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清华大学学报(自然科学版)  2016, Vol. 56 Issue (7): 743-750    DOI: 10.16511/j.cnki.qhdxxb.2016.24.025
  土木工程 本期目录 | 过刊浏览 | 高级检索 |
考虑交通大数据的交通检测器优化布置模型
孙智源, 陆化普
清华大学 土木工程系, 交通研究所, 北京 100084
Optimal traffic sensor layout model considering traffic big data
SUN Zhiyuan, LU Huapu
Institute of Transport Engineering, Department of Civil Engineering, Tsinghua University, Beijing 100084, China
全文: PDF(1096 KB)  
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摘要 为了提高城市交通信息采集的准确性、可靠性和经济性,提出了一种交通检测器优化布置模型。大数据背景下,考虑系统成本、多源数据共享、数据需求、检测器故障、道路基础设施、检测器类型等因素,构建了交通检测器布置的影响因素集。综合分析各个影响因素,提出了由最小系统成本优化、最大截断流优化、最小包含路径优化和OD (origin-destination)覆盖约束构成的多目标优化模型。应用基于遗传算法的宽容分层序列法,对模型进行求解。算例研究表明:该文的模型实现了多目标的优化,反映了多源数据共享和检测器故障的影响,满足了OD覆盖约束,可达到交通检测器的优化布置。
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孙智源
陆化普
关键词 交通调查交通检测器优化布置多目标优化交通大数据遗传算法宽容分层序列    
Abstract:An optimal traffic sensor layout model was developed to improve the accuracy, reliability and economy of urban traffic information collection. The traffic sensor layout was optimized in light of big data traffic information with the system optimized with consideration of the system cost, multi-source data sharing, data demand, fault conditions, road infrastructure, and different types of sensors. The impact of these influential factors was taken into account in a multi-objective programming model that included system cost minimization, traffic flow intercept maximization, path coverage minimization, and an origin-destination(OD) coverage constraint. The model was solved by the tolerant lexicographic method based on a genetic algorithm. A case study shows that the model provides multi-objective optimization, reflects the influence of multi-source data sharing and fault conditions, satisfies the origin-destination coverage constraint, and provides the optimal traffic sensor layout.
Key wordstraffic survey    optimal traffic sensor layout    multi-objective programming    traffic big data    genetic algorithm    tolerant lexicographic method
收稿日期: 2015-05-20      出版日期: 2016-07-22
ZTFLH:  U491.1+1  
基金资助:“十二五”国家科技支撑计划资助项目(2014BAG01B04);清华大学苏州汽车研究院(吴江)返校经费课题(2015WJ-B-02)
通讯作者: 陆化普,教授,E-mail:luhp@tsinghua.edu.cn     E-mail: luhp@tsinghua.edu.cn
引用本文:   
孙智源, 陆化普. 考虑交通大数据的交通检测器优化布置模型[J]. 清华大学学报(自然科学版), 2016, 56(7): 743-750.
SUN Zhiyuan, LU Huapu. Optimal traffic sensor layout model considering traffic big data. Journal of Tsinghua University(Science and Technology), 2016, 56(7): 743-750.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2016.24.025  或          http://jst.tsinghuajournals.com/CN/Y2016/V56/I7/743
  图1 NguyenGDupuis网络
  表1 OD 交通需求
  表2 有效路径集合及流量
  图2 最小系统成本随点位数的变化图
  图3 最大截断流随点位数的变化图
  图4 最小包含路径随点位数的变化图
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