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| 基于浮动车移动检测与感应线圈融合技术的行程时间估计模型 | |
| 引用本文： | 邹亮,徐建闽,朱玲湘,温惠英.基于浮动车移动检测与感应线圈融合技术的行程时间估计模型[J].公路交通科技,2007,24(6):114-117. |
| 作者姓名： | 邹亮 徐建闽 朱玲湘 温惠英 |
| 作者单位： | 1. 深圳大学,土木工程学院,广东,深圳,518060 2. 华南理工大学,交通学院,广东,广州,510640 3. 华南农业大学,理学院,广东,广州,510642 |
| 基金项目： | 国家自然科学基金资助项目(50578064)，华南农业大学校长基金资助项目(2006K017)，深圳大学科研启动基金资助项目(自然科学类200721) |
| 摘 要： | 综合考虑到浮动车检测技术与感应线圈检测技术的优缺点,为了提高道路行程时间估计的精度及完备性,提出基于浮动车与感应线圈的融合检测技术的行程时间估计模型。该模型利用神经网络技术对两种检测技术同一路段的检测数据进行融合,从而达到提高道路行程时间估计精度和完备性的目的。最后,以广州市7 000多辆装有GPS装置的出租车所提供的浮动车数据、100多个安装在广州市各主要道路口上的感应线圈检测器提供的感应线圈数据以及广州市交通电子地图为基础,在10条道路上分别随机选取的500个两种检测数据对提出的模型进行了验证,试验结果表明,此模型在道路行程时间估计的精度方面较浮动车移动检测技术与感应线圈技术有较大提高。 |
| 关 键 词： | 交通工程 数据融合技术 神经网络 行程时间 浮动车 |
| 文章编号： | 1002-0268（2007）06-0114-04 |
| 修稿时间： | 2006-01-12 |
Estimation Model of Travel Time Based on Fusion Technique from Probe Vehicle and Crossing Data |
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| ZOU Liang,XU Jian-min,ZHU Ling-xiang,WEN Hui-ying.Estimation Model of Travel Time Based on Fusion Technique from Probe Vehicle and Crossing Data[J].Journal of Highway and Transportation Research and Development,2007,24(6):114-117. | |
| Authors: | ZOU Liang XU Jian-min ZHU Ling-xiang WEN Hui-ying |
| Institution: | 1.School of Civil Engineering, Shenzhen University, Guangdong Shenzhen 518060, China; 2.Scholl of Transportation, South China University of Technology, Guangdong Guangzhou 510640, China; 3.School of Science, South China Agricultural University, Guangdong Guangzhou 510642, China |
| Abstract: | Considering the advantages and disadvantages of both probe vehicle and loop techniques,to improve the accuracy and completeness of estimating travel time,a new estimation model of travel time is described based on fusion technique performing travel time studies using probe vehicle and loop detectors.This model uses neural network to fuse the same road detecting data of two detecting techniques to improve the accuracy and completeness of estimating travel time.Finally,the test of the model is verified using random 500 data in 10 roads based on probe vehicle data from 7 000 taxies equipped with GPS receivers,100 fixed detectors fixed in main roads in Guangzhou and electronic map of Guangzhou City.The results indicate that the model is more efficient than probe vehicle and loop technique on estimating travel time. |
| Keywords: | traffic engineering data fusion technique neural network travel time probe vehicle |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |