Distracted Walking: Does it impact pedestrian-vehicle interaction behavior?

被引:0
|
作者
Alsharif, Tala [1 ]
Lanzaro, Gabriel [1 ]
Sayed, Tarek [1 ]
机构
[1] Univ British Columbia, Dept Civil Engn, Vancouver, BC, Canada
来源
关键词
Distracted pedestrians; Multi-Agent Modeling; Adversarial Inverse Reinforcement Learning; Pedestrian-Vehicle Conflicts; Urban Traffic Simulations; SOCIAL FORCE MODEL; COLLISION-AVOIDANCE; SHARED SPACE; CROSSING BEHAVIOR; INJURY SEVERITY; SAFETY; CROSSWALK; PHONES;
D O I
10.1016/j.aap.2024.107789
中图分类号
TB18 [人体工程学];
学科分类号
1201 ;
摘要
Several studies have developed pedestrian-vehicle interaction models. However, these studies failed to consider pedestrian distraction, which considerably influences the safety of these interactions. Utilizing data from two intersections in Vancouver, Canada, this research uses the Multi-agent Adversarial Inverse Reinforcement Learning (MA-AIRL) framework to make inferences about the behavioral dynamics of distracted and nondistracted pedestrians while interacting with vehicles. Results showed that distracted pedestrians maintained closer proximity to vehicles, moved at reduced speeds, and rarely yielded to oncoming vehicles. In addition, they rarely changed their interaction angles regardless of lateral proximity to vehicles, indicating that they mostly remain unaware of the surrounding environment and have decreased navigational efficiency. Conversely, nondistracted pedestrians executed safer maneuvers, kept greater distances from vehicles, yielded more frequently, and adjusted their speeds accordingly. For example, non-distracted pedestrian-vehicle interactions showed a 46.5% decrease in traffic conflicts severity (as measured by the average Time-to-Collision (TTC) values) and an average 30.2% increase in minimum distances when compared to distracted pedestrian-vehicle interactions. Vehicle drivers also demonstrated different behaviors in response to distracted pedestrians. They often opted to decelerate around distracted pedestrians, indicating recognition of potential risks. Furthermore, the MA-AIRL framework provided different results depending on the type of interactions. The performance of the distracted vehicle-pedestrian model was lower than the non-distracted model, suggesting that predicting nondistracted behavior might be relatively easier. These findings emphasize the importance of refining pedestrian simulation models to include the unique behavioral patterns from pedestrian distractions. This should assist in further examining the safety impacts of pedestrian distraction on the road environment.
引用
收藏
页数:19
相关论文
共 50 条
  • [1] PEDESTRIAN-VEHICLE INTERACTION AT PEDESTRIAN CROSSINGS
    GRIFFITHS, JD
    HUNT, JG
    [J]. BULLETIN OF THE BRITISH PSYCHOLOGICAL SOCIETY, 1982, 35 (SEP): : A74 - A74
  • [2] A Multiagent System for Simulating Pedestrian-Vehicle Interaction
    Yu, Chang-Han
    Liu, Alan
    Zhou, Pei-Chuan
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC), 2014, : 359 - 364
  • [3] A Pedestrian-Pedestrian and Pedestrian-Vehicle Interaction Motion Model for Pedestrians Tracking
    Sheng, Hao
    Liu, Shukai
    Ji, Hengshan
    Chen, Jiahui
    Xiong, Zhang
    [J]. ADVANCES IN VISUAL COMPUTING (ISVC 2014), PT 1, 2014, 8887 : 270 - 280
  • [4] Reconstruction model of vehicle impact speed in pedestrian-vehicle accident
    Xu, Jun
    Li, Yibing
    Lu, Guangquan
    Zhou, Wei
    [J]. INTERNATIONAL JOURNAL OF IMPACT ENGINEERING, 2009, 36 (06) : 783 - 788
  • [5] Pedestrian-Vehicle Interaction at Unsignalized Crosswalks: A Systematic Review
    Amado, Harley
    Ferreira, Sara
    Tavares, Jose Pedro
    Ribeiro, Paulo
    Freitas, Elisabete
    [J]. SUSTAINABILITY, 2020, 12 (07)
  • [6] Effect of vehicle external acceleration signal light on pedestrian-vehicle interaction
    Li, Feng
    Pan, Wenjun
    Xiang, Jiali
    [J]. SCIENTIFIC REPORTS, 2023, 13 (01)
  • [7] Effect of vehicle external acceleration signal light on pedestrian-vehicle interaction
    Feng Li
    Wenjun Pan
    Jiali Xiang
    [J]. Scientific Reports, 13
  • [8] Evaluation and Impact Analysis of Pedestrian-vehicle Conflict Severity
    Peng, Yong
    Jiang, Pei
    Sha, Xiao-Yu
    Zou, Tian
    Liu, Song
    [J]. Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology, 2019, 19 (02): : 175 - 181
  • [9] A Framework of Pedestrian-Vehicle Interaction Scenarios for eHMI Design and Evaluation
    Song, Yuanming
    Zhuang, Xiangling
    Zhang, Jingyu
    [J]. ENGINEERING PSYCHOLOGY AND COGNITIVE ERGONOMICS, EPCE 2023, PT II, 2023, 14018 : 523 - 532
  • [10] Pedestrian-Vehicle Interaction in Shared Space: Insights for Autonomous Vehicles
    Wang, Yiyuan
    Hespanhol, Luke
    Worrall, Stewart
    Tomitsch, Martin
    [J]. PROCEEDINGS OF THE 14TH INTERNATIONAL ACM CONFERENCE ON AUTOMOTIVE USER INTERFACES AND INTERACTIVE VEHICULAR APPLICATIONS, AUTOMOTIVEUI 2022, 2022, : 330 - 339