In the video detection system of highway traffic flow

it is difficult to detect vehicles This paper studies nighttime highway traffic vehicles and proposes a robust vehicle detection and tracking algorithm based on optimization theory. The proposed algorithm improves the previous methods for headlight detection and the rules for trajectory tracking. At the same time

it can not only automatically present traffic flow and vehicles speed statistically

but also recognize traffic vehicle event such as jam-packed or driving against the traffic. Experiment results demonstrate the algorithm has lower complexity and better performance than other methods. The detection rate can reach up to 95% or so

robust with low complexity

real-time feature and its detection ratio reaches up to 95% in smooth traffic conditions and 80% in traffic jams.