Vision-based turning movement counting at intersections by cooperating zone and trajectory comparison modules

This work presents a vision-based vehicle tracking system with an improved method for automatically obtaining turning movement counts at intersections. Improved accuracy is obtained for intersections of varying difficulty through cooperation between complimentary counting modules. When vehicle tracking is robust, a typical zone comparison module quickly accounts for predefined image regions. When vehicle tracking is broken due to occlusion or noise, a trajectory comparison module utilizing the least common subsequence distance is able to count the broken trajectories using the typical scene paths. Experimental evaluations during evening peak hours at two different intersections show an 15% average improvement at two intersections where the trajectory comparison module is in use 22% of time. Finally, counts of five working days are compared for another intersection in 15 minute intervals to highlight the system's operational utility for turning behavior analysis at high temporal resolution.