基于深度学习和粒子滤波的公交车到站时间预测

来源 :北京交通大学学报 | 被引量 : 0次 | 上传用户：chinagirlxin

【摘要】

：

在现代城市中,准确预测公交车的到站时间具有重要意义.尤其是在交通拥堵条件下,公交车的到站时间受到复杂路况的极大影响.本文结合深度学习和粒子滤波技术,提出了一种基于深度学习(长短期记忆人工神经网络)和粒子滤波(Particle Filter,PF)的公交到站时间预测模型.该模型使用了公交车卫星定位系统和公交线路位置等数据,对所采集的数据进行插值与归一化等预处理,并充分考虑了公交车在运行过程中受到的影响因素,对北京公交集团的4条典型公交线路进行了分析.结果表明,基于深度学习和粒子滤波的公交车到站时间预测模型的

【作者】

：

安宇航马继辉刘慧勇纪安琪

【机构】

：

北京交通大学交通运输学院 ,北京 100044;北京信息科技大学信息管理学院 ,北京100192;青岛市市政工程设计研究院有限责任公司 ,山东青岛 266000

【出处】

：

北京交通大学学报

【发表日期】

：

2022年1期

【关键词】

：

公交到站时间预测深度学习粒子滤波 LSTM

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基于深度学习和粒子滤波的公交车到站时间预测

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