Volume 40 Issue 2
Apr.  2022
Turn off MathJax
Article Contents
LIU Zhiwei, SONG Zhengyun, DENG Wei, BAO Danwen. Impacts of Autonomous Vehicles on Mode Choice Behavior in the Context of Short- and Medium- Distance Intercity Travel[J]. Journal of Transport Information and Safety, 2022, 40(2): 91-97. doi: 10.3963/j.jssn.1674-4861.2022.02.011
Citation: LIU Zhiwei, SONG Zhengyun, DENG Wei, BAO Danwen. Impacts of Autonomous Vehicles on Mode Choice Behavior in the Context of Short- and Medium- Distance Intercity Travel[J]. Journal of Transport Information and Safety, 2022, 40(2): 91-97. doi: 10.3963/j.jssn.1674-4861.2022.02.011

Impacts of Autonomous Vehicles on Mode Choice Behavior in the Context of Short- and Medium- Distance Intercity Travel

doi: 10.3963/j.jssn.1674-4861.2022.02.011
  • Received Date: 2021-11-18
    Available Online: 2022-05-18
  • This paper studies the impacts of autonomous vehicles on mode choice behavior in the context of shortand medium-distance intercity travel. Based on the theory of planned behavior, a structure equation model isdeveloped, through which latent psychological variables of individuals towards autonomous vehicles are developed, including perceived behavioral control, subjective norms, attitudes, and behavioral intentions. These latent psychological variables are then integrated into a random parameter Logit model to develop a hybrid choice model. The City of Wuhan is used as a case to carry out an empirical study, and the study results show that: in the utility function, the coefficients of three variables, including in-vehicle time, access and exit and waiting time, and travel cost, are not fixed but follow a normal distribution with a mean of -0.014, -0.008, and -0.010 and with the standard deviations of 0.014, 0.021, and 0.017, respectively. When the perceived behavior control and attitude of individuals towards autonomous vehicles increased by 1 unit, the probability of using autonomous vehicles to travel increased by 64.3% and 77.9%, respectively. For every 1% decrease in the travel cost and in-vehicle time of autonomous vehicles, the probability of choosing autonomous vehicles and intercity shuttles increases by 0.403% and 0.467%, respectively. This paper studies the impacts of autonomous vehicles on mode choice behavior in the context of shortand medium-distance intercity travel. Based on the theory of planned behavior, a structure equation model isdeveloped, through which latent psychological variables of individuals towards autonomous vehicles are developed, including perceived behavioral control, subjective norms, attitudes, and behavioral intentions. These latent psychological variables are then integrated into a random parameter Logit model to develop a hybrid choice model. The City of Wuhan is used as a case to carry out an empirical study, and the study results show that: in the utility function, the coefficients of three variables, including in-vehicle time, access and exit and waiting time, and travel cost, are not fixed but follow a normal distribution with a mean of -0.014, -0.008, and -0.010 and with the standard deviations of 0.014, 0.021, and 0.017, respectively. When the perceived behavior control and attitude of individuals towards autonomous vehicles increased by 1 unit, the probability of using autonomous vehicles to travel increased by 64.3% and 77.9%, respectively. For every 1% decrease in the travel cost and in-vehicle time of autonomous vehicles, the probability of choosing autonomous vehicles and intercity shuttles increases by 0.403% and 0.467%, respectively. Study results show that travelers have heterogeneous preferences toward the attributes of the transport service offered by autonomous vehicles, such as in-vehicle time, access/egress and waiting time, and travel costs. It is also found that perceived behavioral control and behavioral attitudes have significantly positive impacts on traveler's choice on autonomous vehicles. Therefore, reducing travel costs and travel time of autonomous vehicles can increase the attractiveness of autonomous vehicles.

     

  • loading
  • [1]
    FAGNANT D J, KOCKELMAN K. Preparing a nation for autonomous vehicles: Opportunities, barriers and policy recommendations[J]. Transportation Research Part A: Policy and Practice, 2015, 77(7): 167-181.
    [2]
    PERRINE K A, KOCKELMAN K M, HUANG Y. Anticipating long-distance travel shifts due to self-driving vehicles[J]. Journal of Transport Geography, 2020, 82(1): 102547.
    [3]
    KRÖGER L, KUHNIMHOF T, TROMMER S. Does context matter? A comparative study modelling autonomous vehicle impact on travel behaviour for Germany and the USA[J]. Transportation Research Part A: Policy and Practice, 2019, 122(4): 146-161.
    [4]
    CHEN T D, KOCKELMAN K M, HANNA J P. Operations of a shared, autonomous, electric vehicle fleet: Implications of vehicle & charging infrastructure decisions[J]. Transportation Research Part A: Policy and Practice, 2016, 94(12): 243-254.
    [5]
    BOESCH P M, CIARI F, AXHAUSEN K W. Autonomous vehicle fleet sizes required to serve different levels of demand[J]. Transportation Research Record, 2016, 2542(1): 111-119. doi: 10.3141/2542-13
    [6]
    LAMONDIA J J, FAGNANT D J, QU H, et al. Shifts in long-distance travel mode due to automated vehicles statewide mode-shift simulation experiment and travel survey analysis[J]. Transportation Research Record Journal of the Transportation Research Board, 2016, 2566(1): 1-11. doi: 10.3141/2566-01
    [7]
    刘志伟, 刘建荣, 邓卫. 无人驾驶汽车对出行方式选择行为的影响[J]. 西南交通大学学报, 2021, 56(6): 1161-1168. https://www.cnki.com.cn/Article/CJFDTOTAL-XNJT202106004.htm

