A Study on the Traffic Predictive Cruise Control Strategy With Downstream Traffic Information

Abstract

A vehicle traffic predictive cruise control (TPCC) system, responding to the change of downstream traffic situation, has been proposed to improve traffic operation and the fuel efficiency of vehicle based on the asymmetric traffic theory. The proposed predictive cruise control system consists of four parts: 1) deceleration-based safety surrogate measure (DSSM); 2) single-vehicle control algorithm; 3) multivehicle safety measurement (Co-DSSM); and 4) TPCC. The single-vehicle control algorithm basically decides the acceleration action based on estimated safety state between a subject vehicle and the immediate preceding vehicle, and the control strategy is determined by asymmetric driving behavior. Then, TPCC adjusts the amount of acceleration based on the Co-DSSM from multiple downstream vehicles, which contains the information on future traffic condition of the subject vehicle. A simulation using the real vehicle trajectories from the Next Generation Simulation (NGSIM) data validates the proposed TPCC system, and we compare the results with the real vehicles' car-following patterns. It is found that the proposed TPCC system can contribute to both the energy consumption and traffic flow operation by obtaining a higher level of traffic stability. Such results are due to the effects of suppressing the shockwave from downstream traffic and removing the unnecessary deceleration and acceleration actions.