A Research In Dynamic Traffic Assignment And Route Guide System Based On Ant Colony Algorithm

Dynamic traffic assignment and route guide is the two core content of Intelligent Transportation System, How to assigning the traffic to route and optimize the route guiding system effectively is an important project in transportation research . With the spreading of route net and the increasing traffic vehicle, Transportation became full , At the same time ,the traffic jam became seriously. Assigning and guiding the traffic became more and more important in traffic control system. Almost Academic circles meet the complex problem of optimizing on researching, how to solving these optimizing problem with efficiency become the key Target.Used to traffic assignment module almost belong to static traffic module that didn't consider the impact of the changing traffic information, That lead to the module can't reflect with the road information . This article intends to add the traffic information to the Dynamic traffic assignment and route guide module. And expect through using the information to influence the driver'route choice to gain a better effective.This article's main work and research result list below:(1)Improved the basic ant colony algorithm and advanced the ant colony algorithm that based on the average of route. That is mainly change the way of information in adaptation., Improving speed of searching time.(2)Applying the developed algorithm to the dynamic traffic assignment model with real-time information and obtain a good result.(3)Applying the real-time information to the route guide system, and searching best solution with the ant colony algorithm that based on the average of route. And obtained a good result in searching the route.At the end, this article imitated the primary route of changsha city, The simulation proved that this algorithm can react with the real-time traffic information, dynamic adapting the route information, and improved the classic dynamic traffic assignment model and the route guide algorithm, and promoted the speed of finding the model's solution.