Combining RFID and Image-Based Vehicle Identification Data to Detect Illegal Vehicles

Effective Road law enforcement is a vital part of transportation systems. Escalating traffic congestion and widespread illegal road usage pose fresh hurdles for road law enforcement systems. An intelligent system that aims to reduce illegal road use must enable immediate intervention on a tactical level without disrupting the flow of legal vehicles. To achieve a fast tactical response, strategic-level information, such as location and identity, must ensure law enforcement officials are in the right place at the right time. This paper presents a system that equips authorities with the correct information to act against illegal road users while maintaining normal traffic flow. The proposed system improves upon existing solutions by combining Radio Frequency Identification (RFID) and Computer Vision (CV) data to detect and identify illegal vehicles. The authorities can leverage this information to remove illegal vehicles from the road without affecting the legal road user's experience. This paper is the first to quantify the performance of this concept based on real-world performance criteria through practical experiments. Our work verifies that the theoretical requirements to read a combination of data fields that enable accurate vehicle identification of vehicles traveling at high speeds can be achieved in practice for various scenarios.