基于鱼群算法的城市交通仿真

Navigation system of city for car based on fish characteristic

良好的城市车载导航将对城市发展具有良好的经济效益和社会效应。本文通过仿生学的鱼群算法,建立理论模型,寻求城市道路交通的最优化解决方案。在前人的基础上,提出了基于局部分隔鱼群算法的城市车载导航系统(PBFS)模型,对城市交通进行了理论建模,实现了一种新的新型寻优策略。仿真效果表明,该方法是可行的,具有良好的寻优效果,能有效的减少交通阻塞,提高城市道路的整体效率,具有广阔的应用前景。

Transportation is one of the most important facts influence in economic performance for cities.The good navigation of city for car will produce the very positive influence to the economic performance in city.Fish —swarm Algorithm is a new optimizing method which has the excellent result goodly.According to the Characteristic of fish swarm,this paper puts forward for the very first time the part boxs off for fish—swarm algorithm （PBFS）,and set up the module for the city transportation system according to PBFS.The imitation result shows that it is viable to effectively decrease traffic jam,and increase the efficiency of the whole of the city roads.As result,there is the very vast and applied foreground for PBFS.