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Influence of conventional driving habits on takeover performance in joystick-controlled autonomous vehicles: A
Shijian He1, Xinyi Liu1, Jie Wang1
1School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410114, China.
Abstract:
Takeover is a critical factor in the safety of autonomous driving. Takeover refers to the action of a human driver assuming control of an autonomous vehicle from its automated driving system. This can occur when the vehicle encounters a situation it cannot handle, when the system requests the driver to take control, or when the driver chooses to intervene for safety or other reasons. This study explored how traditional steering-wheel driving habits affect takeover performance in joystick-controlled autonomous vehicles. We conducted an experiment using a joystick-controlled Dongfeng Sharing-VAN autonomous vehicle in a low-speed campus environment. The participants were divided into three groups based on their driving experience: the individuals who have no licence and no experience (NN Group), the drivers who have licence but not experienced (HN Group), and the drivers who have licence and have been experienced (HH Group), representing varying levels of driving habits. The experiment focused on two takeover tasks: passive takeover and active takeover. We evaluated takeover performance using takeover time and takeover quality as key metrics. The results from the passive takeover task indicated that traditional driving habits had a significant negative impact on takeover performance. The HH Group took 2.65 s longer to complete the task compared to the NN Group, while the HN Group took 3.78 s longer. When we analyzed takeover time in stages, the initial stage showed the most significant difference in takeover time among the three groups. In the active takeover task, driving habits did not significantly affect takeover braking in front of obstacles in a low-speed driving environment. These findings suggest that conventional driving habits can hinder passive takeover in joystick-controlled autonomous vehicles. This insight can be valuable for developing training programs and guidelines for drivers transitioning from conventional to autonomous driving.
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