基于高德地图API的路段车速预测研究

为了更容易地获取交通数据，实现车速预测，利用Python语言开发一套操作简单、界面友好的程序，实现路段车速数据采集、处理、分析、预测和发布过程的简捷和集成化。根据高德地图开发平台的操作指南，利用Python编写爬虫程序，完成数据采集；将采集的数据进行清洗、修复，提取出指定路段的时间序列车速数据；将时间序列进行分解，使用ARIMA模型进行预测；利用Qt Designer生成界面代码，将逻辑代码与界面代码合并，完成数据采集、处理、分析和预测过程的可视化设计；利用Django框架，完成发布预测结果的Web页面。本文的研究结果可供研究人员快速获取指定路段车速数据，为出行者提供“拥堵预报”。

Research on the Prediction of Road Speed Based on Amap API

In order to obtain traffic data more easily and put the prediction of vehicle speed, a simple-to-use and user-friendly program is developed based on Python, which makes the collection, processing, analysis, prediction and release of road speed data more accessible and integrated. Such goal can be achieved, according to the operation guide of Amap development platform, by taking the following steps: Firstly, through python, a crawler program is designed to collet road speed data. Secondly, these collected data are purified and restored to extract the time series speed data of designated road section. Thirdly, the data are decomposed and used for prediction based on ARIMA model. Fourthly, through Qt Designer, the interface code is devloped and merged with logic code to complete the visual design process including data collection, processing, analysis and prediction. At last, the Django framework is used to complete the Web page of publishing prediction. The program can quickly obtain the speed data of designated road section and provide "congestion forecast" for travelers.