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摘要：高速公路交通检测器布设是高速公路管理运营的先决条件与重要研究课题。交通检测器的布设决定着路段行程时间估算及预测的精度。同时，检测器技术、行程时间估计方法也会影响到检测器布设方法。研究利用手机切换数据交通信息提取支持，结合传统固定检测器，基于BP神经网络实现行程时间融合估计。基于新的行程时间估计方法，以估计精度为约束，研究传统固定检测器的布设。结合实例分析，验证行程时间融合估计方法有效性，并在均匀布设和盲区补充方案基础上，研究检测器布设间距对交通参数估计的影响。
关键词：智能交通系统；检测器布设；移动信令数据；BP神经网络；数据融合
 
Freeway Detector Placement Strategy Research Based on Mobile Signaling Data Support
 
Wang Hao-miao, Lei Yi, Yang Bin-bin
 
Shanghai Meihui Software Co.,Ltd., Shanghai 200081
 
Abstract：Freeway traffic detector placement is the prerequisite of freeway management operation and one of the important research subjects, which decides the accuracy of travel time estimation and prediction. Meanwhile, detection technology and travel time estimation methodology have a great influence on traffic detector placement. The research used support of cellular handoff data extracting traffic information and combined with traditional point detector data to realize travel time fusion estimation on basis of BP neural network. Based on the new estimation method, with estimation precision as constraints, the research focused on traditional point detector placement. The effectiveness of travel time fusion estimation proposed got verified with a study case. Based on uniform spacing strategy and blind area compaction strategy, the research explored the influence of detector spacing to traffic parameters using proposed travel time fusion estimation method.

Keywords：Intelligent transportation system; detector placement; mobile signaling data; BP neural network; data fusion

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