Multi-objective optimal route search for road networks by dynamic programming

One of the most important functions of car navigation systems is to assist drivers to travel to destinations. Minimum traveling distance or time is often considered to find the optimal route to the destination. However, when searching for the optimal route, it is essential to consider userspsila preference in the search. In this paper, we propose a new dynamic programming method to find the optimal route to the destination considering multiple criteria. The proposed method is an extension of our previous route search algorithm, Q method. In this study, we will define the Q values for the pair of road sections. A general index will be introduced, which takes multiple criteria into consideration. Q values are updated based on the local information available including other Q values at the adjacent road sections. When the traveling time changes, we use the already obtained Q values to find the new optional route. We applied the proposed method to a very simple artificial road network. Simulation results show that we can find better routes when considering multiple criteria compared to the optimization using the traveling time only.