Integrated risk management based automated vehicle following system on inner-city streets

This paper represents model predictive steering control scheme for automated vehicle following system. In contrast to highway, there are some unexpected obstacles such as parked or oncoming vehicles on inner-city streets. Therefore, an automated vehicle following system should consider these obstacles as well as a leading vehicle to guarantee the safety of the system. The model predictive steering control scheme of this paper aims to ensure the safety from unexpected obstacles. The MPC computes the sequence of optimal steering input based on a simplified nonlinear model and the information of leading vehicle's and obstacle's states. At each time step, steering control inputs are optimized under constraints related to vehicle stability and safety. The performance of the proposed algorithm has been investigated via computer simulation conducted using the vehicle dynamic software CARSIM and Matlab/Simulink. Test results show the robust performance of vehicle following on an inner-city street scenario.