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Citation |
Lee J, Abdel-Aty MA, Cai Q. Accid. Anal. Prev. 2017; 102: 213-226. |
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Affiliation |
Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816-2450, United States. |
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Copyright |
(Copyright © 2017, Elsevier Publishing) |
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DOI |
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PMID |
28340414 |
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Abstract |
There have been great efforts to develop traffic crash prediction models for various types of facilities. The crash models have played a key role to identify crash hotspots and evaluate safety countermeasures. In recent, many macro-level crash prediction models have been developed to incorporate highway safety considerations in the long-term transportation planning process. Although the numerous macro-level studies have found that a variety of demographic and socioeconomic zonal characteristics have substantial effects on traffic safety, few studies have attempted to coalesce micro-level with macro-level data from existing geographic units for estimating crash models. In this study, the authors have developed a series of intersection crash models for total, severe, pedestrian, and bicycle crashes with macro-level data for seven spatial units. The study revealed that the total, severe, and bicycle crash models with ZIP-code tabulation area data performs the best, and the pedestrian crash models with census tract-based data outperforms the competing models. Furthermore, it was uncovered that intersection crash models can be drastically improved by only including random-effects for macro-level entities. Besides, the intersection crash models are even further enhanced by including other macro-level variables. Lastly, the pedestrian and bicycle crash modeling results imply that several macro-level variables (e.g., population density, proportions of specific age group, commuters who walk, or commuters using bicycle, etc.) can be a good surrogate exposure for those crashes. Language: en |
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Keywords |
Crash prediction model; Macro-level traffic safety; Micro-level traffic safety; Random-effects model; Safety performance function; Zonal effect |