Background:
Emergency vehicles required a quick clearance so as to reach the destination with minimum delay and the human life could be saved. Emergency vehicle required a dedicated path for clearance. The dedicated path creates a chaos by blocking the entire route for others vehicles and it is not always possible to create a dedicated path. So there is an imperative need for a smart road navigation system which adapts to the traffic congestion in real-time velocity of vehicle, count of vehicle, number of lanes and distance from source to destination.
Objective:
The objective of this paper is to find an optimal route for providing a least congested optimal route for emergency vehicle with least delay considering various issues such as congestion, numbers of vehicles, average traffic flow on the roads and width of the lane between source and destination.
Proposed approach:
Real-time traffic data like number of vehicles, velocity of the vehicles, and the width of the road and distance of the route are used to determine the congestion factor on all possible route. Congestion factor is used for finding the shortest route to requesting emergency vehicle.
Result:
Experimental results establish that the travel time of a vehicle is reduced by approximately 26%, when the vehicle uses the optimized route. This is beneficial for any emergency vehicle as the optimal path is provided on a real-time basis.
Conclusion:
This research work proposes an analytical approach that provides the least congested optimal route on-demand based on real-time traffic.
Real-time traffic congestion detection based on frame difference function and virtual loop
