基于城市交通大数据的行驶路径快速生成算法  

Fast Route Generation Algorithm Based on Urban Traffic Big Data

作　　者：张胜敏[1] ZHANG Shengmin(Information Engineering College,Kaifeng University,Kaifeng Henan 475004,China)

机构地区：[1]开封大学信息工程学院,河南开封475004

出　　处：《信息与电脑》2022年第3期52-54,共3页Information & Computer

基　　金：2020年度河南省高等职业学校青年骨干教师培养计划项目(项目编号:2020GZGG043)。

摘　　要：在经济快速化发展的趋势下,车辆不断增加为我国城市交通带来一定困扰,道路拥挤的情况不断增多。因此,本文提出基于城市交通大数据的行驶路径快速生成算法。通过构建城市交通大数据卷积神经网络(Convolutional Neural Networks,CNN)预测模型,获取模型深度与结构参数;设置模型的参数,得出车辆到达目的地的时间间隔;根据驾驶人员与乘客提供的交通信息与需求,设计行驶路径快速生成算法,经过路径障碍物碰撞检测,生成最优化行驶路径。实验证明,此种行驶路径快速生成算法的路径生成时间较短,且各项评价指标的误差率较传统算法更具优势。Under the trend of rapid economic development,the increasing number of vehicles has brought some troubles to China’s urban traffic,and the situation of road congestion is increasing.Therefore,this paper proposes a fast path generation algorithm based on urban traffic big data.By constructing the prediction model of urban traffic big data CNN,the depth and structural parameters of the model are obtained;Set the parameters of the model to get the time interval of vehicles arriving at the destination;According to the traffic information and needs provided by drivers and passengers,a fast driving path generation algorithm is designed to generate the optimal driving path through path obstacle collision detection.Experiments show that this fast path generation algorithm has shorter path generation time,and the error rate of each evaluation index has more advantages than the traditional algorithm.

关 键 词：城市交通 大数据 行驶路径 算法 误差率 

分 类 号：U116.2[交通运输工程]