. Inst. Transp. Eng. 6(1), 1–13 (2014)Google Scholar
  18. Dziekan, K., Kottenhoff, K.: Dynamic at-stop real-time information displays for public transport: effects on customers. Transp. Res. Part A Policy Pract. 41(6), 489–501 (2007). doi: 10.1016/j.tra.2006.11.006 CrossRefGoogle Scholar
  19. Forsyth, D.K., Burt, C.D.B.: Allocating time to future tasks: the effect of task segmentation on planning fallacy bias. Mem. Cognit. 36(4), 791–798 (2008). doi: 10.3758/MC.36.4.791 CrossRefGoogle Scholar
  20. Fox, J., Daly, A., Patruni, B., & Milthorpe, F.: Extending the Sydney Strategic Model to represent toll road and park-and-ride choices. In: Australasian Transport Research Forum 2011 Proceedings (2011)Google Scholar
  21. Fraisse, P.: Perception and estimation of time. Annu. Rev. Psychol. 35, 1–36 (1984)CrossRefGoogle Scholar
  22. Grisolía, J.M., Ortúzar, J.D.D.: Forecasting vs. observed outturn: studying choice in faster inter-island connections. Transp. Res. Part A 44(3), 159–168 (2010). doi: 10.1016/j.tra.2009.12.005 Google Scholar
  23. Grondin, S.: From physical time to the first and second moments of psychological time. Psychol. Bull. 127(1), 22–44 (2001). doi: 10.1037/0033-2909.127.1.22 CrossRefGoogle Scholar
  24. Grotenhuis, J.W., Wiegmans, B.W., Rietveld, P.: The desired quality of integrated multimodal travel information in public transport: customer needs for time and effort savings. Transp. Policy 14(1), 27–38 (2007). doi: 10.1016/j.tranpol.2006.07.001 CrossRefGoogle Scholar
  25. Gunn, H.: Valuation of travel time savings and loses. In: Hensher, D., Button, K. (eds.) Handbook of Transport Modelling. Elsevier, Oxford (2000)Google Scholar
  26. Halkjelsvik, T., Jørgensen, M.: From origami to software development: a review of studies on judgment-based predictions of performance time. Psychol. Bull. 138(2), 238–271 (2012). doi: 10.1037/a0025996 CrossRefGoogle Scholar
  27. Hammond, K.: Case-based planning: a framework for planning from experience. Cognit. Sci. 14, 385–443 (1990). doi: 10.1016/0364-0213(90)90018-R CrossRefGoogle Scholar
  28. Henley, D.H., Levin, I.P., Louviere, J.J., Meyer, R.J.: Changes in perceived travel cost and time for the work trip during a period of increasing gasoline costs. Transportation 10(1), 23–34 (1981). doi: 10.1007/BF00165615 CrossRefGoogle Scholar
  29. Hornik, J.: Subjective vs. objective time measures: a note on the perception of time in consumer behavior. J. Consum. Res. 11(1), 615 (1984). doi: 10.1086/208998 CrossRefGoogle Scholar
  30. Jiao, J., Moudon, A.V., Drewnowski, A.: Grocery shopping—How individuals and built environments influence choice of travel mode. Transp. Res. Rec. J. Transp. Res. Board 2230(−1), 85–95 (2011). doi: 10.3141/2230-10 CrossRefGoogle Scholar
  31. Kahneman, D., Tversky, A.: Intuitive prediction: biases and corrective procedures. TIMS Stud. Manag. Sci. 12, 313–327 (1979)Google Scholar
  32. Leavitt, H.J.: A note on some experimental findings about the meanings of price. J. Bus. 27(3), 205–210 (1954)CrossRefGoogle Scholar
  33. Mackie, P.J., Wardman, M., Fowkes, A.S., Whelan, G., Nellthorp, J., Bates, J.: Valuation of travel time savings in the UK. Summary report to the Department of Transport, London (2003)Google Scholar
  34. Mishalani, R.G., Mccord, M.M., Wirtz, J.: Passenger wait time perceptions at bus stops: empirical results and impact on evaluating real-time bus arrival information. J. Publ. Transp. 9(2), 89–106 (2006)CrossRefGoogle Scholar
  35. Morris, J.M., Dumble, P.L., Wigan, M.R.: Accessibility indicators for transport planning. Transp. Res. Part A General 13(2), 91–109 (1979). doi: 10.1016/0191-2607(79)90012-8 CrossRefGoogle Scholar
  36. Nakayama, S., Kitamura, R., Fujii, S.: Drivers’ learning and network behavior: dynamic analysis of the driver-network system as a complex system. Transp. Res. Rec. J. Transp. Res. Board 1676, 30–36 (1999). doi: 10.3141/1676-04 CrossRefGoogle Scholar
  37. O’Farrell, P., Markham, J.: Commuter perceptions of public transport work journeys. Environ. Plan. A 6(1), 79–100 (1974)CrossRefGoogle Scholar
  38. Pappas, E., Machemehl, R.: Predicting the incremental effects on transit ridership due to bus-on-shoulder operations 6. Retrieved from Research Report SWUTC/10/476660-00073-1 (2010)Google Scholar
