Analysing Variables Associated With Driver Reaction During the Transition From Automated to Manual Driving

With the increasing development and implementation of Automated Driving Systems (ADS), understanding driver reactions during the transition from automated to manual driving has become a critical research area. The transition from automated to manual driving is a challenging task that requires the driver to take over control of the ADS-equipped vehicle in a safe and timely manner. Previous studies have identified various variables associated with driver reactions, but a comprehensive classification is lacking. This paper addresses this gap by systematically identifying and classifying the independent and dependent variables that affect drivers’ reactions in ADS-equipped vehicles during the transition from automated to manual driving. This is achieved through an extensive review of major findings in the designs of driving simulator experiments in this field. Additionally, an analysis of five hundred on-road collision reports from 2014 to 2023 involving ADS-equipped test vehicles is conducted. Finally, a comprehensive overview of the identified dependent and independent variables from both studies, along with their synergies and shortcomings, is presented. The variables are categorised and mapped, highlighting key research gaps. The main research gaps were identified by comparing the variables extracted from reviewed papers with the statistical analysis in the DMV reports. Some gaps include the need for incorporating real-world scenarios into experiments, driver-initiated take-over requests and applying physiological measures to assess driver-centric factors. This detailed identification and classification of variables assists in designing a range of future experimental scenarios to assess drivers’ reactions to the transition of control in ADS-equipped vehicles.