基于浮动车数据的经验知识获取与时空建模

项目名称： 基于浮动车数据的经验知识获取与时空建模

项目编号： No.41271442

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 天文学、地球科学

项目作者： 唐炉亮

作者单位： 武汉大学

项目金额： 75万元

中文摘要： 人们在熟悉的城市环境中，会根据自己的经验知识，找到合理的出行路径，但是当人们处于陌生环境中，由于对城市交通不熟悉，在日益拥堵的城市中出行非常困难。如何将熟悉城市环境人群的经验知识用于公众在陌生环境中出行，一直是科学家们亟待解决的课题。 2010年《Science》指出"基于历史轨迹数据的统计，发现有93%的规律和重复性"，"经验路径比当前导航系统规划的路径更优越"。本课题以出租车GPS采集的浮动车轨迹数据为研究对象，研究出租车司机对于城市交通的时空认知规律与经验知识的获取，解决"经验知识获取需求亲身体验"的难题；提出采用基于Space-Time的经验知识多维度、多尺度时空表达与建模方法，解决困扰国内外研究者们"经验知识时空表达困难"的科学问题，建立个性化出行用户需求模型，将经验知识用于公众个性化出行的路径优化，避开和缓解城市交通拥堵，方便公众出行，具有重要的研究价值和应用前景。

中文关键词： 经验知识；动态导航；浮动车；路径优化；时空建模

英文摘要： With the rapid social and economic developments in China, the amount of vehicles has increased so rapidly that many traffic problems have become more and more serious, such as traffic congestion, traffic accidents, and the contradictory relationship between roads and vehicles. Traffic data collection is crucial in a traffic management information system. The term Floating Car Data (FCD) refers to the data collected continuously by a fleet of vehicles (i.e., taxis in this study), which can be considered as a distributed network of sensors similar to GPS, mobile phones, and WIFI access points.Taxi drivers drive on the roads every day and become very knowledgeable of the spatiotemporal traffic patterns in a city. It therefore is reasonable to assume that the routes chosen by taxi drivers often work out better than those selected by other drivers. Since dynamic navigation assistance based on real-time traffic information faces limitations such as the spatial coverage of real-time data collection sites, performance of real-time data processing and communications, and accuracy of short-term traffic forecasts in a large urban area, experiences gained by taxi drivers can be a valuable data source for improving the quality of vehicle navigation guidance. This project develops a vehicle navigation guidance system based on

英文关键词： Experience knowledge；Dynamic navigation；Floating car data；Route optimization；Space-time modeling