Improving GPS-based vehicle positioning for Intelligent Transportation Systems

Intelligent Transportation Systems (ITS) have emerged to utilize different technologies to enhance the performance and quality of transportation networks. Many applications of ITS need to have a highly accurate location information from the vehicles in a network. The Global Positioning System (GPS) is the most common and accessible technique for vehicle localization. However, conventional localization techniques which mostly rely on GPS technology are not able to provide reliable positioning accuracy in all situations. This paper presents an integrated localization algorithm that exploits all possible data from different resources including GPS, radio-frequency identification, vehicle-to-vehicle and vehicle-to-infrastructure communications, and dead reckoning. A localization algorithm is also introduced which only utilizes those resources that are most useful when several resources are available. A close-to-real-world scenario has been developed to evaluate the performance of the proposed algorithms under different situations. Simulation results show that using the proposed algorithms the vehicles can improve localization accuracy significantly in situations when GPS is weak.