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Quantifying errors in travel time and cost by latent variables

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  • Varela, Juan Manuel Lorenzo
  • Börjesson, Maria
  • Daly, Andrew

Abstract

Travel time and travel cost are key variables for explaining travel behaviour and deriving the value of time. However, a general problem in transport modelling is that these variables are subject to measurement errors in transport network models. In this paper we show how to assess the magnitude of the measurement errors in travel time and travel cost by latent variables, in a large-scale travel demand model. The case study for Stockholm commuters shows that assuming multiplicative measurement errors for travel time and cost result in a better fit than additive ones, and that parameter estimates of the choice model are impacted by some of the key modelling assumptions. Moreover, our results suggest that measurement errors in our dataset are larger for the travel cost than for the travel time, and that measurement errors are larger in self-reported travel time than software-calculated travel time for car-driver and car-passenger, and of similar magnitude for public transport. Among self-reported travel times, car-passenger has the largest errors, followed by car-driver and public transport, and for the software-calculated times, public transport exhibits larger errors than car. These errors, if not corrected, lead to biases in measures derived from the models, such as elasticities and values of travel time.

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  • Varela, Juan Manuel Lorenzo & Börjesson, Maria & Daly, Andrew, 2018. "Quantifying errors in travel time and cost by latent variables," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 520-541.
    • Handle: RePEc:eee:transb:v:117:y:2018:i:pa:p:520-541
    DOI: 10.1016/j.trb.2018.09.010
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    6. Carlos Carrion & David Levinson, 2019. "Overestimation and underestimation of travel time on commute trips: GPS vs. self- reporting," Working Papers 2019-05, University of Minnesota: Nexus Research Group.
    7. Aaditya, Bh. & Rahul, T.M., 2021. "Psychological impacts of COVID-19 pandemic on the mode choice behaviour: A hybrid choice modelling approach," Transport Policy, Elsevier, vol. 108(C), pages 47-58.
    8. Stephane Hess & Andrew Daly & Maria Börjesson, 2020. "A critical appraisal of the use of simple time-money trade-offs for appraisal value of travel time measures," Transportation, Springer, vol. 47(3), pages 1541-1570, June.
    9. Peer, Stefanie & Börjesson, Maria, 2018. "Temporal framing of stated preference experiments: does it affect valuations?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 319-333.
    10. Batarce, Marco, 2024. "Estimation of discrete choice models with error in variables: An application to revealed preference data with aggregate service level variables," Transportation Research Part B: Methodological, Elsevier, vol. 185(C).
    11. Andersson, Angelica & Engelson, Leonid & Börjesson, Maria & Daly, Andrew & Kristoffersson, Ida, 2022. "Long-distance mode choice model estimation using mobile phone network data," Journal of choice modelling, Elsevier, vol. 42(C).
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