Leading Cruise Control in Mixed Traffic Flow: System Modeling, Controllability, and String Stability

Connected and autonomous vehicles (CAVs) have great potential to improve road transportation systems. Most existing strategies for CAVs' longitudinal control focus on downstream traffic conditions, but neglect the impact of behaviors upstream flow. In this paper, we introduce a notion Leading Cruise Control (LCC), in which CAV maintains car-following operations adapting states its preceding vehicles, also aims lead motion following vehicles. Specifically, by controlling CAV, LCC attenuate perturbations smooth flow actively. We first present dynamical modeling LCC, with three fundamental scenarios: car-following, free-driving, Control. Then, analysis controllability, observability, head-to-tail string stability reveals feasibility improving mixed performance. Extensive numerical studies validate that capability CAVs dissipating is further strengthened when incorporating information behind into CAV's control.