Reports from University of Toronto Add New Data to Findings in Risk Management (Modelling the impact of causal and non-causal factors on disruption…

Reports from University of Toronto Add New Data to Findings in Risk Management (Modelling the impact of causal and non-causal factors on disruption duration for Toronto's subway system: An exploratory investigation using hazard modelling)

By a News Reporter-Staff News Editor at Insurance Weekly News -- Investigators publish new report on Risk Management. According to news originating from Toronto, Canada, by VerticalNews correspondents, research stated, "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."

Our news journalists obtained a quote from the research from the University of Toronto, "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."

According to the news editors, the research concluded: "The estimated models are believed to be useful tools in predicting the relative magnitude of incident delay duration for better management of subway operations."

For more information on this research see: Modelling the impact of causal and non-causal factors on disruption duration for Toronto's subway system: An exploratory investigation using hazard modelling. Accident Analysis and Prevention, 2017;98():232-240. Accident Analysis and Prevention can be contacted at: Pergamon-Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, England. (Elsevier - www.elsevier.com; Accident Analysis and Prevention - www.journals.elsevier.com/accident-analysis-and-prevention/)

The news correspondents report that additional information may be obtained from J. Louie, University of Toronto, Toronto, ON M5S 1A1, Canada. Additional authors for this research include A. Shalaby and K.N. Habib.

Keywords for this news article include: Toronto, Ontario, Canada, North and Central America, Risk Management, University of Toronto.

Our reports deliver fact-based news of research and discoveries from around the world. Copyright 2017, NewsRx LLC