One of the main challenges in limiting the application of conditional driving automation is the presence of safety hazards during the process of drivers taking over vehicle control. In order to deal with the takeover safety challenge, automated driving system can provide the driver with safety control assistance under some complex and dangerous takeover conditions, and directly hand over control to the driver only under some simple and safe takeover conditions. There are no other vehicles around the ego vehicle and the weather is good, which is a relatively simple takeover scenario. In this scenario, takeover time budget and non-driving related tasks (NDRTs) are the key to determine whether the automated driving system can directly hand over control to the driver. This paper designed a conditional automated driving takeover experiment based on a driving simulator, recruiting a total of 45 participants to explore the impact of takeover time budget (5 s, 7 s, 10 s) and NDRTs (monitoring driving, non-visual NDRT, visual NDRT) on drivers’ takeover performance in the simple takeover scenario. Statistical analysis showed that both the takeover time budget and NDRTs significantly affected the driver’s takeover time and quality. More importantly, we found that under the condition of 5 s takeover time budget, the driver's visual distraction state could cause a near-crash situations (minimum TTC after takeover < 1 s). This result indicates that when the driver is visually distracted under 5 s budget condition, the system should also provide safety control assistance in the simple takeover scenario. When the takeover time budget is greater than 5 s, the system can directly hand over control to the driver. This conclusion can provide a theoretical basis for the safety design of conditional automated driving system.
Analyzing Takeover Performance in Conditional Driving Automation: Focusing on Takeover Conditions in Which Vehicle Control Can Be Transferred Directly to Drivers
Lect. Notes Electrical Eng.
International Conference on Green Intelligent Transportation System and Safety ; 2022 ; Qinghuangdao, China September 16, 2022 - September 18, 2022
2024-09-29
13 pages
Article/Chapter (Book)
Electronic Resource
English