Analyzing Take-over Event of Autonomous Vehicle for Driving Safety Evaluation

Worldwide efforts have been made to conduct various demonstration projects on real roads to accelerate the commercialization of autonomous vehicles (AVs). However, traffic safety issues associated with mixed traffic streams need to be systematically addressed to facilitate the adoption of AVs. The objective of this study is to evaluate driving safety of AV based on analyzing real-world AV data obtained from a real-world autonomous mobility testbed in Seoul, Korea. In addition, this study attempts to identify potential risk factors including road infrastructure and traffic conditions. Behavior characteristics and driving safety were evaluated using data collected from AVs that drove on actual roads in autonomous driving (AD) mode and manual driving (MD) mode. This study also proposed a driving risk indicator (DRI) for autonomous vehicle based on take-over triggered events to evaluate driving safety. Potential risk factors were identified by modeling a binomial logistic regression using the road facility characteristics data. Statistically significant independent variables were defined as potential risk factors. 'Illegal parking', 'dedicated turning lanes', and ‘turning movements at the intersection' were identified as potential risk factors in the AV. The results of this study are expected to provide a foundation for the improvement of infrastructure and to establish policies to enhance traffic safety for AVs.