Winter highway maintenance operations are performed to ensure safe driving conditions during snow events. However, variability in truck speeds and changing weather conditions limit the ability of practitioners to optimize plans in a timely manner. The time required to manually adjust plans in response to actual conditions prevents modifications from being completed and applied during the operation phase. To overcome this challenge, a data-driven, near real-time simulation approach to assist short-term planning of winter highway maintenance operations is proposed. The approach integrates dynamic project data to quickly (1) predict required truck fleet size for upcoming operations, (2) devise operation schedules, and (3) recommend operation routes. Functionality and validity of the proposed approach was demonstrated using both an illustrative example and a real case study. The proposed approach was found capable of rapidly generating operation plans that were more efficient than current practice.
|Number of pages||12|
|Journal||Journal of Computing in Civil Engineering|
|Early online date||8 Jul 2021|
|Publication status||Published - Sep 2021|