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Map matching for error prone GPS data on a sparse road network and predicting travel time of a route

机译:稀疏道路网络上易于出错的GPS数据的地图匹配,并预测路线的行驶时间

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Optimal ambulance route detection in an urban area is a challenging problem especially in the presence of difficulties such as sparse road network, error-prone GPS data and irregular traffic conditions. We have worked on solutions robust to these challenges and for the first time ever in the context of Dhaka, Bangladesh. This paper presents our newly designed map-matching algorithms as well as an intelligent route prediction scheme. We have implemented our algorithms on real traffic data and discuss the results here.
机译:在市区中最佳的救护车路线检测是一个具有挑战性的问题,尤其是在存在诸如稀疏的道路网络,容易出错的GPS数据和不规则的交通状况之类的困难的情况下。我们一直致力于解决这些挑战,这是孟加拉国达卡有史以来的第一次。本文介绍了我们新设计的地图匹配算法以及智能路线预测方案。我们已经在实际流量数据上实现了算法,并在此处讨论了结果。

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