Park Juneyoung, Abdel-Aty Mohamed, Wang Jung-Han
Department of Civil, Environmental and Construction Engineering, University of Central Florida Orlando, FL 32816-2450, United States.
Department of Civil, Environmental and Construction Engineering, University of Central Florida Orlando, FL 32816-2450, United States.
Accid Anal Prev. 2017 Apr;101:78-86. doi: 10.1016/j.aap.2017.02.006. Epub 2017 Feb 10.
This study evaluated the safety performance of pavement resurfacing projects on urban arterials in Florida using the observational before and after approaches. The safety effects of pavement resurfacing were quantified in the crash modification factors (CMFs) and estimated based on different ranges of heavy vehicle traffic volume and time changes for different severity levels. In order to evaluate the variation of CMFs over time, crash modification functions (CMFunctions) were developed using nonlinear regression and time series models. The results showed that pavement resurfacing projects decrease crash frequency and are found to be more safety effective to reduce severe crashes in general. Moreover, the results of the general relationship between the safety effects and time changes indicated that the CMFs increase over time after the resurfacing treatment. It was also found that pavement resurfacing projects for the urban roadways with higher heavy vehicle volume rate are more safety effective than the roadways with lower heavy vehicle volume rate. Based on the exploration and comparison of the developed CMFucntions, the seasonal autoregressive integrated moving average (SARIMA) and exponential functional form of the nonlinear regression models can be utilized to identify the trend of CMFs over time.
本研究采用前后观测法评估了佛罗里达州城市主干道路面重铺工程的安全性能。路面重铺的安全效果通过碰撞修正因子(CMF)进行量化,并根据不同严重程度下重型车辆交通量和时间变化的不同范围进行估算。为了评估CMF随时间的变化,利用非线性回归和时间序列模型开发了碰撞修正函数(CM函数)。结果表明,路面重铺工程降低了碰撞频率,总体上发现对减少严重碰撞更具安全效果。此外,安全效果与时间变化之间的一般关系结果表明,重铺处理后CMF随时间增加。还发现,重型车辆流量率较高的城市道路路面重铺工程比重型车辆流量率较低的道路更具安全效果。基于对所开发的CM函数的探索和比较,非线性回归模型的季节性自回归积分移动平均(SARIMA)和指数函数形式可用于识别CMF随时间的趋势。