Identification and location tracking of drivers and vehicles can be effectively realized by utilizing license plate recognition data and WIFI hotspot data. However, matching collected vehicles and vehicle driver data is challenging because the process has to cope with multiple data sources. In response to this problem, we propose an association analysis algorithm to efficiently solve the Person-Vehicle matching problem in a parallel manner. Experiments in Yunnan Province show that the method effectively solves the problem of matching drivers and vehicles, and has achieved good results. The research provides valuable insights on violation identification of vehicles.

CICTP