CASIA OpenIR  > 毕业生  > 博士学位论文
基于自适应动态规划的路口交通信号优化控制
其他题名Traffic Signal Optimal Control based on Adaptive Dynamic Programming
李涛
2009-05-26
学位类型工学博士
中文摘要随着社会、经济的高速发展和城市化进程的加快,城市机动车数辆及道路交通量急剧增加。拥挤的城市交通反过来制约经济的发展和城市化的进程。一个重要的问题是现有的城市交通信号控制系统未充分发挥道路的承载力,而从理论上来说,城市交通信号控制系统是一个复杂巨系统,具有极强的随机性,因此,研究城市交通控制问题具有理论意义和实用价值。 自适应动态规划(ADP)作为一类新的优化控制方法,因其所具有的学习和优化能力,在理论和实际应用方面受到日益重视。本文在理论上研究ADP的新方法,在应用上提出基于ADP的城市路口交通信号智能控制问题。 首先,对城市交通系统及其控制问题进行了介绍,综述了本论文的研究背景和意义、研究目的和任务以及论文的主要内容和结构安排。 其次,介绍ADP的发展。对常见的几种自适应动态规划算法进行说明,包括算法结构和计算公式等。 第三,以单路口为例,介绍了基本的路口交通流模型。在此基础上,设计了基于ADP算法的路口交通信号优化控制算法。并将所设计的控制算法与经典的定时信号控制、感应信号控制等方法进行仿真实验比较,结果表明基于ADP算法的交通信号优化控制算法可以随波动的交通状况动态优化控制参数,取得较好的控制效果。 第四,针对传统ADP算法存在的训练速度较慢的问题,改用群集智能的启发式搜索方法来实现ADP算法的学习和训练。设计基于人工蜂群理论的ADP算法,以加快ADP算法的优化速度。仿真结果显示本文给出的算法所需的训练次数少,便于在实时交通信号控制领域的应用。 第五,针对ADP算法由于初始参数随机选择而带来的优化效果的不稳定问题,以模糊神经网络代替传统的前向神经网络,引入先验知识,改善ADP算法的优化趋势。设计带有模糊规则的自适应交通信号控制算法,以两路口为例验证了本文算法的有效性。 第六,针对多交叉路口协调交通信号优化控制问题,提出一种基于ADP算法的多路口交通信号协调控制策略。本协调控制策略中,路口间所需交互的信息量较少,且无需上级协调控制单元,便于形成分布式交通信号控制系统。在所示的四路口交通信号协调控制仿真中,本文算法取得了较好的控制效果。 最后,对本论文的研究成果进行了总结,并展望了需要进一步研究的工作。
英文摘要With the rapid development of society and economy, as well as the fast urbanization, the number of city motor and traffic flow increased dramatically. As a result, the city becomes crowded and congested, lagging the economic development and urbanization process. As a complex giant system, the city traffic signal control is a random problem. So city traffic control research has important theoretical significance and practical value. At the same time, adaptive dynamic programming (ADP) is a class of relatively new optimization method. ADP is received more and more emphasis in theory and practical applications for its ability in studing and optimization. In this paper, we study the traffic signal intelligent control problems based on ADP under the background of city traffic singal control problem. Firstly, we pay attention to urban traffic control systems and their control problems. We also present the research background and significance of this paper. The research aims, as well as this paper’s main work and missions are introduced. Secondly, we present the development of adaptive dynamic programming. Several types of adaptive dynamic programming are illuminated. We present their structure and calculation. Thirdly, the basic model of junction traffic flow is introduced. A traffic signal intelligent controller is designed based on adaptive dynamic programming algorithm. And some simulations are carried out to compare the performance of the proposed controller with the normal pertimed signal control, traffic-actuated signal control, and so on. Fourthly, for dealing with the training problem in the normal adaptive dynamic programming, this paper adapts the artificial bee colony theory for training adaptive dynamic programming quickly. As a result, the adaptive dynamic programming can achieve an optimal control policy more quickly. It is important for applying the adaptive dynamic programming in real time traffic signal control. Fifthly, the normal adaptive dynamic programming chooses initial parameters randomly. But the random initial parameters lead to uncertain performance of this algorithm. For dealing with this disadvantage, this paper adapts the people’s knowledge in the adaptive dynamic programming. Thus, the training of the adaptive dynamic programming can begin with a better direction. Sixthly, this paper designs a new cooperative multi-intersections control algorithm based on the adaptive dynamic programming to deal with area traffic cooperative ...
关键词智能系统 自适应动态规划 交通信号控制 区域协调 蜂群理论 Intelligent System Adaptive Dynamic Programming Traffic Signal Control Area Cooperation Artifical Bee Colony
语种中文
文献类型学位论文
条目标识符http://ir.ia.ac.cn/handle/173211/6161
专题毕业生_博士学位论文
推荐引用方式
GB/T 7714
李涛. 基于自适应动态规划的路口交通信号优化控制[D]. 中国科学院自动化研究所. 中国科学院研究生院,2009.
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
CASIA_20061801462800(1378KB) 暂不开放CC BY-NC-SA
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[李涛]的文章
百度学术
百度学术中相似的文章
[李涛]的文章
必应学术
必应学术中相似的文章
[李涛]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。