期刊名称：International Journal of Statistics and Applications
印刷版ISSN：2168-5193
电子版ISSN：2168-5215
出版年度：2019
卷号：9
期号：1
页码：21-28
DOI：10.5923/j.statistics.20190901.03
语种：English
出版社：Scientific & Academic Publishing Co.
摘要：Wet pavement crashes tend to occur at a higher rate than crashes when the roadway surface is dry, when accounting for the number of hours of actual rainfall and amount of time the roadways would be wet. This study examines data from Alabama for non-intersection, or segment crashes, on the state system against a variety of potential variables hypothesized to contribute to wet pavement crashes. Models were developed relating the number of crashes (severe and non-severe) by pavement condition (wet pavement and dry pavement) at different traffic intensity levels (not congested, moderately congested and highly congested) to a collection of roadway, pavement and traffic variables. The results indicate that for severe crashes on congested roadways with dry pavement, the main variable that can be used to predict crashes is segment length, essentially an exposure variable, indicating that the pavement characteristics have no impact. In addition, the exposure variable is nearly one indicating that the length of the roadway has almost a direct relationship to crash number. However, for non-severe crashes in congested locations and all crashes in either moderate and no congestion there are a variety of factors that impact the number of crashes. The results show that there are certain roadway elements such as macrotexture, the level of friction between the roadway and the tires that allows for stopping, and International Roughness Index, a measure of the level of cracking in the pavement, which contribute to the number of crashes. These values are monitored by transportation agencies on a recurring interval and the impact of exceeding certain thresholds can be used to incorporate crash reductions into a safety maintenance strategy. Other variables that could not be improved through maintenance activities but have an influence on the number of crashes are presented.
