基于OpenStreetMap的中国跨区域交通预测

Frank F. Xu, Bill Yuchen Lin, Qi Lu, Yifei Huang, Kenny Q. Zhu
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引用次数: 15

摘要

OpenStreetMap (OSM)是一个免费的、开源的、流行的地图服务。然而,由于各种原因,它不提供中国的实时交通信息或交通预测。本文提出了一种从中国商业闭源地图提供商百度地图(Baidu Map)提供的图形交通状况数据中学习预测模型的方法和系统,并将该模型应用于OSM,在百度地图没有提供该地区交通数据的情况下,对中国上海各地区的交通状况进行预测,准确率接近90%。该系统可用于城市规划、交通调度以及个人出行规划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cross-region traffic prediction for China on OpenStreetMap
OpenStreetMap (OSM) is a free, open-source and popular mapping service. However, due to various reasons, it doesn't offer live traffic information or traffic prediction for China. This paper presents an approach and a system to learn a prediction model from graphical traffic condition data provided by Baidu Map, which is a commercial, close-source map provider in China, and apply the model on OSM so that one can predict the traffic conditions with nearly 90% accuracy in various parts of Shanghai, China, even though no traffic data is available for that area from Baidu Map. This novel system can be useful in urban planning, transportation dispatching as well as personal travel planning.
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