Dijkstra beats genetic algorithm: Integrating uncomfortable intersection-turns to subjectively optimal route selection

Route selection is one of the most important problems for a car navigation system. Given a pair of origin and destination, there are many possible routes. Most current car navigation systems propose the shortest path from the origin to the destination. Selecting the shortest path is not a hard problem, but the shortest path is not always what the user wants; what the user really wants to have is the most comfortable route for him or her to drive. In other words, the driver wants to have a car navigation system to propose the subjectively optimal route for him or her. Finding such a route requires enumerating all the possible routes, and is known as a NP-complete problem. In order to reduce computational complexity, we employed a GA to find a (subjectively) quasi-optimal route for the driver. In the previous paper, we reported our attempt to integrate uncomfortable-turns to our GA-based route selection algorithm. Even though GA provided a quasi-optimal route in most cases and certainly much faster than exhaustive search, we have found that the classical Dijkstra algorithm can be used to find subjectively the most comfortable route by changing the data structure. In this paper, we show how the data structure that represents routes can be modified to assist Dijkstra´s algorithm to find subjectively optimal driving route. The numerical experiments demonstrate the feasibility of our route selection based on Dijkstra algorithm with extended data structure.