Data on Risk Management Detailed by Researchers at Purdue University (Analyzing crash frequency in freeway tunnels: A correlated random parameters…

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Data on Risk Management Detailed by Researchers at Purdue University (Analyzing crash frequency in freeway tunnels: A correlated random parameters approach)

By a News Reporter-Staff News Editor at Insurance Weekly News -- Current study results on Risk Management have been published. According to news reporting originating from West Lafayette, Indiana, by VerticalNews correspondents, research stated, "The majority of past road safety studies focused on open road segments while only a few focused on tunnels. Moreover, the past tunnel studies produced some inconsistent results about the safety effects of the traffic patterns, the tunnel design, and the pavement conditions."

Our news editors obtained a quote from the research from Purdue University, "The effects of these conditions therefore remain unknown, especially for freeway tunnels in China. The study presented in this paper investigated the safety effects of these various factors utilizing a four-year period (2009-2012) of data as well as three models: 1) a random effects negative binomial model (RENB), 2) an uncorrelated random parameters negative binomial model (URPNB), and 3) a correlated random parameters negative binomial model (CRPNB). Of these three, the results showed that the CRPNB model provided better goodness-of-fit and offered more insights into the factors that contribute to tunnel safety. The CRPNB was not only able to allocate the part of the otherwise unobserved heterogeneity to the individual model parameters but also was able to estimate the cross-correlations between these parameters. Furthermore, the study results showed that traffic volume, tunnel length, proportion of heavy trucks, curvature, and pavement rutting were associated with higher frequencies of traffic crashes, while the distance to the tunnel wall, distance to the adjacent tunnel, distress ratio, International Roughness Index (IRI), and friction coefficient were associated with lower crash frequencies."

According to the news editors, the research concluded: "In addition, the effects of the heterogeneity of the proportion of heavy trucks, the curvature, the rutting depth, and the friction coefficient were identified and their inter-correlations were analyzed."

For more information on this research see: Analyzing crash frequency in freeway tunnels: A correlated random parameters approach. Accident Analysis and Prevention, 2018;111():94-100. 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 editors report that additional information may be obtained by contacting Q.Z. Hou, Purdue University, Lyles Sch Civil Engn, Center Rd Safety, West Lafayette, IN 47907, United States. Additional authors for this research include A.P. Tarko and X.H. Meng.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.aap.2017.11.018. 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: West Lafayette, Indiana, United States, North and Central America, Risk Management, Purdue University.