IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i12p7208-d837133.html
   My bibliography  Save this article

Analysis of the Effect of Human-Machine Co-Driving Vehicle on Pedestrian Crossing Speed at Uncontrolled Mid-Block Road Sections: A VR-Based Case Study

Author

Listed:
  • Kun Wang

    (School of Transportation Science and Engineering, Beihang University, Beijing 102206, China
    Beihang Hangzhou Innovation Institute Yuhang, Hangzhou 310023, China)

  • Liang Xu

    (Beihang Hangzhou Innovation Institute Yuhang, Hangzhou 310023, China)

  • Han Jiang

    (School of Transportation Science and Engineering, Beihang University, Beijing 102206, China)

Abstract

The current study investigates the effects of speed and time headway of human-machine co-driving vehicles on pedestrian crossing speed at uncontrolled mid-block road sections. A VR-based simulation study is conducted to study pedestrian crossing behaviour when facing human-machine co-driving vehicles. A total of 30 college students are recruited, and each participant is required to complete 5 street-crossing simulator trials facing human-machine co-driving vehicles with varying time headway levels and speeds. The correlations and differences between demographic information, time headway, vehicle speed, and pedestrian crossing speed are analyzed. The results show that gender and pedestrian’s trust in human-machine co-driving vehicles are significantly correlated with pedestrian crossing speed. The pedestrian crossing speed increases with the increase in vehicle speed and decreases with the increase in vehicle time headway. In addition, the time headway has a stronger correlation with the pedestrian crossing speed than the vehicle speed. The findings will provide theoretical and methodological support for the formulation of pedestrian crossing control measures in the stage of human-machine co-driving.

Suggested Citation

  • Kun Wang & Liang Xu & Han Jiang, 2022. "Analysis of the Effect of Human-Machine Co-Driving Vehicle on Pedestrian Crossing Speed at Uncontrolled Mid-Block Road Sections: A VR-Based Case Study," IJERPH, MDPI, vol. 19(12), pages 1-12, June.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:12:p:7208-:d:837133
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/12/7208/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/12/7208/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. G. Yannis & E. Papadimitriou & A. Theofilatos, 2013. "Pedestrian gap acceptance for mid-block street crossing," Transportation Planning and Technology, Taylor & Francis Journals, vol. 36(5), pages 450-462, July.
    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. Wafaa Saleh & Monika Grigorova & Samia Elattar, 2020. "Pedestrian Road Crossing at Uncontrolled Mid-Block Locations: Does the Refuge Island Increase Risk?," Sustainability, MDPI, vol. 12(12), pages 1-16, June.
    2. Jiaming Shi & Changxu Wu & Xiuying Qian, 2020. "The Effects of Multiple Factors on Elderly Pedestrians’ Speed Perception and Stopping Distance Estimation of Approaching Vehicles," Sustainability, MDPI, vol. 12(13), pages 1-16, June.
    3. Chen, Qun & Wang, Yan, 2015. "Cellular automata (CA) simulation of the interaction of vehicle flows and pedestrian crossings on urban low-grade uncontrolled roads," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 43-57.
    4. Nam Seok Kim & Seung Sub Yoon & Donghyung Yook, 2017. "Performance comparison between pedestrian push-button and pre-timed pedestrian crossings at midblock: a Korean case study," Transportation Planning and Technology, Taylor & Francis Journals, vol. 40(6), pages 706-721, August.
    5. Arshad Jamal & Muhammad Ijaz & Meshal Almosageah & Hassan M. Al-Ahmadi & Muhammad Zahid & Irfan Ullah & Rabia Emhamed Al Mamlook, 2022. "Implementing the Maximum Likelihood Method for Critical Gap Estimation under Heterogeneous Traffic Conditions," Sustainability, MDPI, vol. 14(23), pages 1-13, November.
    6. Lachapelle, Ugo & Cloutier, Marie-Soleil, 2017. "On the complexity of finishing a crossing on time: Elderly pedestrians, timing and cycling infrastructure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 54-63.
    7. Nadine Schuurman & Blake Byron Walker & David Swanlund & Ofer Amram & Natalie L. Yanchar, 2020. "Qualitative Field Observation of Pedestrian Injury Hotspots: A Mixed-Methods Approach for Developing Built- and Socioeconomic-Environmental Risk Signatures," IJERPH, MDPI, vol. 17(6), pages 1-15, March.
    8. Savvas Emmanouilidis & Socrates Basbas & Alexandros Sdoukopoulos & Ioannis Politis, 2022. "Settlements along Main Road Axes: Blessing or Curse? Evaluating the Barrier Effect in a Small Greek Settlement," Land, MDPI, vol. 11(12), pages 1-20, December.
    9. Yu, Chunhui & Ma, Wanjing & Lo, Hong K. & Yang, Xiaoguang, 2015. "Optimization of mid-block pedestrian crossing network with discrete demands," Transportation Research Part B: Methodological, Elsevier, vol. 73(C), pages 103-121.
    10. Wang, Yan & Peng, Zhongyi & Chen, Qun, 2018. "Simulated interactions of pedestrian crossings and motorized vehicles in residential areas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1046-1060.

    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:19:y:2022:i:12:p:7208-:d:837133. 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.