Signal processing requirements and uncertainty modeling issues in cooperative vehicular positioning

Accurate and reliable vehicle localization is a key component to numerous applications, including active vehicle safety systems, real time estimation of traffic conditions, and high occupancy tolling. Up to now, most of the localization techniques rely on a given set of sensors embedded in a single vehicle. In this paper, we survey the issues considered in designing collaborative methods for localizing vehicles on roads using information coming from neighbor vehicles as well as from fixed infrastructures. We will in particular examine the signal processing issues and uncertainty modeling in estimating the relative ranges and angles of vehicles and the vehicles' position from noisy measurements.