Collision Avoidance of Autonomous Driving at Low Speed in the Near Field of Vehicle

Abstract

This paper aims to propose a new idea for realizing low-power-consumption, real-time, microcontroller-based, redundant embedded collision avoidance systems in autonomous driving applications. When operating a fully automated vehicle, the vehicle generates a driving trajectory based on the global route to the destination. The car must follow the generated driving path. It is essential to ensure the safety of this path by checking that it is collision-free. The goal of our low-level embedded collision avoidance system is to guarantee the safety of the path. After defining the driving path area associated with the generating path and the safe monitoring distance, the system can monitor the vehicle's defined Keep-Out-Area (KOA) by using 3D Light Detection and Ranging (LiDAR) sensor. Considering the relatively limited computing power of the microcontroller, the KOA is calculated offline and stored in a look-up table (LUT). This paper also introduces an experimental hardware platform based on the proposed system concept. This platform can facilitate the testing of various collision avoidance algorithms. Moreover, we also identify the challenges, such as false positives and deviation from the actual driving path.