Understanding take-over performance of high crash risk drivers during conditionally automated driving

• Published in: Accident analysis and prevention Vol. 143; p. 105543
• Main Authors: Lin, Qingfeng, Li, Shiqi, Ma, Xiaowei, Lu, Guangquan
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.08.2020
• Subjects: Automated driving; Crash risk; Distraction; Driver behavior; Take-over; Distraction; Crash risk; Automated driving; Take-over; Driver behavior
• DOI: 10.1016/j.aap.2020.105543
• ISSN: 0001-4575; 1879-2057

•A driving simulator study examined the effects of time budget and task on take-over performance for lower crash risk (LCR) and high crash risk (HCR) drivers.•LCR drivers had shorter brake reaction time compared to HCR drivers.•Reading the news and watching a video seem to have a similar effect on the drivers’ workload. Understanding driver behavior of conditionally automated driving is necessary to ensure a safe transition from automated to manual driving. This study aimed to examine the difference in take-over performance between high crash risk (HCR) and lower crash risk (LCR) drivers in emergency take-over situations during conditionally automated driving. In the current simulator study, a 3 × 3 (within-subjects) factorial design was used, including the task factors (no task, reading the news, and watching a video) and time budget factors (time budget = 3 s, 4 s, and 5 s). Forty-eight participants completed a test drive on an approximately 10 km long two-way six-lane urban road. The participants firstly were in manual control and then switched to the automated driving mode at a speed of 50 km/h. The automated driving system was able to detect a broken car in the ego-lane and requested the driver to take over the control of the vehicle. There are at least one or two other vehicles or motorcycles on each side of the ego-vehicle, resulting in fewer escape paths. For the two non-handheld non-driving-related tasks (NDRTs), the participants were asked to be fully engaged in a task without any need to monitor the road environments. Each participant completed nine emergency take-over situations. The participants were classified into two groups that were labeled LCR (N ≤ 2) and HCR drivers (N ≥ 3) according to the number of accidents per driver. The results show that LCR drivers had shorter brake reaction time compared to HCR drivers. For all drivers, the engagement in a task led to longer response times, and the time budget affected the longitudinal vehicle control. In addition, the task affected the response times for LCR and HCR drivers, but only the time budget affected the longitudinal vehicle control for LCR drivers. For all drivers, LCR and HCR drivers, the time budget and task affected the safety of take-over. Especially, the two non-handheld everyday tasks seem to have a similar effect on the drivers’ workload. Therefore, the HCR drivers had a lower hazard perception compared to the LCR drivers, and the factor regarding the individual difference of driving ability in take-over situations should be considered to design safe take-over concepts for automated vehicles.