An efficient multi‐sensor fusion and tracking protocol in a vehicle‐road collaborative system

Abstract

Nowadays, driving safety has become an important topic in the field of intelligent driving. The key step in the intelligent transportation system (ITS) is to detect and track the vehicles on the road through various sensors equipped on the vehicle. While putting the sensors aside the road can have benefits in the vehicle-road collaborative scenario. In this paper, an efficient and applicable multi-sensor fusion protocol for a vehicle-road collaborative system is proposed where roadside units (RSUs) are equipped with cameras and radars. To fully use the history information and the multi-source heterogeneous sensing data to improve the reliability of multi-sensor fusion, a Bayesian-based two-layer fusion scheme is further proposed. Moreover, the efficiency and robustness of the proposed scheme are evaluated in a real highway environment in Changsha, China.