| Road safety is important in our daily life. Among all road safety problems, winter road safety has its particularity and importance. The weather of northern China is extremely cold during winter times. The road surface often suffers from snow and frozen problems. Such bad surface condition may increase the possibility of road accidents that risk drivers’ lives. To solve the problems, proper and scientific winter road maintenance should be carried out. Therefore, scientific analysis methods should be applied to examine the impacts of winter road maintenance on road safety.Sufficient and accurate crash data is significant for accident analysis and prediction. In this research, crash data, winter maintenance data and other related road information are all provided by Idaho Transportation Department (ITD). Crash data reduction was performed to identify the crash events in which winter road weather conditions were reported to play a role. Several screening criteria were developed for the data reduction. The weather data e.g. temperature, precipitation were transformed to a winter severity index (WSI) for subsequent analysis. In addition, the crash data were summarized to identify the time-space distribution patterns.A safety performance function was built to explain the relationship between road safety and its explanatory variables. Statistic methods like Poisson Regression Model, Negative Binomial Model, Bayesian Networks and Artificial Neural Networks were considered and finally the Back-Propagation Neural Network (BPNN) was selected for this study. Sensitivity analysis and benefit-cost analysis were also applied for the better understanding of the relationship between safety and winter maintenance operations.At last, Idaho data was used for model calibration.I-90 data and US 12 data were selected for the analysis. Severity analysis and benefit-cost analysis were conducted to evaluate the influence of winter maintenance operations on road safety. |
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