A Joint Route Choice Model for Capturing Preferences of Electric and Conventional Car Drivers

    Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review

    Abstract

    Battery electric vehicles (BEVs) play an important role in the increasing effort by governments to curtail the pollution from the transport sector and reduce the dependence from fossil fuels of internal combustion engine vehicles (ICEVs). Although traffic assignment models exist for BEVs, the assumption of shortest path search on the basis of time constrained by energy consumption does not have any empirical basis. The current paper presents a revealed preference study of route choice behaviour of drivers participating in a large-scale experiment with BEVs. Observed routes while driving BEVs and ICEVs were map matched and a joint route choice model was specified and estimated to reveal whether the type of vehicle is related to the preference structure. Significantly different parameters for trip length for BEV and ICEV are obtained in the model estimation, indicating a higher sensitivity to the distance travelled when driving BEVs. Moreover, the level of charge of the battery and the travel in the morning peak make drivers less sensitive to distance. The findings from this study suggest the need to revise the cost functions in the literature about traffic assignment with BEVs as these functions should not consider similar parameters regardless of the vehicle type, but instead a higher sensitivity to distance that reflects heterogeneity in driving behaviour with BEVs.
    Original languageEnglish
    Publication date2018
    Publication statusPublished - 2018
    Event Transportation research Board: 97th Annual Meeting - Washington DC, United States
    Duration: 7 Jan 201811 Jan 2018
    Conference number: 97

    Conference

    Conference Transportation research Board: 97th Annual Meeting
    Number97
    CountryUnited States
    CityWashington DC
    Period07/01/201811/01/2018

    Cite this

    Jensen, A. F., Rasmussen, T. K., & Prato, C. G. (2018). A Joint Route Choice Model for Capturing Preferences of Electric and Conventional Car Drivers. Abstract from Transportation research Board: 97th Annual Meeting, Washington DC, United States.
    Jensen, Anders Fjendbo ; Rasmussen, Thomas Kjær ; Prato, Carlo G. / A Joint Route Choice Model for Capturing Preferences of Electric and Conventional Car Drivers. Abstract from Transportation research Board: 97th Annual Meeting, Washington DC, United States.
    @conference{e88649a8f320401a8fec8a697eba82e5,
    title = "A Joint Route Choice Model for Capturing Preferences of Electric and Conventional Car Drivers",
    abstract = "Battery electric vehicles (BEVs) play an important role in the increasing effort by governments to curtail the pollution from the transport sector and reduce the dependence from fossil fuels of internal combustion engine vehicles (ICEVs). Although traffic assignment models exist for BEVs, the assumption of shortest path search on the basis of time constrained by energy consumption does not have any empirical basis. The current paper presents a revealed preference study of route choice behaviour of drivers participating in a large-scale experiment with BEVs. Observed routes while driving BEVs and ICEVs were map matched and a joint route choice model was specified and estimated to reveal whether the type of vehicle is related to the preference structure. Significantly different parameters for trip length for BEV and ICEV are obtained in the model estimation, indicating a higher sensitivity to the distance travelled when driving BEVs. Moreover, the level of charge of the battery and the travel in the morning peak make drivers less sensitive to distance. The findings from this study suggest the need to revise the cost functions in the literature about traffic assignment with BEVs as these functions should not consider similar parameters regardless of the vehicle type, but instead a higher sensitivity to distance that reflects heterogeneity in driving behaviour with BEVs.",
    author = "Jensen, {Anders Fjendbo} and Rasmussen, {Thomas Kj{\ae}r} and Prato, {Carlo G.}",
    year = "2018",
    language = "English",
    note = "Transportation research Board: 97th Annual Meeting ; Conference date: 07-01-2018 Through 11-01-2018",

    }

    Jensen, AF, Rasmussen, TK & Prato, CG 2018, 'A Joint Route Choice Model for Capturing Preferences of Electric and Conventional Car Drivers', Transportation research Board: 97th Annual Meeting, Washington DC, United States, 07/01/2018 - 11/01/2018.

    A Joint Route Choice Model for Capturing Preferences of Electric and Conventional Car Drivers. / Jensen, Anders Fjendbo; Rasmussen, Thomas Kjær; Prato, Carlo G.

    2018. Abstract from Transportation research Board: 97th Annual Meeting, Washington DC, United States.

    Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review

    TY - ABST

    T1 - A Joint Route Choice Model for Capturing Preferences of Electric and Conventional Car Drivers

    AU - Jensen, Anders Fjendbo

    AU - Rasmussen, Thomas Kjær

    AU - Prato, Carlo G.

    PY - 2018

    Y1 - 2018

    N2 - Battery electric vehicles (BEVs) play an important role in the increasing effort by governments to curtail the pollution from the transport sector and reduce the dependence from fossil fuels of internal combustion engine vehicles (ICEVs). Although traffic assignment models exist for BEVs, the assumption of shortest path search on the basis of time constrained by energy consumption does not have any empirical basis. The current paper presents a revealed preference study of route choice behaviour of drivers participating in a large-scale experiment with BEVs. Observed routes while driving BEVs and ICEVs were map matched and a joint route choice model was specified and estimated to reveal whether the type of vehicle is related to the preference structure. Significantly different parameters for trip length for BEV and ICEV are obtained in the model estimation, indicating a higher sensitivity to the distance travelled when driving BEVs. Moreover, the level of charge of the battery and the travel in the morning peak make drivers less sensitive to distance. The findings from this study suggest the need to revise the cost functions in the literature about traffic assignment with BEVs as these functions should not consider similar parameters regardless of the vehicle type, but instead a higher sensitivity to distance that reflects heterogeneity in driving behaviour with BEVs.

    AB - Battery electric vehicles (BEVs) play an important role in the increasing effort by governments to curtail the pollution from the transport sector and reduce the dependence from fossil fuels of internal combustion engine vehicles (ICEVs). Although traffic assignment models exist for BEVs, the assumption of shortest path search on the basis of time constrained by energy consumption does not have any empirical basis. The current paper presents a revealed preference study of route choice behaviour of drivers participating in a large-scale experiment with BEVs. Observed routes while driving BEVs and ICEVs were map matched and a joint route choice model was specified and estimated to reveal whether the type of vehicle is related to the preference structure. Significantly different parameters for trip length for BEV and ICEV are obtained in the model estimation, indicating a higher sensitivity to the distance travelled when driving BEVs. Moreover, the level of charge of the battery and the travel in the morning peak make drivers less sensitive to distance. The findings from this study suggest the need to revise the cost functions in the literature about traffic assignment with BEVs as these functions should not consider similar parameters regardless of the vehicle type, but instead a higher sensitivity to distance that reflects heterogeneity in driving behaviour with BEVs.

    M3 - Conference abstract for conference

    ER -

    Jensen AF, Rasmussen TK, Prato CG. A Joint Route Choice Model for Capturing Preferences of Electric and Conventional Car Drivers. 2018. Abstract from Transportation research Board: 97th Annual Meeting, Washington DC, United States.