Cooperative Shock Waves Mitigation in Mixed Traffic Flow Environment

Human driver behavior strongly influences traffic flow by increasing the spread of shock waves in a downstream direction. This paper addresses the problem of traffic congestion mitigation in a mixed scenario composed of connected human-driven and autonomous vehicles. The control protocol, driving the longitudinal motion of the autonomous vehicles, is designed for damping down traffic waves. The effectiveness of the strategy, and ability to cope with multiple and time-varying delays originated by the non-ideal wireless communication among connected vehicles, is both analytically and numerically analyzed. The asymptotic stability of the algorithm is mathematically proved by leveraging a Lyapunov-Krasovskii functional, while the head-to-tail stability tool is exploited for the tuning of the control gains. The performance of the control strategy is disclosed by using hardware-in-the-loop real-time simulation for an exemplary pattern of three vehicles. The effectiveness of the proposed cooperative strategy in longer queues of vehicles is, instead, investigated through PLEXE, an inter-vehicular communication and mobility simulator that includes features for autonomous vehicles as well as for the realistic emulation of the IEEE 802.11p standard. The results confirm the robustness of the approach and its ability in damping disturbances and mitigating stop-and-go effects according to the theoretical derivation