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Route Planning Heuristic Approach Each result shown in the graph is the average time needed to get the shortest path for 10 real route planning results in which there are more than 65 charging stations in the graph and the test was tested on Samsung Tab S2 T-815 with Android OS version of 6.0.1. 1000000 100000 10000 1000 100 10 1 Floyd-Warshall Dijkstra Floyd-Warshall vs Dijkstra 5860 15120 225333 number of edges in graph Figure 6.7: Route planning with 3 different states of charge. In Fig. 6.7 is on the left side logarithmic scale. We can see that the biggest difference rises up with bigger number of edges and the Floyd-Warshall algorithm is inappropriate for the third situation of accuracy. The result time using Floyd-Warshall algorithm in third situation takes several minutes to get the result so in the final application I use only Dijkstra algorithm with priority queue. 6.11 Heuristic Approach A heuristic function can be used in this problematics, especially if there is a need to reduce the number of queries to Google servers. From the principle of route planning, I can consider in which direction, I mean by angle, is the destination and I do not have to consider using stations which are in the opposite direction, and that is true for the direction from the destination to the start position. In the following Fig. 6.8 is described this aforementioned thought. 33 time (ms)PDF Image | Driving Range Estimation and Trajectory Planning
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