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.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)