[1]陈坚,陈健,邵毅明,等.粗糙集的过饱和多交叉口协同优化模型研究[J].智能系统学报编辑部,2015,10(5):783-789.[doi:10.11992/tis.201406045]
 CHEN Jian,CHEN Jian,SHAO Yiming,et al.Collaborative optimization model for oversaturated multiple intersections based on the rough set theory[J].CAAI Transactions on Intelligent Systems,2015,10(5):783-789.[doi:10.11992/tis.201406045]
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粗糙集的过饱和多交叉口协同优化模型研究(/HTML)
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《智能系统学报》编辑部[ISSN:1673-4785/CN:23-1538/TP]

卷:
第10卷
期数:
2015年5期
页码:
783-789
栏目:
出版日期:
2015-10-25

文章信息/Info

Title:
Collaborative optimization model for oversaturated multiple intersections based on the rough set theory
作者:
陈坚12 陈健3 邵毅明12 邓天民12
1. 重庆交通大学 山地城市交通系统与安全重庆市重点实验室, 重庆 400074;
2. 重庆交通大学 交通运输学院, 重庆 400074;
3. 中国中铁二院工程集团有限责任公司, 四川 成都 610031
Author(s):
CHEN Jian12 CHEN Jian3 SHAO Yiming12 DENG Tianmin12
1. Chongqing Key Lab of Traffic System & Safety in Mountain Cities, Chongqing Jiaotong University, Chongqing 400074, China;
2. School of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China;
3. China Railway Eryuan Engineering Group Co., Ltd, Chengdu 610031, China
关键词:
交通工程交通控制多交叉口过饱和粗糙集决策规则
Keywords:
traffic engineeringtraffic controlmultiple intersectionsoversaturatedrough set theorydecision rule
分类号:
U491.54
DOI:
10.11992/tis.201406045
文献标志码:
A
摘要:
为解决现有模糊智能控制方法仅适用于单交叉口非饱和状态,满足区域交通过饱和多交叉口信号协同联动控制的需要,提出了高峰时期主通道优化控制策略。在粗糙集知识推理基础上,构建了以多交叉口状态信息为条件属性,以绿灯延长方式、绿灯延长相位和绿灯延长时间3个参数为决策属性的多决策属性模糊控制模型。运用可辨识矩阵与属性频度的属性约简方法对模型进行约简,提取决策规则。实例分析表明:多交叉口主通道绿灯时间延长3~8 s能够有效提高区域交通整体通行效能,同时延长时间不仅与过饱和状态车辆最大排队长度有关,还与绿灯延长方式、绿灯延长相位存在关联,这与交警经验总结的控制规律一致。
Abstract:
To solve the defect that the existing fuzzy intelligent control method is only suitable for a single intersection under unsaturated state, and to meet the need of coordination control of regional traffic for oversaturated multiple intersections, an optimization control strategy for main channel at peak time was proposed. The fuzzy control model with multiple decision attributes was established on the basis of knowledge reasoning in rough sets theory. It took multiple intersections state information as condition attributes, and the elongation mode, phase, and green light timing, as decision attributes. The methods of attribute reduction of the discernibility matrix and the frequency of attribute were used in the model, then some decision rules were extracted. The results show that the efficiency of regional traffic was improved via 3-8 more seconds of green light signal at the main channel. In addition, the extension time is not only related to the maximum queue length of vehicles under oversaturated vehicle conditions, but also the extension mode and phase of green light, which is consistent with the experience of traffic police.

