Transport System, The Optimal Path Selection Algorithm

In recent years, Intelligent Transportation System (ITS) has been paid more and more attention. It was given birth to in the background of contemporary science and technology fully developed which seeks to introduce advanced computer technology, communication technology, database technology and Artifical Intelligence to transpotation so as to solve the traffic congestion, ensure the the safety and improve the using rate of traffic network. ITS involves many aspects of traffic field. And in these aspects, one important application is the choosing of the optimal path.Before starting off, the users are interested in how to find an optimal path from the start point to end point. The traditional optimal algorithms were represented by Dijkstra algorithm. These are all greedy which are static local optimal algorithm and have typical local optimization problem. At present, the scale of real traffic data is huge. And it should be loaded in advance of algorithm carried out into the path chosen. Obviously, this cannot reflect the actual continuous situation of traffic on path chosen. Ant Colony Algorithm is a new bionic simulation algorithm. It has the capibility in simulating colony cooperation and finding a shortest path from nest to food, which could respond dynamically to external affection in the routing search process. So it has infinite feasibility and flexibility in the optimal path chosen of traffic.This paper analysised the current problem in traffic path chosen generally, presented the expression and storge structure in computer of traffic data, discussed and researched the traditional algorithm of current optimal path chosen, which contained Dijkstra Algorithm, Floyd Algorithm and A* Algorithm. And the algorithm's advantage and disadvantage was discussed from basic idea, algorithm process, idiographic implement and algorithm analyse. Combined these several traditional optimal path algorithms and ant foraging behavior, a new algorithm was introduced, that was Ant Colony Algorithm (ACA). And then further researched the ACA's basic principles and the application and implementation process of traffic optimal path chosen. Through large numbers of different experience, the best experimental parameters' combination of ACA was made certain. At last, carried out data simulation and compared them with classicoptimal path chosen algorithm's result.Through this paper's research, we confirmed that using ACA as the optimal path chosen algorithm could exert the simulated algorithm's predominance of global search, improve the rate of path chosen, reduce the time use in path selection in the situation of big quantity of traffic data and complicated traffic status. And this algorithm will be helpful in achieving the dynamic optimal path selection process.