Reports Summarize Risk Management Findings from University of New South Wales (Application of Fractal theory for crash rate prediction: Insights from…

Reports Summarize Risk Management Findings from University of New South Wales (Application of Fractal theory for crash rate prediction: Insights from random parameters and latent class tobit models)

By a News Reporter-Staff News Editor at Insurance Weekly News -- Current study results on Risk Management have been published. According to news reporting out of Sydney, Australia, by VerticalNews editors, research stated, "The repercussions from congestion and accidents on major highways can have significant negative impacts on the economy and environment. It is a primary objective of transport authorities to minimize the likelihood of these phenomena taking place, to improve safety and overall network performance."

Our news journalists obtained a quote from the research from the University of New South Wales, "In this study, we use the Hurst Exponent metric from Fractal Theory, as a congestion indicator for crash-rate modeling. We analyze one month of traffic speed data at several monitor sites along the M4 motorway in Sydney, Australia and assess congestion patterns with the Hurst Exponent of speed (H-speed).Random Parameters and Latent Class Tobit models were estimated, to examine the effect of congestion on historical crash rates, while accounting for unobserved heterogeneity. Using a latent class modeling approach, the motorway sections were probabilistically classified into two segments, based on the presence of entry and exit ramps."

According to the news editors, the research concluded: "This will allow transportation agencies to implement appropriate safety/traffic countermeasures when addressing accident hotspots or inadequately managed sections of motorway."

For more information on this research see: Application of Fractal theory for crash rate prediction: Insights from random parameters and latent class tobit models. Accident Analysis and Prevention, 2018;112():30-38. 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/)

Our news journalists report that additional information may be obtained by contacting S. Chand, Univ New South Wales, Sch Civil & Environm Engn, Res Center Integrated Transport Innovat RCITI, Sydney, NSW 2052, Australia.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.aap.2017.12.023. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

Keywords for this news article include: Sydney, Australia, Australia and New Zealand, Risk Management, University of New South Wales.

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