SmartRoad: A New Approach to Law Enforcement in Dense Traffic Environments

Abstract

Road transport law enforcement is facing new challenges against the background of increasingly congested traffic conditions. An ideal law enforcement system must enable authorities to detect, identify and act against illegal road users with minimum disruption of normal traffic flows. This paper presents a new concept for in-traffic law enforcement that overcomes many of the limitations of existing approaches. The SmartRoad system combines the best abilities of imaging, automated identification, radio communications and artificial intelligence technologies to identify not only vehicles with anomalous identities but also anomalous behavior displayed by legal vehicles. The proposed system utilizes the combined abilities of traffic cameras and RFID to firstly detect vehicles and subsequently verify their true identity. Such information is passed downstream to enable the removal of such vehicles from the road with minimal disruption to other road users. As more historical statistics representing normal and abnormal road usage are collected the system will learn from such data in order to improve its ability to reduce both false positives and negatives. Successful deployment of the SmartRoad concept should therefore result in a self-regulating traffic system that discourages unacceptable road use and that adapts itself to new forms of road behavior.