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Weather and rail delays: Analysis of metropolitan rail in Dublin

机译:天气和铁路延误:都柏林都市铁路分析

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摘要

With changes in the global climate, the occurrence of severe weather events appears to be becoming ever more frequent. As a result of this, vital transport networks are becoming increasingly exposed to disruption or disablement due to weather related incidents. In order to adapt to these changing conditions it is important to gain an understanding of how weather currently impacts transport systems. This paper presents the results of a statistical analysis of the impact of weather conditions on the performance of metropolitan commuter rail based upon observations made on the Dublin Area Rapid Transit (DART) rail system. Utilising a dataset comprising daily performance observations for 30 train services operating across the DART network, this research applies a number of multiple regression models to gain an understanding of the role of weather, temporal effects, and resulting interactions, on delays experienced by the network. While research in this area has traditional focused on the impact of single events, this study presents an examination of the role of multiple factors and their interactions. With regard to temporal effects, the largest delays are observed in the last third of the year, with peak delays occurring in November. Delays due to adverse weather conditions are observed, with rain being the primary factor related to poor performance. Interactions between different weather conditions, particularly wind and rain, as well as between weather conditions and the month in which a journey took place were also observed to be significant and resulting in delays to services. (C) 2017 Elsevier Ltd. All rights reserved.
机译:随着全球气候的变化,恶劣天气事件的发生似乎变得越来越频繁。结果,由于与天气有关的事件,重要的运输网络越来越容易遭受破坏或瘫痪。为了适应这些不断变化的条件,重要的是要了解当前天气如何影响运输系统。本文基于都柏林地区快速公交(DART)铁路系统的观测结果,对天气状况对大通勤铁路性能的影响进行了统计分析,从而得出了结果。利用包含DART网络上运营的30列火车服务的每日性能观察数据的数据集,这项研究应用了多个多元回归模型,以了解天气,时间影响以及由此产生的相互作用对网络所经历的延误的作用。尽管该领域的研究传统上集中于单个事件的影响,但本研究提出了对多个因素的作用及其相互作用的研究。关于时间上的影响,最大的延误出现在一年的后三分之一,最高的延误发生在11月。观察到由于不利的天气条件而造成的延误,降雨是与性能不佳相关的主要因素。还观察到不同天气条件之间的相互作用,特别是风和雨,以及天气条件和旅行月份之间的相互作用是很大的,并导致服务延迟。 (C)2017 Elsevier Ltd.保留所有权利。

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  • 来源
    《Journal of Transport Geography》 |2017年第2期|69-76|共8页
  • 作者单位

    Trinity Coll Dublin, Dept Civil Struct & Environm Engn, Dublin 2, Ireland;

    Trinity Coll Dublin, Sch Comp Sci & Stat, Dublin 2, Ireland;

    Trinity Coll Dublin, Dept Civil Struct & Environm Engn, Dublin 2, Ireland;

    Trinity Coll Dublin, Dept Civil Struct & Environm Engn, Dublin 2, Ireland;

    Trinity Coll Dublin, Dept Civil Struct & Environm Engn, Dublin 2, Ireland;

    Univ Leeds, Inst Transport Studies, Leeds, W Yorkshire, England;

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