全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

交叉口Agent间的多遇协调策略及其参数影响分析

Keywords: 交通工程,Agent,交互,交通信号控制,学习,协调

Full-Text   Cite this paper   Add to My Lib

Abstract:

为信号控制的城市道路交叉口定义一个Agent结构模型,在分析相邻交叉口交通流关联关系的基础上,利用记忆因子δ、学习概率α、交叉口交通流变化概率βi等参数阐述了交叉口Agent间的多遇协调流程。交叉口Agent多遇协调采用部分获利协作策略,其交互策略更多地考虑在获利少于对方时候如何以更加协作的态度进行协调。利用记忆因子δ构建了交叉口Agent多遇历史学习协调算法。以交叉口Agent集合达到协调平衡模式需要的交互次数为性能指标,以数个交叉口相连接的主干道为例分析了δ、α、βi等参数对此策略和算法的协调性能的影响,结果表明交叉口Agent集合达到协调平衡模式需要的交互次数随着α的减少、βi的增加、δ的减少而增加,具有一定的动态环境适应能力和协调能力。

References

[1]  WIERING M.Multi-Agent Reinforcement Learning for Traffic Light Control
[2]  [C] // Seventeeth International Conference on Machine Learning and "Applications.San Francisco,CA:Morgan Kaufmann Publishers Incorporation,2000:1151-1158.
[3]  PENDRITH M D.Distributed Reinforcement Learning for a Traffic Engineering Apphcation
[4]  [M].New York:ACM Press,2000:404-411.
[5]  ABDULHAI B,PRINGLE P.Autonomous Multiagent Reinforcement Learning:5gc Urban Traffic Control
[6]  [C/OL] //Annual Transportation Research Board Meeting.Shoreham:TRB,2003.
[7]  ABDULHAI B,PRINGLE P,KARAKOULAS G.Reinforcement Learning for True Adaptive Traffic Signal Control
[8]  [J].Journal of Transportation Engineering,ASCE,2003,129 (3):278-284.
[9]  张辉.基于分布式Q学习的区域交通协调控制的研究
[10]  [J].武汉理工大学学报:交通科学与工程版,2007,31(6):1121-1124.ZHANG Hui.Urban Traffic Coordination Control Based on Distributed Q-Learuing
[11]  [J].Journal of Wuhan University of Technology:Transportation Science & Engineering Edition,2007,31 (6):1121-1124.
[12]  欧海涛.基于RMM和贝叶斯学习的城市交通多智能体系统
[13]  [J].控制与决策,2001,16(3):291-295.OU Haitao.Urban Traffic Multi-agent System Based on RMM and Bayesian Learning
[14]  [J].Control and Decision,2001,16 (3):291-295.
[15]  李英.多Agent系统及其在预测与智能交通系统中的应用
[16]  [M].上海:华东理工大学出版社,2004:154-158.LI Ying.MAS and Its Application in Forecast and ITS
[17]  [M].Shanghai:East China University of Science and Technology Press,2004:154-158.
[18]  石纯一.基于Agent的计算
[19]  [M].北京:清华大学出版社,2007:149-161.SHI Chunyi.Computation Based on Agent
[20]  [M].Beijing:Tsinghua University Press,2007:102-106.
[21]  史忠科.交通控制系统导论
[22]  [M].北京:科学出版社,2003:72-73.SHI Zhongke.An Introduction to Traffic Control System
[23]  [M].Beijing:Science Press,2003:72-73.
[24]  ROOZEMOND D A,VAN DER VEER P.Usability of Intelligent Agent Systems in Urban Traffic Management
[25]  [J].Application of Artifical Intelligence in Engineering,1999 (7):15-18.
[26]  马寿峰.一种基于agent协调的两路口交通控制方法
[27]  [J].系统工程学报,2003,6(3):273-278.MA Shoufeng.Agent-based Traffic Coordination Control Method for Two Adjacent Intersections
[28]  [J].Journal of Systems Engineering,2003,6 (3):273-278.
[29]  BAZZAN A L C.A distributed approach for coordination of traffic signal agents
[30]  [J].Autonomous Agents and Multi Agent Systems,2005:131-164
[31]  BAKKER B,STEINGROVER M,SCHOUTEN R,et al.Cooperative Multi-agent Reinforcement Learning of Traffic Lights
[32]  [C] //Proceedings of the Workshop on Cooperative Multi-Agent Learning,European Conference on Machine Learning.Porto,Poetagal:ECML,2005:24-36.LI Mingli,WANG Xuanmin,ZHANG Lichuan.Analysis of Queuing and Stop Delay at Intersection by Method of Stationary Queue
[33]  [J].Journal of Transport Information and Safety,2009,27 (4):43-46.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133