项目名称: 不确定、动态条件下交通检测器网络结构优化研究
项目编号: No.71301115
项目类型: 青年科学基金项目
立项/批准年度: 2014
项目学科: 管理科学
项目作者: 朱宁
作者单位: 天津大学
项目金额: 19万元
中文摘要: 交通检测器网络结构的合理设计有助于提升实时交通信息收集的效果。本项目在不确定、动态的交通网络环境以及检测器自身故障条件下,研究如何优化检测器网络结构,包括检测器的位置、类型和数量。首先运用仿真实验方法,研究不同外界交通环境,不同类型检测器及检测器网络结构对交通信息应用性能的影响机制,并对结果进行统计分析,得出检测器网络与交通信息应用性能之间的数量关系。其次,从交通网络的不确定性和动态性中发现规律并进行数学描述,利用整数或混合整数优化理论与方法,设计不确定、动态交通网络环境下和高鲁棒性要求下的数学优化模型并开发算法进行求解。再次,对于检测器自身故障情况,运用统计分析和数据挖掘技术,从个体和网络两个层面识别检测器故障模式。利用整数优化或随机优化理论与方法,设计故障条件下的检测器网络结构优化模型,并开发精确或启发式算法进行求解。最后,以实际案例对各种检测器网络结构优化模型进行总结。
中文关键词: 检测器网络结构优化;不确定性;动态交通网络;检测器故障;
英文摘要: The efficient deployment of traffic sensor network is helpful for improving efficiency of real time traffic information collection. This project aims to investigate how to optimize traffic sensor network structure which mainly includes location, category and number of traffic sensors under stochastic, dynamic transportation network and considering prevalent sensor failure in practice. Firstly, simulation experiments are going to be designed for figuring out the impact mechanism of different transportation environment, different type of sensors and sensor network topology on the performance of traffic information application. A quantitative relationship between sensor network and traffic information application should be obtained by using statistical analysis. Secondly, uncertainty and dynamics of transportation network will be investigated, and a mathematical description will be proposed. Integer and mixed integer mathematical programming theory and methodology will be designed under uncertain, dynamic traffic environment. Robust sensor network is another objective. Efficient algorithms will be proposed. Thirdly, regarding the sensor failure that we are facing, sensor failure pattern should be identified on both individual and network level by employing statistical analysis tool and data mining technology. Integ
英文关键词: Traffic sensor location;Uncertainty;Dynamic Transportation Networks;Sensor failure;