Campus Units
Civil, Construction and Environmental Engineering, Statistics
Document Type
Article
Publication Version
Accepted Manuscript
Publication Date
3-2018
Journal or Book Title
Analytic Methods in Accident Research
Volume
17
First Page
32
Last Page
46
DOI
10.1016/j.amar.2018.03.001
Abstract
Urban midblock crashes are influenced mainly by traffic operation and roadway geometric features. In this paper, 10-year crash data from 1,506 directional urban midblock segments in Nebraska were analyzed using the multivariate random parameters zero-inflated negative binomial model to account for unobserved heterogeneity produced by correlations across segments, correlations across crash collision types, excessive zero crashes, and over dispersion. The multivariate random parameters zero-inflated negative binomial model was superior to many common crash frequency models in terms of both goodness of fit and prediction accuracy. Compared with the multivariate fixed parameters zero-inflated negative binomial model, the multivariate random parameters zero-inflated negative binomial model identified fewer key influencing factors and revealed segment-specific effects of these factors on different crash types. It showed that the number of lanes, annual average daily traffic per lane, and segment length might have non-positive effects on crash frequencies. Segments with a speed limit of 45 mph had fewer crashes than did those with lower speed limits, and there were fewer crashes on the segments in Omaha than on those in Lincoln. It was also found that neither the presence of a shoulder, on-street parking, or one-way traffic, nor lane width had significant influences on crash frequencies. These findings are informative for transportation agencies to take correct and efficient measures to accommodate diverse transportation demands without reducing traffic safety. By contrast, the fixed parameters model produced results consistent with intuition, but the results were insufficient to provide actionable recommendations.
Research Focus Area
Transportation Engineering
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Copyright Owner
Elsevier Ltd.
Copyright Date
2018
Language
en
File Format
application/pdf
Recommended Citation
Liu, Chenhui; Zhao, Mo; Li, Wei; and Sharma, Anuj, "Multivariate random parameters zero-inflated negative binomial regression for analyzing urban midblock crashes" (2018). Civil, Construction and Environmental Engineering Publications. 178.
https://lib.dr.iastate.edu/ccee_pubs/178
Included in
Civil Engineering Commons, Multivariate Analysis Commons, Transportation Engineering Commons
Comments
This is a manuscript of an article published as Liu, Chenhui, Mo Zhao, Wei Li, and Anuj Sharma. "Multivariate random parameters zero-inflated negative binomial regression for analyzing urban midblock crashes." Analytic Methods in Accident Research 17 (2018): 32-46. DOI: 10.1016/j.amar.2018.03.001. Posted with permission.