IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2020i1p25-d466618.html
   My bibliography  Save this article

The Influence of Individual Differences on Diverging Behavior at the Weaving Sections of an Urban Expressway

Author

Listed:
  • Zhanji Zheng

    (Jiangsu Key Laboratory of Urban ITS, Jiangsu Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing 21189, Jiangsu, China)

  • Qiaojun Xiang

    (Jiangsu Key Laboratory of Urban ITS, Jiangsu Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing 21189, Jiangsu, China)

  • Xin Gu

    (Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China)

  • Yongfeng Ma

    (Jiangsu Key Laboratory of Urban ITS, Jiangsu Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing 21189, Jiangsu, China)

  • Kangkang Zheng

    (Jiangsu Key Laboratory of Urban ITS, Jiangsu Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing 21189, Jiangsu, China)

Abstract

Urban expressway weaving sections suffer from a high crash risk in urban transportation systems. Studying driving behavior is an important approach to solve safety and efficiency issues at expressway weaving sections. This study aimed to investigate the influence of drivers’ individual differences on diverging behavior at expressway weaving sections. First, a k-means cluster analysis of 650 questionnaires was performed, to classify drivers into three categories: aggressive, conservative and normal. Then, the driving behavior of 45 drivers from the three categories was recorded in a driving simulator and analyzed by an analysis of variance. The results show that different types of drivers have different driving behaviors at weaving sections. Aggressive drivers have a higher mean speed and mean longitudinal deceleration, followed by normal and conservative drivers. Significant differences in the range of lane-change positions were found between 100, 150 and 200 m of weaving length for the same type of drivers, and the duration of weaving for aggressive drivers was significantly smaller than for normal and conservative drivers. A significant correlation was found between lane-change position and weaving duration. These results can help traffic engineers to propose effective control strategies for different types of drivers, to improve the safety of weaving sections.

