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Use of Propensity Score Matching Method and Hybrid Bayesian Method to Estimate Crash Modification Factors of Signal Installation.
| 题名： | Use of Propensity Score Matching Method and Hybrid Bayesian Method to Estimate Crash Modification Factors of Signal Installation. |
| 作者： | Aul-Nathan; Davis-Gary |
| 关键词： | Accident-exposure; Accident-risk; Belgium-; Decomposition-Mathematics; Fatalities-; Fatality-risk; Highway-safety; Legislation-; Mathematical-models; Risk-analysis; Socioeconomic-factors; Time-of-acci |
| 摘要： | The general purpose of this research is to improve insight into road safety on Belgian highways by means of a layered model. The monthly number of persons killed on highways in Belgium is decomposed into three parts: exposure, accident risk, and fatality risk. The evolution in each of these dimensions is investigated separately. More specifically, for each dimension a descriptive and explanatory analysis reveals the optimal unobserved components model. The separate analysis of each dimension may reveal different underlying developments. The impact of meteorological, socioeconomic, legislative, and calendar factors on exposure, accident risk, and fatality risk is investigated. The analysis indicates that, although for each dimension the same basic components are available, the optimal model of each dimension has its unique structure of descriptive components and significant variables. Precipitation and snow enhance accident risk, while temperature plays a significant role for exposure. Fatality risk decreases in case of an extra day with precipitation and was significantly affected by the child restraint law. The economic indicators mainly affect accident risk. When the three models are brought back together, the number of highway deaths between 1993 and 2001 is well reconstructed. |
| 总页数： | Transportation Research Record: Journal of the Transportation Research Board. 2006. (1950) pp1-8 (3 Fig., 1 Tab., 37 Ref.) |
| 报告类型： | 科技报告 |
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