Who goes first? A distributed simulator study of vehicle-pedestrian interaction

被引:10
|
作者
Kalantari, Amir Hossein [1 ]
Yang, Yue [1 ]
de Pedro, Jorge Garcia [1 ]
Lee, Yee Mun [1 ]
Horrobin, Anthony [1 ]
Solernou, Albert [1 ]
Holmes, Christopher [1 ,2 ]
Merat, Natasha [1 ]
Markkula, Gustav [1 ]
机构
[1] Univ Leeds, Inst Transport Studies, Leeds LS2 9JT, England
[2] Nissan Tech Ctr Europe, Cranfield MK43 0DB, Beds, England
来源
基金
欧盟地平线“2020”; “创新英国”项目;
关键词
Zebra crossing; Autonomous Vehicles; Gap acceptance; Mixed-effects model; Traffic psychology; DRIVERS SPEED BEHAVIOR; SENSATION SEEKING; GAP ACCEPTANCE; SIGNALIZED INTERSECTIONS; CROSSING BEHAVIOR; TIME; COMMUNICATION; IMPACT; MODEL;
D O I
10.1016/j.aap.2023.107050
中图分类号
TB18 [人体工程学];
学科分类号
1201 ;
摘要
One of the current challenges of automation is to have highly automated vehicles (HAVs) that communicate effectively with pedestrians and react to changes in pedestrian behaviour, to promote more trustable HAVs. However, the details of how human drivers and pedestrians interact at unsignalised crossings remain poorly understood. We addressed some aspects of this challenge by replicating vehicle-pedestrian interactions in a safe and controlled virtual environment by connecting a high fidelity motion-based driving simulator to a CAVE -based pedestrian lab in which 64 participants (32 pairs of one driver and one pedestrian) interacted with each other under different scenarios. The controlled setting helped us study the causal role of kinematics and priority rules on interaction outcome and behaviour, something that is not possible in naturalistic studies. We also found that kinematic cues played a stronger role than psychological traits like sensation seeking and social value orientation in determining whether the pedestrian or driver passed first at unmarked crossings. One main contribution of this study is our experimental paradigm, which permitted repeated observation of crossing in-teractions by each driver-pedestrian participant pair, yielding behaviours which were qualitatively in line with observations from naturalistic studies.
引用
收藏
页数:13
相关论文
共 49 条
  • [21] Study of Reconstruction of Vehicle-Pedestrian Collision Accident Based on Computer Simulation
    Pan, Gongyu
    Zhang, Shu
    Zhu, Lusheng
    [J]. MACHINERY ELECTRONICS AND CONTROL ENGINEERING III, 2014, 441 : 448 - 451
  • [22] A Multi-State Social Force Based Framework for Vehicle-Pedestrian Interaction in Uncontrolled Pedestrian Crossing Scenarios
    Yang, Dongfang
    Redmill, Keith
    Ozguner, Umit
    [J]. 2020 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2020, : 1807 - 1812
  • [23] Designing Wearable Augmented Reality Concepts to Support Scalability in Autonomous Vehicle-Pedestrian Interaction
    Tram Thi Minh Tran
    Parker, Callum
    Wang, Yiyuan
    Tomitsch, Martin
    [J]. FRONTIERS IN COMPUTER SCIENCE, 2022, 4
  • [24] Analysis of a Game Theory-based Model of Vehicle-Pedestrian Interaction at Uncontrolled Crosswalks
    Skugor, Branimir
    Topic, Jakov
    Deur, Josko
    Ivanovic, Vladimir
    Tseng, Eric
    [J]. PROCEEDINGS OF 2020 INTERNATIONAL CONFERENCE ON SMART SYSTEMS AND TECHNOLOGIES (SST 2020), 2020, : 73 - 81
  • [25] A study of an Asian anthropometric pedestrian in vehicle-pedestrian accidents using real-world accident data
    Guo, R.
    Yuan, Q.
    Sturgess, C. E. N.
    Hassan, A. M.
    Li, Y.
    Hu, Y.
    [J]. INTERNATIONAL JOURNAL OF CRASHWORTHINESS, 2006, 11 (06) : 541 - 551
  • [26] A Study on Vehicle-Pedestrian Communication System Using Warning Ranges of Mobile Objects
    Otani, Ruka
    Shikishima, Akito
    Wada, Tomotaka
    [J]. 2020 34TH INTERNATIONAL CONFERENCE ON INFORMATION NETWORKING (ICOIN 2020), 2020, : 517 - 522
  • [27] A POMDP Treatment of Vehicle-Pedestrian Interaction: Implicit Coordination via Uncertainty-Aware Planning
    Hsu, Ya-Chuan
    Gopalswamy, Swaminathan
    Saripalli, Srikanth
    Shell, Dylan A.
    [J]. 2020 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2020, : 1984 - 1991
  • [28] Evaluating the effectiveness of new-designed crosswalk markings at intersections in China considering vehicle-pedestrian interaction
    Bian, Yang
    Liang, Kun
    Zhao, Xiaohua
    Li, Haijian
    Yang, Liping
    [J]. ACCIDENT ANALYSIS AND PREVENTION, 2020, 139
  • [29] In-Depth Safety Analysis for Right-Turn Vehicle-Pedestrian Interaction Based on Checkpoint Video
    Zhou, Yun-Tong
    Chen, Yan-Yan
    Gu, Xin
    Guo, Yin-Jia
    Cao, Bing-Xin
    [J]. CICTP 2023: INNOVATION-EMPOWERED TECHNOLOGY FOR SUSTAINABLE, INTELLIGENT, DECARBONIZED, AND CONNECTED TRANSPORTATION, 2023, : 1504 - 1514
  • [30] Autonomous Vehicle-Pedestrian Interaction Across Cultures: Towards Designing Better External Human Machine Interfaces (eHMIs)
    Ranasinghe, Champika
    Hollaender, Kai
    Currano, Rebecca
    Sirkin, David
    Moore, Dylan
    Schneegass, Stefan
    Ju, Wendy
    [J]. CHI'20: EXTENDED ABSTRACTS OF THE 2020 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, 2020,