How various urgencies and visibilities influence drivers' takeover performance in critical car-following conditions? A driving simulation study

被引:4
作者
Lin, Zijian [1 ]
Chen, Feng [1 ]
机构
[1] Tongji Univ, Key Lab Rd & Traff Engn, Minist Educ, 4800 Caoan Rd, Shanghai 201804, Peoples R China
基金
中国国家自然科学基金;
关键词
Automated driving; Takeover; Visibility; Urgency; ADAPTIVE CRUISE CONTROL; HIGHLY AUTOMATED VEHICLES; SITUATION AWARENESS; BEHAVIORAL ADAPTATION; VISUAL-ATTENTION; CONTROL ACC; TIME; LOOP; FOG; SPEED;
D O I
10.1016/j.trf.2024.06.007
中图分类号
B849 [应用心理学];
学科分类号
040203 ;
摘要
Drivers of Level 3 automated vehicles are relieved from the driving task in specific circumstances but are required to take over control once the takeover request is prompted. Previous studies have investigated drivers' takeover performance in non-critical car-following. However, little is known about drivers' takeover behaviors in critical car-following, especially in low-visibility weather, which remarkably increases the risk of car-following. A driving simulator experiment with a 2 x 3 x 3 factor within-group design was conducted. The design matrix contained two weather conditions (clear and foggy), three car-following time headways (2 s, 3 s, 4 s) and three deceleration rates of the lead vehicle (LV) (0, 2 m/s2, 4 m/s2). A total of 30 participants completed the experiment. The results showed that in critical car-following situations, drivers faced greater challenges in negotiating with adjacent vehicles rather than the LV itself. Urgency and visibility did not significantly impact the likelihood of a crash with the LV due to drivers' adoption of stronger braking. However, decreased visibility and higher LV's deceleration increased the crash rate when drivers attempted lane changes. As urgency increased, drivers tended to change lanes earlier, leading to higher lane-changing risks and compromised lateral stability. This study can provide some insights for the car-following strategies of automated driving vehicles and the design of dedicated takeover schemes in various transportation environments.
引用
收藏
页码:303 / 317
页数:15
相关论文
共 58 条
  • [1] A study on crashes related to visibility obstruction due to fog and smoke
    Abdel-Aty, Mohamed
    Ekram, Al-Ahad
    Huang, Helai
    Choi, Keechoo
    [J]. ACCIDENT ANALYSIS AND PREVENTION, 2011, 43 (05) : 1730 - 1737
  • [2] [Anonymous], 2009, TRAFFIC SAFETY FACTS
  • [3] Bertoncello M., 2015, Ten ways autonomous driving could redefine the automotive world
  • [4] Driver's behavioral adaptation to Adaptive Cruise Control (ACC): The case of speed and time headway
    Bianchi Piccinini, Giulio Francesco
    Rodrigues, Carlos Manuel
    Leitao, Miguel
    Simoes, Anabela
    [J]. JOURNAL OF SAFETY RESEARCH, 2014, 49 : 77 - 84
  • [5] Behavioral changes to repeated takeovers in automated driving: The drivers' ability to transfer knowledge and the effects of takeover request process
    Brandenburg, Stefan
    Roche, Fabienne
    [J]. TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2020, 73 : 15 - 28
  • [6] Effects of Fog in a Brazilian Road Segment Analyzed by a Driving Simulator for Sustainable Transport: Drivers' Visual Profile
    Calsavara, Felipe
    Kabbach Junior, Felipe Issa
    Larocca, Ana Paula C.
    [J]. SUSTAINABILITY, 2021, 13 (16)
  • [7] Charlton S.G., 2002, Handbook of Human Factors Testing and Evaluation, P115
  • [8] Effects of adaptive cruise control and highly automated driving on workload and situation awareness: A review of the empirical evidence
    de Winter, Joost C. F.
    Happee, Riender
    Martens, Marieke H.
    Stanton, Neville A.
    [J]. TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2014, 27 : 196 - 217
  • [9] Effects of non-driving-related tasks on takeover performance in different takeover situations in conditionally automated driving
    Dogan, Ebru
    Honnet, Vincent
    Masfrand, Stephan
    Guillaume, Anne
    [J]. TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2019, 62 : 494 - 504
  • [10] Predicting driver reaction time and deceleration: Comparison of perception-reaction thresholds and evidence accumulation framework
    Durrani, Umair
    Lee, Chris
    Shah, Dhwani
    [J]. ACCIDENT ANALYSIS AND PREVENTION, 2021, 149