A preemptive hybrid ant particle optimization (HAPO-P) algorithm for smart transportation

Due to exponential increase in number of vehicles, people are facing the problem of extreme congestion in developing countries like India. This congestion wastes the precious time and fuel in unnecessary waiting either at the intersections due to the presence of traffic signals or during the drive on the congested routes. This paper proposes a novel preemptive Hybrid Ant Particle Optimization (HAPO-P) algorithm to minimize overall journey time in VANETs by reducing both waiting at intersections and avoiding the congestion enroute. The aim is to select a path in peak hours with minimum waiting at the intersections with least possible congestion enroute. Here the best path is selected using HAPO algorithm and green light allocation is done by the preemptive algorithm. The proposed HAPO-P algorithm combines the benefits provided by both HAPO algorithm and preemptive algorithm with actual road conditions. The performance of the HAPO-P algorithm is tested on a map of North-West Delhi, India. The result obtained after applying the proposed HAPO-P significantly reduces the overall journey time with the growth in traffic over the existing MACO with assumption; both MACO and HAPO algorithms with actual road conditions used independently.