基于浮动车数据的动态交通诱导系统研究与实现

发布时间：2018-06-07 14:25

本文选题：动态交通诱导 + 浮动车数据　；参考：《长安大学》2014年硕士论文

【摘要】：动态交通诱导系统对提高车辆出行效率、增加道路使用效率、缓解交通拥堵具有十分重要的意义。传统的交通诱导系统多基于静态交通信息构建，没有结合实时动态交通信息、实用性不高。针对该问题，论文开发了一种基于浮动车数据的动态交通诱导系统，对系统中动态路网自动生成、动态道路阻值估算、动态交通诱导等多个关键技术进行了研究。论文主要工作如下： 1．提出了一种基于关系型数据的动态路网自动生成算法。该算法针对基于GIS（Geographic Information System）空间实体数据进行诱导存在的搜索冗余度大、效率低等问题，，对GIS数据进行重新分析，剔除冗余数据，并将结果存储在关系型数据库中，根据用户输入的起讫点动态构造搜索空间，提高了路网生成效率。 2．研究了浮动车数据预处理算法。针对原始浮动车数据存在误差、属性信息不足等问题，设计了数据清洗规则，对错误数据进行过滤，同时采用ST地图匹配算法对有误差的浮动车数据进行修正。 3．建立了一种基于交叉口延误与空间拓扑关系的道路阻值估算模型。动态道路阻值估算是交通诱导系统的核心，该模型通过浮动车数据预估交叉口延误时间，同时融合道路拓扑关系信息，实现了道路阻值的实时估算。 4．提出了一种基于改进蚁群算法的交通诱导算法，该算法针对传统蚁群算法在大规模路网中效率低的问题提出了三条改进规则，克服了传统蚁群算法在大规模路网下效率较低的不足，同时更能适应浮动车数据离散但又相互关联的特性。论文对上述算法进行了系统集成，并基于西安市6000多辆出租车60天运营数据对系统进行了测试，测试结果表明：系统运行稳定、实用性强，浮动车数据匹配准确率高达93%，系统生成的动态诱导路径比基于静态信息生成的路径平均节省20%出行时间，提高了出行效率。
[Abstract]:Dynamic traffic guidance system plays an important role in improving vehicle travel efficiency, increasing road use efficiency and alleviating traffic congestion. The traditional traffic guidance system is based on static traffic information and has no real-time dynamic traffic information. To solve this problem, a dynamic traffic guidance system based on floating vehicle data is developed in this paper. Several key technologies, such as automatic generation of dynamic road network, dynamic road resistance estimation, dynamic traffic guidance and so on, are studied. The main work of the thesis is as follows: 1. A dynamic road network automatic generation algorithm based on relational data is proposed. In order to solve the problems of large redundancy and low efficiency in search induced by spatial entity data based on GIS(Geographic Information system, the algorithm reanalyzes GIS data, removes redundant data, and stores the results in relational database. The search space is constructed dynamically according to the starting point of user input, and the efficiency of road network generation is improved. 2. The data preprocessing algorithm of floating vehicle is studied. Aiming at the problems of errors in original floating vehicle data and insufficient attribute information, the data cleaning rules are designed, the error data is filtered, and the St map matching algorithm is used to correct the error floating vehicle data. 3. A road resistance estimation model based on the relationship between intersection delay and spatial topology is established. Dynamic road resistance estimation is the core of traffic guidance system. The model estimates the delay time of intersection by floating vehicle data and integrates the road topology information to realize the real-time estimation of road resistance value. 4. A traffic guidance algorithm based on improved ant colony algorithm is proposed. The algorithm proposes three improved rules to solve the problem of low efficiency of traditional ant colony algorithm in large-scale road network. It overcomes the shortcoming of the traditional ant colony algorithm which is low efficiency under the large-scale road network and adapts to the discrete but interrelated characteristics of floating vehicle data at the same time. The system is integrated and tested based on the 60 days operation data of more than 6000 taxis in Xi'an. The test results show that the system is stable and practical. The accuracy rate of floating vehicle data matching is as high as 93%. The dynamic induced path generated by the system saves an average of 20% travel time and improves the travel efficiency compared with the path generated based on static information.
【学位授予单位】：长安大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U495

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