Adaptive route selection for dynamic route guidance system based on fuzzy-neural approaches

One functionality of an in-vehicle navigation system is route planning. Given a set of origin-destination (O/D) pairs, there could be many possible routes for a driver. A useful routing system should have the capability to support the driver effectively in deciding on an optimum route to his preference. The objective of this work is to model the driver behavior in the area of route selection. In particular, the research focuses on an optimum route search function in a typical in-car navigation system or dynamic route guidance (DRG) system. In this work, we want to emphasize the need to orientate the route selection method on the driver's preference. Each feasible route has a set of attributes. A fuzzy-neural (FN) approach is used to represent the correlation of the attributes with the driver's route selection. A recommendation or route ranking can be provided to the driver. Based on a training of the FN net on the driver's choice, the route selection function can be made adaptive to the decision making of the driver.