Driving simulator study for the effects of autonomous vehicles on drivers behaviour under car-following conditions
Authors: Alessandro Calvi, Fabrizio D'Amico, Chiara Ferrante, Gaia Calcaterra
Abstract: Research on autonomous vehicles has shown their high potential for reducing traffic congestion and emissions, as well as improving road accessibility and driving safety. Despite several contributions in the field, few studies have examined the impact that the presence of autonomous vehicles might have on conventional vehicle drivers in the mixed traffic flows that will characterize the transition from conventional vehicles to autonomous vehicles. The overall goal of this study is to provide new insights into the impact of autonomous vehicles on the behavior of following human drivers under car-following conditions. To achieve this goal, a driving simulator study was conducted, and the behavioral changes of forty drivers were examined by comparing their driving performance under three different car-following configurations, where the lead vehicle was: i) a recognizable (Marked) Autonomous Vehicle (AVM); ii) an unrecognizable Autonomous Vehicle (AV); iii) a Conventional Vehicle (CV). Finally, for each car-following configuration, different conditions were examined: ordinary conditions (constant speeds of the leading vehicle) and braking conditions. The results indicated that, under ordinary conditions, poorer safety performance was observed in the CV configuration. Conversely, under braking conditions, the safest performances were demonstrated in the CV configuration, while shorter response times were recorded in the AVM configuration. The study's findings contribute significantly to our understanding of human driving behavior in the car-following state in a mixed traffic flow.
Keywords: Autonomous Vehicle, Driving Simulator, Car-Following, Driving Performance
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