  39. Peer, S., Knockaert, J., Koster, P., Verhoef, E.: Overreporting vs. overreacting: commuters’ perceptions of travel times. Tinbergen Institute Discussion Paper 13-123/VIII. http://doi.org/http://www.sciencedirect.com/science/journal/09658564 (2014)
  40. Prashker, J.N.: Direct analysis of the perceived importance of attributes of reliability of travel modes in urban travel. Transportation 8(8), 329–346 (1979)CrossRefGoogle Scholar
  41. Raghubir, P., Morwitz, V.G., Chakravarti, A.: Spatial categorization and time perception: why does it take less time to get home? J. Consum. Psychol. 21(2), 192–198 (2011). doi: 10.1016/j.jcps.2010.08.006 CrossRefGoogle Scholar
  42. Rao, A.R., Monroe, K.B.: The effect of price, brand name, and store name on buyers’ perceptions of product quality: an integrative review. J. Market. Res. XXVI, 351–357 (1989)CrossRefGoogle Scholar
  43. Rietveld, P., Zwart, B., van Wee, B., van den Hoorn, T.: On the relationship between travel time and travel distance of commuters. Ann. Reg. Sci. 33(3), 269–287 (1999). doi: 10.1007/s001680050105 CrossRefGoogle Scholar
  44. Roy, M.M., Christenfeld, N.J.S., McKenzie, C.R.M.: Underestimating the duration of future events: memory incorrectly used or memory bias? Psychol. Bull. 131(5), 738–756 (2005). doi: 10.1037/0033-2909.131.5.738 CrossRefGoogle Scholar
  45. Scholnick, E.K.: Plannning. In: Vilayanur, R. (ed.) Encyclopedia of Human Behavior, pp. 525–534. Academic Press Inc., Cambridge (1994)Google Scholar
  46. Shiftan, Y., Bekhor, S.: Investigating individual’s perceptions of auto travel cost. Int. J. Transp. Econ. XXIX(2), 151–166 (2002)Google Scholar
  47. Shiftan, Y., Shefer, D.: Evaluating the impact of transport projects: lessons for other disciplines. Eval. Progr. Plan. 32(4), 311–314 (2009). doi: 10.1016/j.evalprogplan.2009.08.003 CrossRefGoogle Scholar
  48. Stevens, S.S.: On the psychophysical law. Psychol. Rev. 64(3), 153–181 (1957). doi: 10.1126/science.3.71.712-a CrossRefGoogle Scholar
  49. Stevens, S.S., Galanter, E.H.: Ratio scales and category scales for a dozen perceptual continua. J. Exp. Psychol. 54(6), 377–411 (1957)CrossRefGoogle Scholar
  50. Thomas, K.E., Handley, S.J., Newstead, S.E.: The effects of prior experience on estimating the duration of simple tasks. Cahiers de Psychol. Cognit. 22(1), 83–100 (2004)Google Scholar
  51. Van Exel, N.J.A., Rietveld, P.: Perceptions of public transport travel time and their effect on choice-sets among car drivers. J. Transp. Land Use 2(3), 75–86 (2009). doi: 10.5198/jtlu.v2i3.15 Google Scholar
  52. Ven, N., Rijswijk, L., Roy, M.M.: The return trip effect: why the return trip often seems to take less time. Psychon. Bull. Rev. 18(5), 827–832 (2011). doi: 10.3758/s13423-011-0150-5 CrossRefGoogle Scholar
  53. Vreeswijk, J., Thomas, T., Van Berkum, E., Van Arem, B.: Perception bias in route choice. Transportation 7451(October), 1–14 (2014). doi: 10.1007/s11116-014-9552-3 Google Scholar
  54. Vreeswijk, J., Thomas, T., Van Berkum, E., Van Arem, B.: Drivers’ perception of route alternatives as indicator for the indifference band. Transp. Res. Board Travel Behav. 2, 10–17 (2013). doi: 10.3141/2383-02 CrossRefGoogle Scholar
  55. Weick, M., Guinote, A.: How long will it take? Power biases time predictions. J. Exp. Soc. Psychol. 46(4), 595–604 (2010). doi: 10.1016/j.jesp.2010.03.005 CrossRefGoogle Scholar
  56. Yáñez, M.F., Raveau, S., Ortúzar, J.D.D.: Inclusion of latent variables in mixed logit models: modelling and forecasting. Transp. Res. Part A 44(9), 744–753 (2010). doi: 10.1016/j.tra.2010.07.007 Google Scholar
  57. Yefe Nof: Haifa metropolitan area travel survey 2006, Report. Yefe Nof, Haifa, Israel (2007)Google Scholar
  58. Zakay, D.: The evasive art of subjective time measurement: some methodological dilemmas. In: Block, R.A. (ed.) Cognitive Models of Psychological Time, pp. 59–83. Hillsdale, New Jersey, Lawrence Erlbaum (1990)Google Scholar
  59. Zakay, D., Block, R.A.: Temporal cognition. Curr. Dir. Psychol. Sci. 6(1), 12–16 (1997). doi: 10.1111/1467-8721.ep11512604 CrossRefGoogle Scholar
  60. Zauberman, G., Kim, B.K., Malkoc, S.A., Bettman, J.R.: Discounting time and time discounting: Subjective time perception and intertemporal preferences. J. Mark. Res. 46(4), 543–556 (2009). doi: 10.1509/jmkr.46.4.543 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.TechnionHaifaIsrael

Personalised recommendations