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《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:

期数:

2019年02期

页码:

30-32

栏目:

出版日期:

2019-04-15

文章信息/Info

Title:

Intelligent transportation system path planning based on improved ant colony algorithm

作者:

赵艳东; 张申申

青岛科技大学 电子工程及自动化学院，山东 青岛 266100

Author(s):

ZHAO Yandong; ZHANG Shenshen

Qingdao University of Science and Technology，Electronic Engineering and Automation College，Shandong Qingdao 266100,China）

关键词:

智能交通系统; 蚁群算法; 路径寻优

Keywords:

intelligent transportation system; ant colony algorithm; path optimization

分类号:

TN391

DOI:

1000-0682(2019)02-0000-00

文献标志码:

A

摘要:

社会的快速发展，带来了越来越严重的交通问题，长期以来导致环境污染，能源浪费，专家提出智能交通系统能够有效的改善交通问题，而路径寻优算法又是其中的关键点之一，但是原来研究的算法往往只是针对路径长短，没有考虑实际的路况和当时的情景。该文结合传统蚁群算法，模拟现实的路况和情景改进算法，并进行仿真和数据分析。仿真实验结果显示，改进蚁群算法在动态路径规划中具有良好的效果。

Abstract:

The rapid development of society has brought more and more serious traffic problems. It has caused environmental pollution and wasted energy for a long time. Experts suggest that intelligent transportation systems can effectively improve traffic problems, and path optimization algorithms are one of the key points. However, the original research algorithm is often only for the length of the path, without considering the actual situation and the situation at that time. In this paper, the traditional ant colony algorithm is used to simulate the realistic road conditions and scene improvement algorithms, and simulation and data analysis are performed. The simulation results show that the improved ant colony algorithm has a good effect in dynamic path planning.

参考文献/References:

[1] 陆化普,李瑞敏.城市智能交通系统的发展现状与趋势[J].工程研究-跨学科视野中的工程,2014,6(01):6-19.

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备注/Memo

备注/Memo:

收稿日期：2018-07-12

作者简介：赵艳东(1976)，女，山东青岛人，博士，副教授，主要研究方向为时滞、非线性系统最优控制，智能控制理论及应用。

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更新日期/Last Update: 2019-04-15