Collision-Free Path Planning for Automated Vehicles Risk Assessment via Predictive Occupancy Map

Abstract

Vehicle collision avoidance system (CAS) is a control system that can guide the vehicle into a collision-free safe region in the presence of other objects on road. Common CAS functions, such as forward-collision warning and automatic emergency braking, have recently been developed and equipped on production vehicles. However, these CASs focus on mitigating or avoiding potential crashes with the preceding cars and objects. They are not effective for crash scenarios with vehicles from the rear-end or lateral directions. This paper proposes a novel collision avoidance system that will provide the vehicle with all-around (360-degree) collision avoidance capability. A risk evaluation model is developed to calculate potential risk levels by considering surrounding vehicles (according to their relative positions, velocities, and accelerations) and using a predictive occupancy map (POM). By using the POM, the safest path with the minimum risk values is chosen from 12 acceleration-based trajectory directions. The global optimal trajectory is then planned using the optimal rapidly exploring random tree (RRT*) algorithm. The planned vehicle motion profile is generated as the reference for future control. Simulation results show that the developed POM-based CAS demonstrates effective operations to mitigate the potential crashes in both lateral and rear-end crash scenarios.