ABSTRACT
A new kind of ad hoc network is hitting the streets: Vehicular ad hoc networks (VANETs).1-4 In these networks, vehicles communicate with each other and, possibly, with roadside infrastructure to provide a long list of applications varying from tra c safety to driver assistance and Internet access. In these networks, real-time position knowledge of nodes is an assumption made by most protocols, algorithms, and applications. is is a reasonable assumption, because GPS receivers can be easily installed in vehicles, a number of which already come with this technology. However, as VANETs advance into critical areas and become more dependent on localization systems, some undesirable problems with GPS begin to surface, including not always being available or not being robust enough for some applications. For this reason, a number of other localization techniques such as dead reckoning, cellular localization, and image/video localization, to cite a few, have been used in VANETs to overcome such limitations. A common factor in all these cases is the possibility of using data fusion techniques to compute an accurate vehicle position, creating a
new paradigm for localization where di erent localization techniques are combined into a single solution that is more robust and precise than the individual approaches. In this chapter, we further discuss this subject, describe each localization technique, and show how they can be combined by means of data fusion techniques.