    LIU Z W, LIU J R, DENG W. Impact of autonomous vehicle on travel mode choice behavior[J]. Journal of Southwest Jiaotong University, 2021, 56(6): 1161-1168. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XNJT202106004.htm
    [8]
    姚荣涵, 杨澜, 王仲. 考虑潜变量的自动驾驶汽车租赁行为[J]. 西南交通大学学报, 2021, 56(6): 1153-1160. https://www.cnki.com.cn/Article/CJFDTOTAL-XNJT202106003.htm

    YAO R H, YANG L, WANG Z. Leasing behavior for autonomous vehicles considering latent variables[J]. Journal of Southwest Jiaotong University, 2021, 56(6): 1153-1160. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XNJT202106003.htm
    [9]
    范琪, 王炜, 杨洋, 等. 家庭收入差异对出行方式选择的影响分析[J]. 交通信息与安全, 2019, 37(6): 111-120. https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS201906015.htm

    FAN Q, WANG W, YANG Y, et al. Effects of household income differences on travel mode choice[J]. Journal of Transport Information and Safety, 2019, 37(6): 111-120. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS201906015.htm
    [10]
    BEN-AKIVA M, MCFADDEN D, TRAIN K, et al. Hybrid choice models: Progress and challenges[J]. Marketing Letters, 2002, 13(3): 163-175. doi: 10.1023/A:1020254301302
    [11]
    SANBONMATSU D M, STRAYER D L, YU Z, et al. Cognitive underpinnings of beliefs and confidence in beliefs about fully automated vehicles[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2018, 55(2): 114-122.
    [12]
    KAUR K, RAMPERSAD G. Trust in driverless cars: Investigating key factors influencing the adoption of driverless cars[J]. Journal of Engineering and Technology Management, 2018, 48(4): 87-96.
    [13]
    LIU P, YANG R, XU Z. Public acceptance of fully automated driving: Effects of social trust and risk/benefit perceptions[J]. Risk Analysis, 2019, 39(2): 326-341.
    [14]
    JING P, HUANG H, RAN B, et al. Exploring the factors affecting mode choice intention of autonomous vehicle based on an extended theory of planned behavior: A case study in China[J]. Sustainability, 2019, 11(4): 1155. doi: 10.3390/su11041155
    [15]
    KRUEGER R, RASHIDI T H, ROSE J M. Preferences for shared autonomous vehicles[J]. Transportation Research Part C: Emerging Technologies, 2016, 69(8): 343-355.
    [16]
    刘建荣, 刘志伟, 任倩. 考虑出行者异质性的高铁站到达方式选择[J]. 华南理工大学学报(自然科学版), 2019, 47(9): 47-52. https://www.cnki.com.cn/Article/CJFDTOTAL-HNLG201909008.htm

    LIU J R, LIU Z W, REN Q. Incorporating heterogeneity into travelers' high-speed rail station arrival mode choice[J]. Journal of South China University of Technology, 2019, 47(9): 47-52. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-HNLG201909008.htm
    [17]
    GKARTZONIKAS C, GKRITZA K. What have we learned? A review of stated preference and choice studies on autonomous vehicles[J]. Transportation Research Part C: Emerging Technologies, 2019, 98(1): 323-337.
    [18]
    王灿, 王德, 朱玮, 等. 离散选择模型研究进展[J]. 地理科学进展, 2015, 34(10): 1275-1287. https://www.cnki.com.cn/Article/CJFDTOTAL-DLKJ201510008.htm

    WANG C, WANG D, ZHU W, et al. Research progress of discrete choice models[J]. Progress in Geography, 2015, 34(10): 1275-1287. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DLKJ201510008.htm
    [19]
    AJZEN I. The theory of planned behavior[J]. Journal of Leisure Research, 1991, 50(2): 179-211.
    [20]
    BIERNACKI C, GOVAERT G. Choosing models in model-based clustering and discriminant analysis[J]. Journal of Statistical Computation and Simulation, 1999, 64(1): 49-71.
    [21]
    YÁÑEZ M F, RAVEAU S, ORTÚZAR J D D. Inclusion of latent variables in mixed logit models: Modelling and forecasting[J]. Transportation Research Part A: Policy and Practice, 2010, 44(9): 744-753.
    [22]
    WANG J, WANG X. Structural equation modeling: Applications using Mplus[M]. New York: John Wiley & Sons, 2019.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(1)  / Tables(7)

    Article Metrics

    Article views (846) PDF downloads(50) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return