Study Findings from California Polytechnic State University Provide New Insights into Risk Management (Multimodal crash frequency modeling:…

Study Findings from California Polytechnic State University Provide New Insights into Risk Management (Multimodal crash frequency modeling: Multivariate space-time models with alternate spatiotemporal interactions)

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 in Pomona, California, by VerticalNews journalists, research stated, "Enhancement of safety for all transportation mode users plays an essential role in the implementation of multimodal transportation systems. Compared with crash frequency models dedicated to motorized mode users, the use of these models has been considerably scarce in the multimodal literature."

Financial support for this research came from 2017 UCCONNECT Research Program.

The news reporters obtained a quote from the research from California Polytechnic State University, "To fill this research gap, the authors aimed to develop and evaluate three multivariate space-time models with different temporal trends and spatiotemporal interactions. The model estimates justified the use of mode-varying coefficients for explanatory variables as the impact of these factors varied across different crash modes. largely, a similar set of influential covariates was generated by the three models which indicate their robustness. However, notable differences were observed from the assessment of evaluation criteria pertaining to predictive accuracy based on criteria assessing the training and test errors. The model with time-varying spatial random effects demonstrated superior performance for training and test errors. However, due to the significant increase in number of effective parameters that were utilized for model development, this model appeared to have the largest value of deviance information criterion (DIC). In terms of the comparison between models based on site ranking performance, the time-varying spatial random effects model demonstrated the best performance in both site consistency and method consistency."

According to the news reporters, the research concluded: "In other words, the superiority of the model's predictive performance could be transferred to yield more accurate result at site ranking."

For more information on this research see: Multimodal crash frequency modeling: Multivariate space-time models with alternate spatiotemporal interactions. Accident Analysis and Prevention, 2018;113():159-170. 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 correspondents report that additional information may be obtained by contacting W. Cheng, Calif State Polytechnic Univ Pomona, Dept. of Civil Engn, Pomona, CA 91768, United States. Additional authors for this research include G.S. Gill, J.L. Ensch, J. Kwong and X.D. Jia.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.aap.2018.01.034. 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: Pomona, California, United States, North and Central America, Risk Management, California Polytechnic State University.

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