Abstract
The objective of this study is to investigate and evaluate the effects of weather information (in terms of accuracy and frequency of usage) on winter maintenance costs. To this end, a general winter maintenance cost model is presented, and then a methodology combining sensitivity analysis and neural network methods is proposed. Sensitivity analysis is used to identify the key input variables that significantly affect the output variable. The proposed method and cost model are applied to a case study of the Iowa winter maintenance operations. The results from the case study show that the lane miles of roadway maintained by maintenance units have the most important impact on winter maintenance costs; also, the increased use and accuracy of weather information can reduce costs. Finally, a benefit–cost analysis shows that the use of accurate weather information is a promising way to reduce winter maintenance costs.