Cooperative Adaptive Cruise Control: A Field Experiment

Abstract

In this study, a Human-in-the-Platoon CACC (HiP-CACC) controller is proposed for connected and automated vehicles to “include” human drivers into platooning process. The goal is to form a platoon between automated vehicles and human drivers so that turbulences caused by human drivers could be smoothed out by automated vehicles. Unlike the conventional CACC where only longitudinal control is automated, the proposed HiP-CACC regulates both longitudinally and laterally. In other words, the followers in a HiP-CACC platoon are fully autonomous. The controller is formulated as a model predictive control (MPC) solved by Chang-Hu's method. The technology has the following advantages: i) take advantage of human drivers' perception to enable conditional full autonomy; ii) accommodate actuator delay in system dynamics to improve actuator control accuracy; iii) automate both longitudinally and laterally; iv) ensure string stability in partially connected and automated vehicles environment. Field tests were conducted to verify the effectiveness of the proposed algorithm. The results show that the platoon is able to keep a constant distance gap with maximum 40 cm error longitudinally and maximum 40 cm error laterally.