An Efficient Failure Detection Algorithm for CCTV and Roadside Equipment (RSE)

Travel speed is an important parameter for measuring road traffic. Urban Traffic Information System (UTIS) was developed as a mobile detector for measuring link travel speeds in South Korea. UTIS is mainly a means of collecting enhanced roadway condition information and then broadcasting related traveler information and various alerts back to vehicles. The proposed wireless media is based on UTIS technology operating at 5.725~5.825 GHz in South Korea. Under the UTIS concept, vehicles will be equipped with an UTIS radio, a highly accurate on-board positioning system, an appropriately configured on-board computer to facilitate communications, support various applications, and provide an interface for the driver. This equipment is collectively referred to as the On-Board Equipment (OBE). Vehicles communicate with Roadside Equipment (RSE), which is linked to the specialized UTIS network. RSEs and CCTVs are positioned at major signaled intersections and along major arterial roads. However, RSEs and CCTVs incur errors caused by the lack of probe vehicles on road segments, system failures and etc. In this paper, we suggests a new model for RSE and CCTV failure detection using neural networks to provide accurate link travel speeds and traffic information to the public.