Drivers' engagement in NDRTs during automated driving linked to travelling speed and surrounding traffic

被引:2
|
作者
Liu, Xian [1 ,2 ]
Madigan, Ruth [1 ]
Sadraei, Ehsan [1 ]
Lee, Yee Mun [1 ]
Merat, Natasha [1 ]
机构
[1] Univ Leeds, Inst Transport Studies, Leeds, England
[2] Southeast Univ, Sch Transportat, Nanjing, Peoples R China
关键词
Automated vehicles; NDRTs; Glance behaviour; Distraction; Driving environment; TAKEOVER TIME; VISUAL-ATTENTION;
D O I
10.1016/j.trf.2024.01.010
中图分类号
B849 [应用心理学];
学科分类号
040203 ;
摘要
Previous simulator and real -world studies with SAE Level 2 automated vehicles (AVs) have shown that, when compared to manual driving, drivers are more inattentive to the driving environment when automation is engaged, as reflected by fewer glances towards the forward roadway and side/rear view mirrors, and more focus on non -driving related tasks (NDRTs). Manual driving studies also suggest that drivers are more likely to engage in NDRTs during slow -moving or stationary traffic conditions. The aim of the current study was to understand whether NDRT engagement and visual attention patterns are impacted by the driving environment while drivers experienced a ride in a real -world SAE Level 3 AV. Forty-six video clips, from 32 drivers interacting with NDRTs during L3 motorway driving were analysed for this study. Due to the absence of externally facing cameras, the mean and standard deviation (SD) of driving speed were used as a proxy for assessing the surrounding traffic volume. The number of glances, and mean glance duration away from NDRTs per minute, were used as proxy measures for NDRT engagement. A generalised linear mixed model (GLMM) was used to investigate the effect of surrounding traffic on NDRT engagement. Results showed that the number and mean duration of glances away from the NDRT increased significantly when the SD of speed was high. The mean speed had a significant effect on the mean glance duration, with longer glances away from NDRTs when mean speed was low, compared to that in high speed. There was a significant effect of age on NDRT engagement, with older drivers less likely to engage in another task, while female drivers were more engaged in NDRTs than males. Overall, the results indicate that drivers' propensity to engage in NDRTs is impacted by the AV's speed, which is influenced by the volume of surrounding traffic. These results are useful for understanding the implications of surrounding traffic on drivers' self -regulated engagement in NDRTs in the real world during SAE Level 3 driving.
引用
收藏
页码:332 / 339
页数:8
相关论文
共 50 条
  • [21] Expert Drivers' Prospective Thinking-Aloud to Enhance Automated Driving Technologies - Investigating Uncertainty and Anticipation in Traffic
    Grahn, Hilkka
    Kujala, Tuomo
    Silvennoinen, Johanna
    Leppanen, Aino
    Saariluoma, Pertti
    ACCIDENT ANALYSIS AND PREVENTION, 2020, 146 (146):
  • [22] Older drivers' perceptions, responses, and driving behaviours during complex traffic conditions at a signalized intersection
    Hong, I.
    Kurihara, T.
    Wasaki, M.
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2008, 222 (D11) : 2063 - 2076
  • [23] Highly Automated Driving Impact on Drivers' Gaze Behaviors during a Car-Following Task
    Navarro, J.
    Osiurak, F.
    Ovigue, M.
    Charrier, L.
    Reynaud, E.
    INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION, 2019, 35 (11) : 1008 - 1017
  • [24] Drivers' gap acceptance during parking maneuvers as a basis for initiating driving actions in automated vehicles
    Hensch, Ann-Christin
    Beggiato, Matthias
    Krems, Josef F.
    TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2023, 92 : 133 - 142
  • [25] The effect of motor control requirements on drivers ' eye-gaze pattern during automated driving
    Goncalves, Rafael C.
    Louw, Tyron L.
    Quaresma, Manuela
    Madigan, Ruth
    Merat, Natasha
    ACCIDENT ANALYSIS AND PREVENTION, 2020, 148 (148):
  • [26] How Do Drivers Perceive Risks During Automated Driving Scenarios? An fNIRS Neuroimaging Study
    Perello-March, Jaume
    Burns, Christopher G.
    Woodman, Roger
    Birrell, Stewart
    Elliott, Mark T.
    HUMAN FACTORS, 2024, 66 (09) : 2244 - 2263
  • [27] The Impact of Expectations about Automated and Manual Vehicles on Drivers' Behavior: Insights from a Mixed Traffic Driving Simulator Study
    Miller, Linda
    Koniakowsky, Ina
    Kraus, Johannes
    Baumann, Martin
    PROCEEDINGS OF THE 14TH INTERNATIONAL ACM CONFERENCE ON AUTOMOTIVE USER INTERFACES AND INTERACTIVE VEHICULAR APPLICATIONS, AUTOMOTIVEUI 2022, 2022, : 150 - 161
  • [28] Overtaking automated truck platoons: Effects of platoon organisations and traffic situation on driving behaviours of nearby manual vehicle drivers
    Lin, Zijian
    Chen, Feng
    Ozturk, Ibrahim brahim
    Merat, Natasha
    TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2025, 109 : 1208 - 1228
  • [29] Exploring driving anger-caused impairment of takeover performance among professional taxi drivers during partially automated driving
    Pan, Hengyan
    Payre, William
    Gao, Zhixiang
    Wang, Yonggang
    ACCIDENT ANALYSIS AND PREVENTION, 2024, 205
  • [30] Using pupillometry and gaze-based metrics for understanding drivers' mental workload during automated driving
    Radhakrishnan, Vishnu
    Louw, Tyron
    Goncalves, Rafael Cirino
    Torrao, Guilhermina
    Lenne, Michael G.
    Merat, Natasha
    TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2023, 94 : 254 - 267