Longitudinal collision mitigation via coordinated braking of multiple vehicles using model predictive control

The vehicular collision can lead to serious casualties and traffic congestions, especially multiple-vehicle collision. Most recent studies mainly focused on collision warning and avoidance strategies for two consecutive vehicles, but only a few on multiple-vehicle situations. This study proposes a coordinated brake control (CBC) strategy for multiple vehicles to minimize the risk of rear-end collision using model predictive control (MPC) framework. The objective is to minimize total impact energy by determining the desired braking force, where the impact energy is defined as the relative kinetic energy for a consecutive pair of vehicles. Under the MPC framework, this problem is further converted to a quadratic programming at each time step for numerical computations. To compare the performance, three other control strategies, i.e. direct brake control (DBC), driver reaction based brake control (DRBC) and linear quadratic regulator (LQR) control are also considered in this paper. The simulation results, in both a typical scenario and a huge number of scenarios under stochastic situations, show that CBC strategy has the best performance among these four strategies. The proposed CBC strategy has the potential to avoid the collision among a group of vehicles, and to mitigate the impact in cases where the collision is unavoidable.