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Quantifying errors in travel time and cost by latent variables

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  • Varela, Juan Manuel Lorenzo

    (CTS - Centre for Transport Studies Stockholm (KTH and VTI))

  • Börjesson, Maria

    (CTS - Centre for Transport Studies Stockholm (KTH and VTI))

  • Daly, Andrew

    (ITS, Leeds)

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; however, when measurement errors are modelled, the estimated time and cost parameters are robust to the 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 elasticity and values of travel time.

Suggested Citation

  • Varela, Juan Manuel Lorenzo & Börjesson, Maria & Daly, Andrew, 2018. "Quantifying errors in travel time and cost by latent variables," Working papers in Transport Economics 2018:3, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    • Handle: RePEc:hhs:ctswps:2018_003
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    References listed on IDEAS

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    1. West, Jens & Börjesson, Maria & Engelson, Leonid, 2016. "Accuracy of the Gothenburg congestion charges forecast," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 266-277.
    2. Guevara, C. Angelo, 2015. "Critical assessment of five methods to correct for endogeneity in discrete-choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 240-254.
    3. Börjesson, Maria & Fosgerau, Mogens, 2015. "Response time patterns in a stated choice experiment," Journal of choice modelling, Elsevier, vol. 14(C), pages 48-58.
    4. Börjesson, Maria & Kristoffersson, Ida, 2018. "The Swedish congestion charges: Ten years on," Transportation Research Part A: Policy and Practice, Elsevier, vol. 107(C), pages 35-51.
    5. Börjesson , Maria & Kristoffersson, Ida, 2017. "The Swedish congestion charges: ten years on: - and effects of increasing charging levels," Working papers in Transport Economics 2017:2, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    6. Díaz, Federico & Cantillo, Víctor & Arellana, Julian & Ortúzar, Juan de Dios, 2015. "Accounting for stochastic variables in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 222-237.
    7. Börjesson, Maria & Eliasson, Jonas, 2014. "Experiences from the Swedish Value of Time study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 144-158.
    8. Holmgren, Johan, 2007. "Meta-analysis of public transport demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 1021-1035, December.
    9. Peer, Stefanie & Knockaert, Jasper & Koster, Paul & Verhoef, Erik T., 2014. "Over-reporting vs. overreacting: Commuters’ perceptions of travel times," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 476-494.
    10. J. P. Royston, 1982. "The W Test for Normality," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 31(2), pages 176-180, June.
    11. Varotto, Silvia F. & Glerum, Aurélie & Stathopoulos, Amanda & Bierlaire, Michel & Longo, Giovanni, 2017. "Mitigating the impact of errors in travel time reporting on mode choice modelling," Journal of Transport Geography, Elsevier, vol. 62(C), pages 236-246.
    12. De Borger, Bruno & Fosgerau, Mogens, 2008. "The trade-off between money and travel time: A test of the theory of reference-dependent preferences," Journal of Urban Economics, Elsevier, vol. 64(1), pages 101-115, July.
    13. Vij, Akshay & Walker, Joan L., 2016. "How, when and why integrated choice and latent variable models are latently useful," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 192-217.
    14. Hess, Stephane & Daly, Andrew & Dekker, Thijs & Cabral, Manuel Ojeda & Batley, Richard, 2017. "A framework for capturing heterogeneity, heteroskedasticity, non-linearity, reference dependence and design artefacts in value of time research," Transportation Research Part B: Methodological, Elsevier, vol. 96(C), pages 126-149.
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    Citations

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    Cited by:

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    3. Thomas E. Guerrero & C. Angelo Guevara & Elisabetta Cherchi & Juan de Dios Ortúzar, 2021. "Addressing endogeneity in strategic urban mode choice models," Transportation, Springer, vol. 48(4), pages 2081-2102, August.
    4. Chakroborty, Partha & Pinjari, Abdul Rawoof & Meena, Jayant & Gandhi, Avinash, 2021. "A Psychophysical Ordered Response Model of Time Perception and Service Quality: Application to Level of Service Analysis at Toll Plazas," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 44-64.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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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    More about this item

    Keywords

    Hybrid choice models; Latent variables; Error quantification; Measurement error models; RP Value of Time; Self-reported indicators;
    All these keywords.

    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

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