A re-optimization dynamic shortest path algorithm for vehicle navigation

The traffic congestion changes over time in the real transportation network, and the vehicle navigation is a real-time processing. Both the accuracy and time performance of navigation algorithm are important. To respond rapidly to transportation network changes, this paper proposes two new dynamic shortest path algorithms based on the re-optimization method. The algorithms take full advantage of the previous search results, thus they take relatively few computing time to obtain the optimal solution. Experimental results demonstrate that the proposed algorithms can be applied to vehicle navigation in the transportation network with dynamic variation of the travel times on arcs and runs much faster than the traditional Dijkstra algorithm.