Abstract
Normally, LBS (Location Based Service) systems provide valuable information like the nearest gas station, ATMs, hospitals, pharmacies, hotels, restaurants, etc. It is difficult to collect real-time traffic data, from vehicles or roadside sensors, to compute the travel time between two locations. Vehicle routing on a road network is a combinatorial NP- hard optimization problem and it is difficult to find an optimal solution. Here, we propose an optimal path prediction method based on distance and travel time. The shortest distance between two locations is static. The actual travel time in each road segment between these two locations can be predicted by taking midnight travel time. The current travel time for this distance will be varied depending on different scenarios and hence we are using the G-Tree indexing method (K shortest path with scenarios). Congestion on these road segments will be calculated using actual travel time and current travel time. Next, we will use ACO (Ant Colony optimization) to find an optimum route
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