Abstract: Large amount of money is lost to manipulate traffic system or road congestion worldwide every year. By providing the travel time for a specic road, traffic congestion can be minimized. Many approaches has been taken such Automatic Vehicle Identication, Loop Detectors etc. But this methods are costly. In this paper, A system is proposed that provides traffic intensity level information to the user according to recent traffic data analysis. To minimize the traffic congestion, the research proposal is to use adaptive concept in this arena. This proposal develops a structure of a simple vehicle device which is installed on a vehicle to trace, data will be send to server using this device and provide information of traffic intensity using proposed algorithms. This algorithm can estimate travel times in a road network accurately. Further, the aim of this research approach is to present a collective intelligence approach to help solving path planning optimization problems and find the shortest path to solve transportation problem to optimize the time. This research approach concentration on Particle Swarm Optimization (PSO), Genetic Algorithms (GA), Ant Colony Optimization and Dijkstra Algorithm for finding the best path within several path. The main objective of this research approach is to proposal an efficient hybrid algorithm that takes prot of the benefits of PSO, GA, ACO and Dijkstra approaches for the sake of capitalize on the chance to nd the best path under real-time environment.