基于机器学习的交通数据分析与应用

Traffic Data Analysis and Application Based on Machine Learning

对海量交通数据进行分析,可为实现智能交通调度提供一定的参考依据,并为进行相关可行性分析提供有效支撑。本文利用Python和Pandas数据处理模块,对成都市1.4+万辆出租车的GPS记录进行分析处理。借助于机器学习中的回归算法,实现对某出租车在某时段行驶于某条线路所需时间的预测,并通过网页交互的形式,为用户提供出租车及出行路线推荐方案。

Analysis of massive traffic data provides a convenient reference for modern traffic scheduling and feasibility prediction,and provide effective support for relevant feasibility analysis. This article uses the Python and Pandas module to deal with the GPS records of more than 14 thousand taxis in Chengdu. Through the regression prediction via machine learning,the forecasting of required time for a taxi to travel on a certain period of time is realized. Finally,the recommendation of travel routes and taxis for users through a web page is provided.