基于动态交通信息的路径诱导技术研究与实现

发布时间：2018-05-04 19:46

本文选题：路径诱导 + 线性回归　；参考：《北京邮电大学》2014年硕士论文

【摘要】：随着城市的发展,交通拥堵问题越来越严重,交通拥堵可导致车辆通行速度下降,并因此带来汽车尾气污染等问题,影响了人民的生活。路径诱导技术是提高道路的通行效率,避免交通拥堵的有效方法,同时也是智能交通领域中的一个重要组成部分。准确可靠的交通流信息是路径诱导系统中的关键数据和基础数据。本文在前人研究的基础上对智能交通领域的短时交通流预测和路径诱导两个方面进行分析和研究。本文的主要工作如下： 1)设计了仿真实验,用于验证基于道路拓扑和权重的地图匹配算法的有效性,该实验模拟真实路况产生的流程,使用真实车辆的GPS数据,得到车辆通过道路的平均速度。 2)设计并实现了基于线性回归的短时交通流预测算法,使用道路速度的历史数据,在算法的选择上,综合考虑线性回归,神经网络,支持向量机,选用更适合于工程环境实现的线性回归算法,设计线性回归模型的输入参数,使之能有效预测道路的短时速度。实现一个改进的拓扑排序的调度算法,减少算法在训练时的内存使用。设计实验,验证了算法预测的准确性。 3)设计了基于动态交通信息的路径诱导算法,根据道路长度,实时速度和短时预测速度设计了一个动态的权重计算方法,使路径诱导算法能有效规避拥堵的道路。设计了仿真实验进行验证,表明算法具有一定的有效性。
[Abstract]:With the development of the city, the problem of traffic congestion becomes more and more serious. Traffic congestion can lead to the decrease of the speed of traffic and the pollution of vehicle exhaust, which affects people's life. Route guidance technology is an effective method to improve the traffic efficiency and avoid traffic congestion. It is also an important part of intelligent transportation field. Accurate and reliable traffic flow information is the key data and basic data in the path guidance system. On the basis of previous studies, this paper analyzes and studies the two aspects of short time traffic flow prediction and route guidance in the field of intelligent transportation. The main work of this paper is as follows: 1) A simulation experiment is designed to verify the validity of the map matching algorithm based on the road topology and weight. The experiment simulates the flow of the real road conditions and uses the GPS data of the real vehicle to get the average speed of the vehicle passing through the road. 2) the short-term traffic flow prediction algorithm based on linear regression is designed and implemented. Using the historical data of road speed, the linear regression, neural network and support vector machine are considered in the selection of the algorithm. The linear regression algorithm which is more suitable for engineering environment is selected and the input parameters of the linear regression model are designed so that it can effectively predict the short time speed of the road. An improved scheduling algorithm for topological sorting is implemented to reduce the memory usage of the algorithm in training. Experiments are designed to verify the accuracy of the algorithm. 3) A path guidance algorithm based on dynamic traffic information is designed, and a dynamic weight calculation method is designed according to road length, real time speed and short time prediction speed, which can effectively avoid congested roads. Simulation experiments are designed to verify the effectiveness of the algorithm.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U495;TP301.6

【参考文献】