参考文献/References:

[1] CHEN Shuiyu, XU Hao, LIU Hongchao. Timing oversaturated signals:what can we learn from classic and state-of-the-art signal control models[J]. Journal of Transportation Systems Engineering and Information Technology, 2013, 13(1):97-110.
[2] 李瑞敏. 过饱和交叉口交通信号控制研究现状与展望[J]. 交通运输工程学报, 2013, 13(6):119-126. LI Ruimin. Study status and prospect of traffic signal control for over-saturated intersection[J]. Journal of Traffic and Transportation Engineering, 2013, 13(6):119-126.
[3] WU Xinkai, LIU H X, GETTMAN D. Identification of oversaturated intersections using high-resolution traffic signal data[J]. Transportation Research Part C:Emerging Technologies, 2010, 18(4):626-638.
[4] ABOUDOLAS K, PAPAGEORGIOU M, KOUVELAS A, et al. A rolling-horizon quadratic-programming approach to the signal control problem in large-scale congested urban road networks[J]. Transportation Research Part C:Emerging Technologies, 2010, 18(5):680-694.
[5] 李岩, 赵志宏, 李鹏飞, 等. 过饱和状态交通信号控制方法综述[J]. 交通运输工程学报, 2013, 13(4):116-126. LI Yan, ZHAO Zhihong, LI Pengfei, et al. Review of traffic signal control methods under over-saturated conditions[J]. Journal of Traffic and Transportation Engineering, 2013, 13(4):116-126.
[6] LIU Hongchao, BALKE K N, LIN Weihua. A reverse causal-effect modeling approach for signal control of an oversaturated intersection[J]. Transportation Research Part C:Emerging Technologies, 2008, 16(6):742-754.
[7] WU Aoxiang, QI Liqun, YANG Xiaoguang. Mechanism analysis and optimization of signalized intersection coordinated control under oversaturated status[J]. Procedia-Social and Behavioral Sciences, 2013, 96:1433-1442.
[8] 向伟铭, 肖建, 蒋阳升. 基于切换系统的过饱和信号交叉口混杂控制[J]. 交通运输系统工程与信息, 2014, 14(2):57-61. XIANG Weiming, XIAO Jian, JIANG Yangsheng. Hybrid control for over-saturated signalized intersection based on switched system[J]. Journal of Transportation Systems Engineering and Information Technology, 2014, 14(2):57-61.
[9] 陈智, 刘小明, 刘文婷, 等. 过饱和交叉口交通信号模糊关联控制方法[J]. 信息与技术, 2014, 43(3):374-380. CHEN Zhi, LIU Xiaoming, LIU Wenting, et al. Interconnected control of traffic signals at oversaturated intersections using fuzzy control method[J]. Information and Control, 2014, 43(3):374-380.
[10] 杨立才, 贾磊, 赵建玉, 等. 基于粗集理论的交通控制系统研究[J]. 中国公路学报, 2005, 18(2):79-83. YANG Licai, JIA Lei, ZHAO Jianyu, et al. Study of traffic control systems based on rough sets theory[J]. China Journal of Highway and Transport, 2005, 18(2):79-83.
[11] 于泉, 荣建. 基于模糊逻辑的过饱和交叉口定周期配时方案优化[J]. 北京工业大学学报, 2007, 33(11):1173-1176. YU Quan, RONG Jian. Fixed timing plan optimization for oversaturated intersection based on fuzzy logic[J]. Journal of Beijing University of Technology, 2007, 33(11):1173-1176.
[12] TONG Yue, ZHAO Lei, LI Li, et al. Stochastic programming model for oversaturated intersection signal timing[J]. Transportation Research Part C:Emerging Technologies, 2015,58,474-486.
