...
首页> 外文期刊>Accident Analysis & Prevention >Modelling the impact of causal and non-causal factors on disruption duration for Toronto's subway system: An exploratory investigation using hazard modelling
【24h】

Modelling the impact of causal and non-causal factors on disruption duration for Toronto's subway system: An exploratory investigation using hazard modelling

机译:对因果关系和非因果因素对多伦多地铁系统中断持续时间的影响进行建模:使用灾害建模的探索性调查

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Most investigations of incident-related delay duration in the transportation context are restricted to highway traffic, with little attention given to delays due to transit service disruptions. Studies of transit based delay duration are also considerably less comprehensive than their highway counterparts with respect to examining the effects of non-causal variables on the delay duration. However, delays due to incidents in public transit service can have serious consequences on the overall urban transportation system due to the pivotal and vital role of public transit. The ability to predict the durations of various types of transit system incidents is indispensable for better management and mitigation of service disruptions. This paper presents a detailed investigation on incident delay durations in Toronto's subway system over the year 2013, focusing on the effects of the incidents' location and time, the train-type involved, and the non-adherence to proper recovery procedures. Accelerated Failure Time (AFT) hazard models are estimated to investigate the relationship between these factors and the resulting delay duration. The empirical investigation reveals that incident types that impact both safety and operations simultaneously generally have longer expected delays than incident types that impact either safety or operations alone. Incidents at interchange stations are cleared faster than incidents at non-interchange stations. Incidents during peak periods have nearly the same delay durations as off-peak incidents. The estimated models are believed to be useful tools in predicting the relative magnitude of incident delay duration for better management of subway operations. (C) 2016 Elsevier Ltd. All rights reserved.
机译:在运输环境中,大多数与事件相关的延迟时间的调查仅限于高速公路交通,很少关注因运输服务中断而引起的延迟。在研究非因果变量对延误持续时间的影响方面,基于公交的延误持续时间的研究还不如高速公路同类研究全面。然而,由于公共交通的举足轻重的作用,公共交通服务事故造成的延误可能对整个城市交通系统造成严重影响。预测各种类型的运输系统事件的持续时间的能力对于更好地管理和减轻服务中断是必不可少的。本文对2013年多伦多地铁系统中的事故延误持续时间进行了详细调查,重点研究了事故发生的地点和时间,所涉及的列车类型以及不遵守适当的恢复程序的影响。估计了加速故障时间(AFT)危害模型,以研究这些因素与延迟持续时间之间的关系。实证研究表明,同时影响安全和运行的事件类型通常比预期影响安全或运行的事件类型具有更长的预期延迟。交换站的事件清除速度比非交换站的事件清除速度快。高峰时段的事件与非高峰事件的延迟时间几乎相同。估计的模型被认为是预测事件延迟时间的相对大小的有用工具,以更好地管理地铁运营。 (C)2016 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号