Exploring the Impact of the Takeover Time for Conditionally Automated Driving Vehicles on Traffic Flow in Highway Merging Area
Qingchao Liu, Jiaqi Liu, Yingfeng Cai, Long Chen
Abstract
Human-machine handover of conditionally automated driving vehicles (CADVs) significantly affects traffic safety. Therefore, a simulation modeling was conducted for the traffic flow mixed with manual driving vehicles, fully automated driving vehicles (FADVs), and CADVs under different takeover times to unravel the impact of CADVs on traffic flow. The results showed that different takeover times significantly affected traffic flow stability. A moderate takeover time allows the driver to complete the takeover quickly with sufficient observation of the surrounding traffic conditions and mitigate the adverse effects of CADVs takeover transition on traffic flow and improve traffic flow safety. Taking moderate takeover time (7s) as the given takeover time, we developed a traffic flow model, and it is found that increasing the total penetration rates of CADVs and FADVs or that of CADVs alone will expand the traffic flow stability area. Moreover, the improving effects of traffic flow stability increase with the value of both penetration rates. This research can be a reference for the safety analysis of heterogeneous traffic flow mixed with CADVs.