Suggested Citation

  • Zhanji Zheng & Qiaojun Xiang & Xin Gu & Yongfeng Ma & Kangkang Zheng, 2020. "The Influence of Individual Differences on Diverging Behavior at the Weaving Sections of an Urban Expressway," IJERPH, MDPI, vol. 18(1), pages 1-17, December.
  • Handle: RePEc:gam:jijerp:v:18:y:2020:i:1:p:25-:d:466618
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/1/25/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/1/25/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zheng, Jihu & Zhou, Yan & Yu, Rujie & Zhao, Dongchang & Lu, Zifeng & Zhang, Peng, 2019. "Survival rate of China passenger vehicles: A data-driven approach," Energy Policy, Elsevier, vol. 129(C), pages 587-597.
    2. Daniel (Jian) Sun & Lily Elefteriadou, 2014. "A Driver Behavior-Based Lane-Changing Model for Urban Arterial Streets," Transportation Science, INFORMS, vol. 48(2), pages 184-205, May.
    3. Golob, Thomas F. & Recker, Wilfred W. & Alvarez, Veronica M., 2004. "Safety aspects of freeway weaving sections," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(1), pages 35-51, January.
    4. Xinhua Mao & Changwei Yuan & Jiahua Gan & Shiqing Zhang, 2019. "Risk Factors Affecting Traffic Accidents at Urban Weaving Sections: Evidence from China," IJERPH, MDPI, vol. 16(9), pages 1-17, May.
    5. Sun, Shichao & Duan, Zhengyu, 2019. "Modeling passengers’ loyalty to public transit in a two-dimensional framework: A case study in Xiamen, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 295-309.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wojciech Rabiega & Artur Gorzałczyński & Robert Jeszke & Paweł Mzyk & Krystian Szczepański, 2021. "How Long Will Combustion Vehicles Be Used? Polish Transport Sector on the Pathway to Climate Neutrality," Energies, MDPI, vol. 14(23), pages 1-19, November.
    2. Fanyu Wang & Junyou Zhang & Shufeng Wang & Sixian Li & Wenlan Hou, 2020. "Analysis of Driving Behavior Based on Dynamic Changes of Personality States," IJERPH, MDPI, vol. 17(2), pages 1-17, January.
    3. Yaqi Liu & Xiaoyuan Wang, 2020. "Differences in Driving Intention Transitions Caused by Driver’s Emotion Evolutions," IJERPH, MDPI, vol. 17(19), pages 1-22, September.
    4. de Oña, Juan, 2020. "The role of involvement with public transport in the relationship between service quality, satisfaction and behavioral intentions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 296-318.
    5. Bi, Hui & Ye, Zhirui & Hu, Liyang & Zhu, He, 2021. "Why they don't choose bus service? Understanding special online car-hailing behavior near bus stops," Transport Policy, Elsevier, vol. 114(C), pages 280-297.
    6. Li, Yi & Wang, Zhaohua & Wang, Ke & Zhang, Bin, 2021. "Fuel economy of Chinese light-duty car manufacturers: An efficiency analysis perspective," Energy, Elsevier, vol. 220(C).
    7. Snelder, M. & Wesseling, B. & van Arem, B. & Hertogh, M.J.C.M., 2017. "Evaluating the robustness effects of infrastructure projects based on their topological and geometrical roadway designs," Transport Policy, Elsevier, vol. 57(C), pages 20-30.
    8. Yu, Bin & Zhou, Huixin & Wang, Lin & Wang, Zirui & Cui, Shaohua, 2021. "An extended two-lane car-following model considering the influence of heterogeneous speed information on drivers with different characteristics under honk environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    9. Jin, Wen-Long, 2010. "A kinematic wave theory of lane-changing traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 1001-1021, September.
    10. Yuquan Zhou & Yingzhi Wang & Feng Zhang & Hongye Zhou & Keran Sun & Yuhan Yu, 2023. "GATR: A Road Network Traffic Violation Prediction Method Based on Graph Attention Network," IJERPH, MDPI, vol. 20(4), pages 1-18, February.
    11. Xu Hao & Yan Zhou & Hewu Wang & Minggao Ouyang, 2020. "Plug-in electric vehicles in China and the USA: a technology and market comparison," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(3), pages 329-353, March.
    12. Yan, Yingying & Zhong, Shiquan & Tian, Junfang & Li, Tong, 2022. "Continuance intention of autonomous buses: An empirical analysis based on passenger experience," Transport Policy, Elsevier, vol. 126(C), pages 85-95.
    13. Shichao Sun & Yuanqian Liu & Yukun Yao & Zhengyu Duan & Xiaokun Wang, 2021. "The Determinants to Promote College Students’ Use of Car-Sharing: An Empirical Study at Dalian Maritime University, China," Sustainability, MDPI, vol. 13(12), pages 1-12, June.
    14. Jihu Zheng & Rujie Yu & Yong Liu & Yuhong Zou & Dongchang Zhao, 2019. "The Technological Progress of the Fuel Consumption Rate for Passenger Vehicles in China: 2009–2016," Energies, MDPI, vol. 12(12), pages 1-14, June.
    15. Abdelhalim Azam & Fayez Alanazi & Mohamed Ahmed Okail & Mohamed Ragab, 2023. "Operational and Environmental Assessment of Weaving Section for Urban Roads: Case Study, Aljouf Region, KSA," Sustainability, MDPI, vol. 15(5), pages 1-13, February.
    16. Yulan Xia & Yaqin Qin & Xiaobing Li & Jiming Xie, 2022. "Risk Identification and Conflict Prediction from Videos Based on TTC-ML of a Multi-Lane Weaving Area," Sustainability, MDPI, vol. 14(8), pages 1-21, April.
    17. Sajjakaj Jomnonkwao & Thanapong Champahom & Vatanavongs Ratanavaraha, 2020. "Methodologies for Determining the Service Quality of the Intercity Rail Service Based on Users’ Perceptions and Expectations in Thailand," Sustainability, MDPI, vol. 12(10), pages 1-20, May.
    18. Zhao, Jingya & Liu, Qingchao, 2024. "Quantitative causality assessment between traffic states and crash risk in freeway segments with closely spaced entrance and exit ramps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    19. Jin, Wen-Long, 2013. "A multi-commodity Lighthill–Whitham–Richards model of lane-changing traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 361-377.
    20. Cheng, Zeyang & Wang, Wei & Lu, Jian & Xing, Xue, 2020. "Classifying the traffic state of urban expressways: A machine-learning approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 411-428.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2020:i:1:p:25-:d:466618. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.