基于交通大数据的车辆行驶路径规划综述  

Review of Vehicle Route Planning Based on Traffic Big Data

作　　者：王迎 赵建军[1] 李兴菊 聂红梅 WANG Ying;ZHAO Jian-jun;LI Xing-ju;NIE Hong-mei(College of Science,Kunming University of Science and Technology,Kunming 650500,China)

机构地区：[1]昆明理工大学理学院,云南昆明650500

出　　处：《软件导刊》2020年第10期50-54,共5页Software Guide

基　　金：国家自然科学基金青年科学基金项目(11103069)。

摘　　要：交通大数据的应用和发展为现代车辆路径规划带来了机遇和挑战。因此,了解交通大数据概念、路网匹配、路径规划算法、交通信息预测等方面的研究现状和研究特点,对明确未来路径规划研究方向和发展趋势显得尤为重要。首先介绍交通大数据概念及轨迹数据预处理方法,归纳总结国内外在路网匹配上的各种匹配算法及其优缺点;然后,阐述常用路径规划算法,其中包括传统经典算法与当下流行的智能算法;随后对交通信息预测研究方法和各种预测模型进行简要概括;最后指出车辆路径规划现阶段存在的问题,并展望未来研究方向。The application and development of traffic big data brings new opportunities and challenges to modern vehicle route planning.Therefore,it is particularly important to understand the concept of traffic big data,the research status and characteristics of road network matching,route planning algorithm,and traffic information forecasting for the research direction and development trend of future route planning.In this regard,the concept of traffic big data and the preprocessing of trajectory data are introduced firstly.Secondly,the various matching algorithms for road network matching at home and abroad and the advantages and disadvantages of each algorithm are summarized.Then,the common route planning algorithm including traditional classical algorithms and current popular intelligent algorithms are elaborated.The following are brief summaries of research methods and various predictive models for traffic information prediction.Finally problems existing at the current stage of vehicle route planning are pointed out and the prospects for future research are presented.

关 键 词：智能交通 路径规划 交通大数据 行驶车辆 路网匹配 交通信息预测 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]