城市智能交通系统拥堵规避算法的研究与实现  

RESEARCH AND REALIZATION OF CITY INTELLIGENT TRANSPORTATION TECHNOLOGY AND AVOIDANCE OF TRAFFIC CONGESTION

作　　者：苏锦[1] 王震 SU Jin;WANG Zhen(Nanyang Institute of Technology,Nanyang 473004,China;Huizhou University,Huizhou 516007,China)

机构地区：[1]南阳理工学院,河南南阳473004 [2]惠州学院,广东惠州516007

出　　处：《南阳理工学院学报》2018年第2期40-44,66,共6页Journal of Nanyang Institute of Technology

摘　　要：智能交通系统(Intelligent Transportation System,ITS)能够提高交通系统的安全性和效率。本文提出了一个用于解决城市交通拥堵预测问题的车联网模型。结合多属性决策方法和理想值逼近技术,基于蚁群优化算法提出了一个基于4个参数的多属性蚁群优化算法(Multimetrics Ant Colony Optimization algorithm,MACO)用来进行路径规划。该算法提高交通系统中行驶在道路上车辆的平均速度并能够减少停车次数和等待时间,有效避免了交通拥堵。Intelligent Transportation System（ ITS） can improve the safety,efficiency,and convenience of traffic systems. In this paper,we first propose a model of vehicular network in urban area for tackling the problems of traffic congestion prediction. With this model,we extend the Multimetrics Ant Colony Optimization algorithm（ MACO） to implement the prediction and avoidance of traffic congestion. Our algorithm indicate that the proposed algorithm can improve the transportation system by increasing the average speed of each vehicle and by reducing both the average stopping and waiting times for those vehicles while they are on the road.

关 键 词：实时路径规划 多属性蚁群优化算法 交通拥堵规避算法 车联网 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]