考虑高速公路差异化收费的货车出行行为研究

孔德学, 敖谷昌, 徐威威, 张惠玲

交通运输研究 ›› 2023, Vol. 9 ›› Issue (4) : 84-92.

交通运输研究 ›› 2023, Vol. 9 ›› Issue (4) : 84-92. DOI: 10.16503/j.cnki.2095-9931.2023.04.008
理论与方法

考虑高速公路差异化收费的货车出行行为研究

作者信息 +

Truck Travel Behavior Considering Expressway Differentiated Charge

  • KONG Dexue 1, 2 ,  
  • AO Guchang 3 ,  
  • XU Weiwei 3 ,  
  • ZHANG Huiling 3
Author information +
文章历史 +

摘要

为探究高速公路差异化收费对货车驾驶员出行行为的影响,选取付费方式、运输时间紧急性、选择重视因素和情境选择行为4个因素作为外显变量,在提高高峰期收费费率的场景下,构建货车驾驶员群体细分的潜在类别模型。基于重庆市584份高速公路货车出行行为问卷调查数据,对其进行类别划分,并对比分析了各类货车驾驶员的出行选择偏好。研究表明:①货车驾驶员群体可划分为灵活型、无奈型和忠诚型3类,且货物类型和运输成本对驾驶员的类别划分有显著影响;②随着高速公路月通行次数的减少,忠诚型选择重视里程的概率呈线性增长趋势,且会显著影响灵活型选择改变出行路径的概率;③当运输成本提高时,灵活型出行选择会更加看重通行费用的高低,而忠诚型则注重高速公路良好的行车体验;④无奈型迫于货物的运输时间要求,提高收费场景下的行为特征差异较小。因此,针对不同类型货车驾驶员群体应制定差异化的收费定价策略,以避免高速公路货运用户流失。

Abstract

To investigate the impact of expressway differentiated charging on the travel behavior of truck drivers, the payment mode, transportation time urgency, choice factor, and situational choice behavior were selected as explicit variables. A latent class model of truck driver groups was established under the scenario of increasing charges during peak periods. Based on 584 questionnaire survey responses on expressway truck travel behavior in Chongqing, the drivers were classified and the travel preferences of various truck drivers were compared and analyzed. The results show that: ①the truck drivers can be classified into three categories: flexible drivers, helpless drivers, and loyal drivers, and cargo type and transportation cost have a significant impact on the classification; ②as the monthly usage frequency of expressway decreases, the probability of loyal drivers choosing to value mileage increases linearly, and it also will significantly affect the probability of flexible drivers changing their travel routes; ③when transportation costs increase, flexible drivers tend to place greater emphasis on the toll, while loyal drivers focus on having a good driving experience on the expressway; ④behavioral characteristics of helpless drivers under the increased charges situation have slight differences due to the transportation time requirements of cargo. Therefore, differentiated charging strategies should be formulated for different categories of truck drivers to avoid the loss of expressway freight users.

关键词

交通工程 / 高速公路 / 潜在类别模型 / 货车驾驶员 / 差异化收费

Key words

traffic engineering / expressway / latent class model / truck driver / differentiated charge

引用本文

导出引用
孔德学, 敖谷昌, 徐威威, . 考虑高速公路差异化收费的货车出行行为研究[J]. 交通运输研究. 2023, 9(4): 84-92 https://doi.org/10.16503/j.cnki.2095-9931.2023.04.008
KONG Dexue, AO Guchang, XU Weiwei, et al. Truck Travel Behavior Considering Expressway Differentiated Charge[J]. Transport Research. 2023, 9(4): 84-92 https://doi.org/10.16503/j.cnki.2095-9931.2023.04.008
中图分类号: U491.122   

参考文献

[1]
交通运输部,国家发展改革委,财政部. 关于印发《全面推广高速公路差异化收费实施方案》的通知(交公路函〔2021〕228号)[EB/OL].(2021-06-02)[2023-04-21]. http://www.gov.cn/zhengce/zhengceku/2021-06/15/content_5617919.htm.
[2]
陈文强, 顾玉磊, 汪勇杰, 等. 基于博弈决策的道路通行费最优定价模型研究[J]. 公路交通科技, 2021, 38(5):152-158.
[3]
王林, 冯国帅, 吴双, 等. 汉宜高速公路分路段差异化收费费率研究[J]. 公路交通科技, 2022, 39(1):183-190.
[4]
FENG T, ARENTZE T, TIMMERMANS H. Capturing preference heterogeneity of truck drivers′ route choice behavior with context effects using a latent class model[J]. European Journal of Transport and Infrastructure Research, 2013, 13(4): 259-273.
[5]
GOMEZ J, VASSALLO J M. Has heavy vehicle tolling in Europe been effective in reducing road freight transport and promoting modal shift?[J]. Transportation, 2020, 47(2): 865-892.
[6]
闫晟煜, 詹振宇, 李艳红, 等. 外省籍货车对省域ETC差异化收费的影响分析[J]. 深圳大学学报(理工版), 2022, 39(5):608-614.
[7]
HECKMAN J J, SINGER B. Econometric duration analysis[J]. Journal of Econometrics, 1984, 24(1-2): 63-132.
[8]
乔珂, 赵鹏, 文佳星. 基于潜在类别模型的高铁旅客市场细分[J]. 交通运输系统工程与信息, 2017, 17(2):28-34.
[9]
戢晓峰, 李德林. 基于潜在类别的公路旅客群体细分模型[J]. 公路交通科技, 2019, 36(10):152-158.
[10]
ROMAN C, ARENCIBIA A I, FEO-VALERO M. A latent class model with attribute cut-offs to analyze modal choice for freight transport[J]. Transportation Research Part A: Policy and Practice, 2017, 102: 212-227.
[11]
RAFIQ R, MCNALLY M G. Heterogeneity in activity-travel patterns of public transit users: An application of latent class analysis[J]. Transportation Research Part A: Policy and Practice, 2021, 152: 1-18.
[12]
刘建荣, 刘志伟. 基于出行者潜在类别的公交出行行为研究[J]. 华南理工大学学报(自然科学版), 2019, 47(6):119-126.
[13]
BONADIO F T, TOMPSETT C. Who benefits from community mental health care? Using latent profile analysis to identify differential treatment outcomes for youth[J]. Journal of Youth and Adolescence, 2018, 47(11): 2320-2336.
[14]
邱皓政. 潜在类别模型的原理与技术[M]. 北京: 教育科学出版社, 2008:20-33.
[15]
ELDEEB G, MOHAMED M. Quantifying preference heterogeneity in transit service desired quality using a latent class choice model[J]. Transportation Research Part A: Policy and Practice, 2020, 139: 119-133.
[16]
FEMATT V L, GRIMM R P, NYLUND-GIBSON K, et al. Identifying transfer student subgroups by academic and social adjustment: A latent class analysis[J]. Community College Journal of Research and Practice, 2021, 45(3): 167-183.
[17]
SWANSON S A, LINDENBERG K, BAUER S, et al. A Monte Carlo investigation of factors influencing latent class analysis: An application to eating disorder research[J]. International Journal of Eating Disorders, 2012, 45(5): 677-684.

基金

重庆市自然科学基金项目(cstc2019jcyj-msxmX0786)
重庆市研究生导师团队建设项目(JDDSTD2018007)

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