Simulation research on emergency path planning of an active collision avoidance system combined with longitudinal control for an autonomous vehicle

Abstract

Autonomous vehicle technology is greatly valued nowadays, and an active collision avoidance system is one of the key parts for autonomous driving. This study presents a comprehensive architecture of an active collision avoidance system for an autonomous vehicle, which is integrated with a decision-making module, a path-planning module, a lateral-path-following module and a fuzzy adaptive following module (longitudinal motion) to deal with potential hazards on a straight road or a curved road. In order to make the planned path for overtaking manoeuvres safer, an improved harmonic velocity potential approach for path planning is presented, which innovatively enhances the effect of an obstacle potential on a road by adding a scale term, so that it can generate a smooth path for a vehicle-overtaking manoeuvre. All the potentials which are used for vehicle lane keeping or lane changing are well designed. The lateral-path-following module is based on the constrained linear model predictive control approach, which ensures that the host vehicle can follow the planned path precisely. Furthermore, when the overtaking manoeuvre is not suitable, the fuzzy adaptive following module is utilized to ensure that the host vehicle can adaptively keep a safe distance from the preceding vehicle. Tactical decisions, such as overtaking, accelerating or decelerating, are determined by the decision-making module. Finally, several typical scenarios with low traffic on a straight road or a curved road are simulated to verify the effectiveness and the feasibility of the active collision avoidance system. The simulation results show that the host vehicle can make a successful collision avoidance manoeuvre without the intervention of a human driver in different situations.