Journal Article
Pengfei Liu and Wei Fan
Jan-20
Liu, P. & Fan, W. (2020). Exploring Injury Severity in Head-On Crashes Using Latent Class Clustering Analysis and Mixed Logit Model: A Case Study of North Carolina. Accident Analysis & Prevention, 135.
Although only 2 % of crashes are head-on crashes in the United States, they account for over 10 % of all crash-related fatalities. This study aims to investigate the contributing factors that affect the injury severity of head-on crashes and develop appropriate countermeasures. Due to the unobserved heterogeneity inherent in the crash data, a latent class clustering analysis is firstly conducted to segment the head-on crashes into relatively homogeneous clusters. Then, mixed logit models are developed to further explore the unobserved heterogeneity within each cluster. Analyses are performed based on the data collected from the Highway Safety Information System (HSIS) from 2005 to 2013 in North Carolina. The estimated parameters and associated marginal effects are combined to interpret significant variables of the developed models. The proposed method is able to uncover the heterogeneity within the whole dataset and the homogeneous clusters. Results of this research can provide more reliable and insightful information to engineers and policy makers regarding the contributing factors to head-on crashes.
Accident Analysis & Prevention
Link not available.
Head-on crashes
Latent class clustering
Mixed logit model
Severity analysis
HSIS Summary Reports are two to eight pages in length and include a brief description of the issue addressed, data used, methodology applied, significant results, and practical implications.
A variety of research studies have been performed using data from HSIS. Many of the final reports prepared are now available electronically.
Research reports are often summarized in executive summaries, technical briefs, or other abbreviated formats. Included here are those road safety summaries that involved research using HSIS data.
In addition to conducting research, HSIS resources are also used to develop products that can be used by practitioners in the analysis of safety problems.
HSIS data are sometimes used in research studies that result in other types of finished products, such as dissertations, theses, and conference proceedings.
