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Accuracy and bias of subjective travel time estimates

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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.

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Notes

  1. Some of the studies reviewed above regarding the deviation from objective time were conducted in a time before technical advances allowed for the gathering of more reliable objective time data (e.g., using GPS trackers, license plate detectors). In Henley et al. (1981), for instance, research assistants replicated respondents’ car trips, timing them the following working day. Similarly, Clark (1982) used objective times gathered by research assistants who replicated respondents’ trips twice and then averaged their timings. Rietveld et al. (1999), on the other hand, employed route planners and various proxies.

  2. The Carmel Tunnels (also known as Route 23) cross Haifa from east to west.

  3. One of the anonymous reviewers of this paper has raised a reasonable concern that the students in our sample may have estimated travel time differently compared to the other respondents, given their lower socio-economic level. Yet, we found that 85% of these students indicated that they regularly use a private car. Indeed, a repetition of the main analyses, separately for students and other adults, found no significant differences between their travel time estimates.

  4. In general, the trips investigated in this study were short urban trips, highly typical in Haifa, which is not a large city (approximately 280,000 residents). Therefore, although the boundary of ±2 min is somewhat arbitrary, it is a reasonable boundary for denoting accurate versus inaccurate estimation as mean trip duration was 11.85 min (standard deviation was 5.00 min). Denoting an accurate estimation as one that is within 10% of objective time has shown highly similar results to those presented here.

  5. Given that the heterogeneity model was performed by the maximum likelihood method, R2 data is unavailable.

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  1. Technion, Haifa, Israel

    Einat Tenenboim & Yoram Shiftan

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  1. Einat Tenenboim
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Tenenboim, E., Shiftan, Y. Accuracy and bias of subjective travel time estimates. Transportation 45, 945–969 (2018). https://doi.org/10.1007/s11116-016-9757-8

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