Approaching index based collision avoidance for V2V cooperative systems

Vehicle risk evaluation is a crucial step for collision avoidance algorithm. By applying wireless communication technologies, environment vehicles can be sensed and considered as potential objects. This paper explores the definition, algorithm and applications of approaching index (AI). First, by taking the advantage of communication, trajectory cross point (TCP) can be derived through calculating vehicle future trajectories, and helps consider the neighbor vehicles as potential objects, which is useful under complicated traffic scenes. Secondly, based on TCP, the definition and algorithm of AI is built. AI is very important for selecting collision object from potential collision objects. Then, hardware in the loop (HIL) tests with different traffic conditions were conducted. Test data confirms the effectiveness of AI in different scenes although subjected to interference. Driver can gain more time to avoid oncoming collision by taking the advantage of AI. Finally, the limitations and future work of AI are discussed.