Multidimensional Evaluation for Driver’s Takeover Performance of Autonomous Vehicles Performance

Due to various limitations such as technological capabilities, condi- tionally automated driving vehicles require driver intervention when they exceed the operational design domain (ODD) of their automated driving functions. The safety, stability, and comfort of the takeover process are collectively referred to as takeover performance, a topic that has garnered widespread attention among researchers. Based on an analysis of existing research on takeover performance, it was found that the evaluation methods for driver takeover performance are not comprehensive. Therefore, this study constructs a system of evaluation indicators for takeover performance based on multi-source data extraction of original evalu- ation indicators. This has significant implications for optimizing takeover request strategies in autonomous driving scenarios. The specific research content includes: (1) Designing and conducting takeover experiments based on driving simulators to simulate the takeover process of automated driving under different driver states and takeover request times; (2) Extracting original evaluation indicators of driver takeover process from multi-source data, including subjective situational awareness, subjective task load, takeover responsiveness, takeover effective response time, takeover stability, and takeover safety; (3) Establishing a system of evaluation indicators for takeover performance based on factor analysis and analyzing the differences in driver takeover performance from multiple dimensions under the influence of different factors.