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基于模糊积分的区域交通服务水平评价研究 被引量:2

Urban Regional Traffic Level of Service Evaluation Based on Fuzzy Integral
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摘要 随着大城市路网建设的逐渐稳定,服务水平评价结果成为城市交通管理决策的一个重要依据,因而对城市道路交通服务水平(LOS)的评价成为一项重中之重的研究内容.本文提出一种基于模糊积分的区域交通LOS评价模型.该模型能够解决区域交通服务水平中多路段评价结果复合时的非可加性问题,即区域交通服务水平不等于局部路段或路口服务水平的简单之和,可满足区域交通的评价需求.在现场海量实测数据集的基础上,利用模糊积分用微观评价数值计算中观评价结果,排除了主观约束,并选取北京市典型区域进行了实验和应用,取得了较好的评价结果. At present,with the stabilization of the big cities' road network buildings,urban traffic level of service becomes the most important evidence for the traffic managements make decision.Thus,the regional traffic level of service(LOS) evaluation becomes a sticking point in urban traffic research to improve urban traffic management.This paper proposes a regional traffic LOS evaluation model based on the fuzzy integral.It can solve non-additivity of regional traffic LOS by synthesizing indexes value of several segments,in other words,the regional traffic LOS is neither the result of single parameter measure,nor the result of local traffic parameters' simple sum.In this paper,we uses fuzzy integral to meso-layer regional LOS assessment results from microcosmic layer attributes by real data.It can get rid of the subjective constraints,numerical examples applied in Beijing typical regions,the computational results show that the methods in region traffic can estimate the LOS of region traffic effectively.
出处 《交通运输系统工程与信息》 EI CSCD 2010年第6期180-184,共5页 Journal of Transportation Systems Engineering and Information Technology
关键词 城市交通 模糊积分 交通管理 服务水平评价 urban traffic fuzzy integral traffic management LOS evaluate
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参考文献13

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同被引文献21

  • 1张和生,张毅,胡东成.一种区域交通状态定量分析方法[J].吉林大学学报(工学版),2009,39(2):336-342. 被引量:6
  • 2郭伟,姚丹亚,付毅,胡坚明,刘宁.区域交通流特征提取与交通状态评估方法研究[J].公路交通科技,2005,22(7):101-104. 被引量:38
  • 3皮晓亮,王正,韩皓,孙亚.基于环形线圈检测器采集信息的交通状态分类方法应用研究[J].公路交通科技,2006,23(4):115-119. 被引量:33
  • 4王伟,杨兆升,李贻武,刘新杰,陈昕.基于信息协同的子区交通状态加权计算与判别方法[J].吉林大学学报(工学版),2007,37(3):524-527. 被引量:11
  • 5张和生.基于多元数据的交通状态分析方法研究[D].北京:清华大学自动化系,2006.
  • 6PAPAGEORGIOU M, DIAKAKI C, DINOPOULOU V. Review of road traffic control strategies [ J ]. Proceedings of the IEEE, 2003, 91 (12) :2043-2067.
  • 7HUANG Yanguo, KANG Yurong, ZHAO Shuling. Ur- ban regional road network traffic state identifying method [ C]//2012 Fifth International Conference on Intelligent Computation Technology and Automation. Zhangjiajie, Hunan: Es. n. ] , 2012:530-533.
  • 8ZHANG Ye, JIA Limin, CAI Guoqiang. A multi-grade evaluation model for traffic level of service [ C ]//2009 In- ternational Conference on Machine Learning and Cyber- netics. Baodine: Fs. n. ], 2009:3112-3115.
  • 9JI Xiaofeng, CHENG Wei, CHEN Yuguang. Traffic state identification methods based on vague sets [ C ]//2009 In- ternational Conference on Computational Intelligence and Software Engineering. Wuhan : [ s. n. ], 2009 : 1-4.
  • 10REN Qiliang, PENG Qiyuan. Application of H-Fuzzy e- valuation model in traffic congestion degree of city road- network [C]//Intemational Conference on Measuring Technology and Mechatronics Automation. Zhangjiajie, Hunan: Fs. n. ]. 2009:550-553.

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