Impact of shared autonomous vehicles on choice of subway station connection methods

被引：0

作者：

Liu Z.-W. ^{[1
]}

Song Z.-Y. ^{[1
]}

Liu J.-R. ^{[2
]}

机构：

[1] School of Civil Engineering and Architecture, Wuhan Polytechnic University, Wuhan

[2] School of Civil Engineering and Transportation, South China University of Technology, Guangzhou

来源：

Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2023年 / 53卷 / 12期

关键词：

autonomous vehicles; engineering of communication and transportation system; last-mile travel; random parameter Logit model (RPLM); theory of planned behavior;

D O I：

10.13229/j.cnki.jdxbgxb.20220912

中图分类号：

学科分类号：

摘要：

In order to explore the heterogeneity of preferences of travel choice and the potential of shared autonomous vehicles to solve the last-mile connection problem of train trips,the last-mile travel mode choice of travelers based on the theory of planned behavior was analyzed. First,a latent variable model was established to obtain travelers' attitudes,subjective norms,perceived behavior control,and behavioral intentions toward autonomous vehicles. Secondly,latent psychological variables into the random parameter Logit model and conduct an empirical analysis was incorporated to study factors of the behavior of the last mile of train trip. Finally,an elasticity analysis was conducted to study the impact of travel time on the travel mode choice. The research results show that the random coefficient Logit model has higher fitness than the traditional multinomial Logit model. Travelers' preferences for travel time are heterogeneous. The travel time coefficient is not a fixed value but follows a normal distribution with a mean of - 0.153 and a standard deviation of 0.520. Travelers' attitudes and perceived behavioral control towards autonomous vehicles have a significant impact on travel behavior. The probability of choosingshared autonomous vehicles increases by 0.799% with every 1% reduction in the travel time of autonomous vehicles;The probability of choosing shared autonomous vehicles increases by 1.155 % with every 1% increase in the travel time of shared bicycles. © 2023 Editorial Board of Jilin University. All rights reserved.

引用

页码：3424 / 3431

页数：7

共 22 条

[11]

Yap M D, Correia G, van Arem B., Valuation of travel attributes for using automated vehicles as egress transport of multimodal train trips, Transportation Research Procedia, 10, pp. 462-471, (2015)

[12]

Moorthy A, de Kleine R, Keoleian G, Et al., Shared autonomous vehicles as a sustainable solution to the last mile problem: a case study of ANN Arbor-Detroit area, SAE International Journal of Passenger Cars-Electronic and Electrical Systems, 10, 1, pp. 328-336, (2017)

[13]

Wang Can, Wang De, Zhu Wei, Et al., Research progress of discrete choice models, Progress in Geography, 34, 10, pp. 1275-1287, (2015)

[14]

Liu Z, Deng W, Chen Y., Influence of autonomous vehicles on short and medium distance mode choice for intercity travel

[15]

Bhat C R., Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences, Transportation Research Part B: Methodological, 37, 9, pp. 837-855, (2003)

[16]

Jmp A, Proust M., Design of Experiments Guide, (2010)

[17]

Wang J, Wang X., Structural Equation Modeling: Applications using Mplus, (2019)

[18]

Zhou H, Norman R, Xia J C, Et al., Analysing travel mode and airline choice using latent class modelling: a case study in western Australia, Transportation Research Part A: Policy and Practice, 137, 7, pp. 187-205, (2020)

[19]

Olfindo R, Transport accessibility, residential satisfaction, and moving intention in a context of limited travel mode choice, Transportation Research Part A: Policy and Practice, 145, 3, pp. 153-166, (2021)

[20]

Haboucha C J, Ishaq R, Shiftan Y., User preferences regarding autonomous vehicles, Transportation Research Part C: Emerging Technologies, 78, 5, pp. 37-49, (2017)

← 1 2 3 →