A TIME-BASED APPROACH FOR SOLVING THE DYNAMIC PATH PROBLEM IN VANETS – AN EXTENSION OF ANT COLONY OPTIMIZATION

Abstract

Over a decade, Vehicular Adhoc Networks (VANETS) has been evolved and the field of vehicular communication has become a promising area for potential research. The challenges vary from a vehicle to vehicle communication, an indication during the event of a collision, and to enhance the drive and passenger safety. This paper aims at improving the performance of VANETs in terms of capacity, size, topological changes and maintaining the shortest routes. A new scheme termed as Ant Queue Optimization Scheme (AQO) has been introduced by extending the traditional Ant Colony Optimization (ACO). The proposed Ant Queue optimization Scheme combines both proactive and reactive mechanisms. Unlike the ACO, the AQO dynamically makes decision in choosing shortest best route in highly congested areas. Route selection is dynamic at each intersection irrespective of the size of the traffic. Encouraging results have been achieved in using the Ant Queue Optimization even at high vehicular density scenarios.

Keywords

• Ant colony optimization (ACO)
• VANET
• Traffic congestion
• Swarm Intelligence
• Dynamic path problem (DPP)