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Pedestrian gap acceptance for mid-block street crossing

Author

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  • G. Yannis
  • E. Papadimitriou
  • A. Theofilatos

Abstract

This paper investigates pedestrians' traffic gap acceptance for mid-block street crossing in urban areas. A field survey was carried out at an uncontrolled mid-block location in Athens, Greece. Pedestrians' decisions and traffic conditions were videotaped in terms of the size of traffic gaps rejected or accepted, waiting times and crossing attempts and vehicle speeds. A lognormal regression model was developed to examine pedestrian gap acceptance. It was found that gap acceptance was better explained by the distance from the incoming vehicle, rather than its speed. Other significant effects included illegal parking, presence of other pedestrians and incoming vehicles' size. A binary logistic regression model was developed to examine the effect of traffic gaps and other parameters on pedestrians' decisions to cross the street or not. The results reveal that this decision is affected by the distance from the incoming vehicles and the waiting times of pedestrians.

Suggested Citation

  • 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.
  • Handle: RePEc:taf:transp:v:36:y:2013:i:5:p:450-462
    DOI: 10.1080/03081060.2013.818274
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    Citations

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    Cited by:

    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.

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