[13] 雷磊, 吴洋, 刘昱岗. 过饱和交叉口群系统建模及优化模型[J]. 计算机工程与应用, 2010, 46(4):26-28. LEI Lei, WU Yang, LIU Yugang. System modeling and optimization model of oversaturated intersection group[J]. Computer Engineering and Applications, 2010, 46(4):26-28.
[14] SUN Weili, WU Xinkai, WANG Yunping, et al. A continuous-flow-intersection-lite design and traffic control for oversaturated bottleneck intersections[J]. Transportation Research Part C:Emerging Technologies, 2015, 56:18-33.
[15] PAI Pingfeng, CHEN Taichi. Rough set theory with discriminant analysis in analyzing electricity loads[J]. Expert Systems with Applications, 2009, 36(5):8799-8806.
[16] 戢晓峰, 刘澜, 吴其刚. 区域路网交通信息提取方法[J]. 西南交通大学学报, 2008, 43(3):422-426. JI Xiaofeng, LIU Lan, WU Qigang. Extraction method for traffic information of regional road network[J]. Journal of Southwest Jiaotong University, 2008, 43(3):422-426.
[17] 蒲世林, 李瑞敏, 史其信. 基于粗糙集-模糊识别技术的交通流状态识别算法研究[J]. 武汉理工大学学报:交通科学与工程版, 2010, 34(6):1154-1158. PU Shilin, LI Ruimin, SHI Qixin. Study on auto-identification algorithm of traffic flow state based on rough set and fuzzy theory[J]. Journal of Wuhan University of Technology:Transportation Science & Engineering, 2010, 34(6):1154-1158.
[18] 陈坚, 霍娅敏, 傅志妍, 等. 基于粗糙集的公路客运量预测[J]. 重庆交通大学学报:自然科学版, 2009, 28(6):1071-1074. CHEN Jian, HUO Yamin, FU Zhiyan, et al. Forecast of highway passenger transport volume based on rough set theory[J]. Journal of Chongqing Jiaotong University:Natural Science, 2009, 28(6):1071-1074.
[19] 王国胤, 姚一豫, 于洪. 粗糙集理论与应用研究综述[J]. 计算机学报, 2009, 32(7):1229-1246. WANG Guoyin, YAO Yiyu, YU Hong. A survey on rough set theory and applications[J]. Chinese Journal of Computers, 2009, 32(7):1229-1246.
[20] 霍娅敏, 陈坚, 李啸虎, 等. 城市建设项目交通影响后评价模型[J]. 交通运输工程学报, 2012, 12(1):79-86. HUO Yamin, CHEN Jian, LI Xiaohu, et al. Traffic impact post-evaluation model of urban construction project[J]. Journal of Traffic and Transportation Engineering, 2012, 12(1):79-86.
[21] 任小康, 吴尚智, 马如云. 基于可辨识矩阵的属性频率约简算法[J]. 兰州大学学报:自然科学版, 2007, 43(1):138-140. REN Xiaokang, WU Shangzhi, MA Ruyun. An algorithm of attribute frequency reduction based on discernibility matrix[J]. Journal of Lanzhou University:Natural Science, 2007, 43(1):138-140.
[22] 欧芳芳, 马晓辉, 马利芳, 等. 基于改进属性频度的属性约简算法[J]. 电力科学与工程, 2009, 25(5):60-63. OU Fangfang, MA Xiaohui, MA Lifang, et al. One improved algorithm of attribute reduction based on frequency of attributes[J]. Electric Power Science and Engineering, 2009, 25(5):60-63.

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备注/Memo

备注/Memo:
收稿日期:2014-06-22;改回日期:。
基金项目:科技部“863”计划资助项目(2011AA110306);国家自然科学基金资助项目(51308569);中国中铁二院工程集团有限责任公司科研资助项目(2014-50).
作者简介:陈坚,男,1985年生,副教授,主要研究方向为交通行为理论与实证、运输系统分析与决策。曾获四川省科技进步三等奖1项,广西发改委优秀成果二等奖1项,发表学术论文30余篇,其中被EI检索11篇;陈健,男,1976年生,高级工程师,主要研究方向为智能交通、交通规划。参加各类项目100余项,担任近50余个项目专业设计负责人,获得四川省及集团公司优秀工程咨询一等奖1项、二等奖2项、三等奖5项;邵毅明,男,1955年生,教授,博士生导师,主要研究方向为道路交通安全、智能交通。曾获上海市科技进步一等奖1项,重庆市科技进步二等奖1项、三等奖2项,重庆市政府发展贡献三等奖1项,中国智能交通协会科学技术三等奖1项,发表学术论文100余篇。
通讯作者:邵毅明.E-mail:sym@cqjtu.edu.cn.
更新日期/Last Update: 2015-11-16