Impact of Automated Driving under Virtual Traffic Signals on Traffic Resilience of Urban Road Networks

With the rapid development of autonomous driving technology, it is imperative to study the impact of this technology on the resilience of urban road transportation networks. This study focuses on virtual traffic signal control (VTS) as a representative of autonomous driving technology and proposes a multi-dimensional resilience evaluation system to compare the impacts of three different signal-timing strategies on the resilience of urban traffic networks under various scenarios. Simulation results demonstrate that the average vehicle speed under VTS control is 38.1% and 40.1% higher than the other two control modes, respectively. In addition, the VTS approach significantly reduces delays and minimizes fuel consumption compared to the other two approaches. Moreover, this paper delves into the intrinsic mechanisms by which VTS enhances traffic resilience. It highlights the importance of integrating autonomous driving technology into traffic strategies to achieve carbon emissions reduction and promote sustainable transportation. The network resilience enhanced by VTS enables cities to effectively respond to unexpected events, thereby ensuring smooth traffic flow and safety. This research provides valuable insights into existing knowledge and promotes further research in the field of traffic resilience.