Cooperative Adaptive Cruise Control for String Stable Mixed Traffic: Benchmark and Human-Centered Design

Abstract

With the emergence of vehicle-to-vehicle communication technology, cooperative adaptive cruise control (CACC) cars can be expected in the near future. In this paper, novel criteria for string stability are proposed for mixed traffic platoons that consist of both automated and manual driving cars. A mixed traffic string stability definition is proposed to guarantee the boundedness of the motion states fluctuation upstream as well as the safety of the entire platoon. With proper arrangements of the platoon sequence as well as mild restrictions on the leading car’s velocity overshoot, the proposed mixed traffic string stability can be realized via some suitable controller design for the automated cars. The benchmark controller with feedback and feedforward path is first used to verify the above results with rigorous proof. Furthermore, a human-centered CACC system is designed to improve both physical and psychological comfort of a driver under the guarantee of mixed traffic string stability. The action-point car-following model is adapted to quantify the driver’s psychological comfort in combination with the quantification of physical comfort based on jerk. A model predictive control-like blending ratio controller is developed to obtain the optimal time headway in the feedback controller for tradeoffs among driver comfort, fuel efficiency, and traffic throughput under string stability constraints. Finally, a seven-car CACC mixed traffic platoon scenario is simulated. Compared with the benchmark CACC controller design, the human-centered CACC design is shown to largely improve the driving comfort.