On‐road multi‐vehicle tracking algorithm based on an improved particle filter

Abstract

Forward collision avoidance systems have shown to be a particularly effective crash-avoidance technology. Multi-vehicle tracking capabilities play an important role in the real-world performance and effectiveness of such systems. In order to effectively and accurately track vehicles in a moving platform and in complicated road environments, the authors proposed a multi-vehicle tracking algorithm based on an improved particle filter. First, the authors used a vehicle disappearance detection and handling mechanism based on the normalised area of the minimum circumscribed rectangle of particle distributions. This mechanism is used to verify whether a new target is a vehicle and can also handle the vehicle exit during the tracking phase. Next, an improved particle filter-based framework, which includes a new process dynamical distribution, allowed for multi-vehicle tracking capabilities was used for vehicle tracking. Finally, an effective occlusion detection and handling mechanism was used to address the significant occlusion between vehicles. The combination of these added improvements in the algorithm results in the enhancement of the vehicle tracking rate in a variety of challenging conditions. Experimental tests carried out from different datasets show excellent performance in multi-vehicle tracking, in terms of accuracy in complex traffic situations and under different lighting conditions.