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Generating Alternative Pre-Trip Guidance for Metro Users by Considering Travel Time and Trip Feeling

机译:通过考虑出行时间和出行感觉为地铁用户生成替代的出行前指导

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The metro system is a critical part of urban public transportation systems because of its high capacity and reliable operation status. Although metro systems have attracted a large number of passengers, information service and trip guidance is still extremely deficient. Lack of effective guidance information may lead to the loss of network capacity and is not conductive to improving the level of service for metro systems. Unfortunately, few studies have paid attention to trip guidance for metro users. In order to provide alternative pre-trip guidance for metro users, a method to generate dynamic path guidance is proposed. First, a valid path set was generated by conducting a K-shortest path searching algorithm to avoid path enumeration. Then, a passenger flow assignment strategy based on the metro schedule was designed to identify the real trip path of each metro user from the valid path set. Third, pre-prior sectional passenger flow was forecasted from historical travel information accumulated from individuals. Finally, alternative pre-trip suggestions were generated by combining trip time and trip feeling with variable weights. The proposed method was tested using the metro network in Nanjing city, China. The empirical results show that metro users without pre-trip guidance information may choose a path which is neither time-saving nor comfortable. Comparatively, the guidance information generated by the proposed algorithm can help metro users find the most suitable paths.
机译:地铁系统由于其高容量和可靠的运行状态而成为城市公共交通系统的关键部分。尽管地铁系统吸引了大量乘客,但信息服务和旅行指南仍然极为匮乏。缺少有效的指导信息可能会导致网络容量的损失,并且不利于提高城域系统的服务水平。不幸的是,很少有研究关注地铁用户的出行指南。为了给地铁用户提供替代的出行前向导,提出了一种生成动态路径向导的方法。首先,通过执行K最短路径搜索算法来避免路径枚举,从而生成有效路径集。然后,设计了基于地铁时间表的客流分配策略,以从有效路径集中识别每个地铁用户的真实出行路径。第三,从个人积累的历史旅行信息中预测了之前的分段客流。最后,通过将出行时间和出行感觉与可变权重相结合,生成了其他出行前建议。在中国南京市的地铁网络中对提出的方法进行了测试。实证结果表明,没有出行前指导信息的地铁用户可能会选择既不省时又不舒适的路径。相比之下,该算法产生的引导信息可以帮助地铁用户找到最合适的路径。

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