Model Predictive Enhanced Adaptive Cruise Control for Multiple Driving Situations

This paper presents an Enhanced Adaptive Cruise Control (EACC) framework that can work in different modes according to the forward targets. The EACC system, which was proposed in this paper, is based on a unified model and can achieve speed tracking, stop & go and autonomous emergency braking (AEB). Notably, speed tracking does not require a real preceding vehicle, a virtual vehicle can be set in front of the EACC vehicle. The mathematical method of setting the virtual preceding vehicle and the switching logic between the different working modes of the EACC system were given. Employing a constraints softening method to avoid computing infeasibility, an optimal control law is numerically calculated using the CVXGEN solver. Finally, real vehicle tests show that the EACC framework provides significant benefits in terms of speed-tracking capability, safety and comfort requirements while satisfying driver desired car following characteristics for different driving situations.