Differed Risk Perception in Manual and Automated Driving: An Empirical Study of Varied Conditions

Abstract

The interface of L3 automated driving systems needs to take both automated and manual driving into consideration. This calls for a comprehension of drivers’ differed risk perception under manual and automated driving conditions, thus supporting description of contextual information and appropriate risk warnings. Existing studies have reported drivers’ impaired ability during automated driving, however, a quantified measurement is still lacking. This study tried to measure the difference in drivers’ ability to perceive risks during automated and manual driving. Specifically, a simulated driving experiment in car-following scenarios was conducted to collect drivers’ perceived risk under multiple manual and automated driving conditions, including varied motion directions, speed, and distance among vehicles. Then, the influences of driving mode, motion directions, speed, and distance on drivers’ risk perceptions were described using a linear mixed model. The result demonstrated a complicated interaction effect. Automated driving impaired drivers’ risk perception, and this effect was less severe in highly risky events. In both manual and automated driving, drivers were less sensitive to risk only when risky events happened backwards. These results indicated drivers’ varied ability under multiple conditions, and supported warning design and interface refinement under automated and manual driving conditions.

Keywords:

• Automated driving
• risk perception
• empirical study

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work is supported by National key research and development program of China (No. 2021YFF0900602), Natural Science foundation of Zhejiang Province (No. LY22F020014).

Notes on contributors

Wei Xiang

Wei Xiang is an assistant professor in Modern Industrial Design Institute of Zhejiang University. He received his Ph.D. in digital art and design from Zhejiang University. His research interests include human AI interaction and intelligent design.

Yingying Huang

Yingying Huang is now studying in Zhejiang University for Master’s degree. She is currently a master candidate of International Design Institute at Zhejiang University. Her recent research mainly focuses on Human-computer Interaction.