An Economical Snow-melting Approach with Snow and Ice Detection Based on Autonomous Scenarios

In the wake of snowfall, it is crucial to restore safe road passage promptly and efficiently. Considering the timeliness of melting operations, comprehensiveness of melting areas, safety of operating personnel, and rationality of the amount of snow-melting agent, this paper proposes a dynamic spraying approach of snow-melting agent based on snow-melting autonomous vehicle. Firstly, a dynamic calculation model is designed based on real-time recognition of ice or snow covered on the road, which uses the first law of thermodynamics to calculate the required amount of snow-melting agent for specific road segments, especially considering the surrounding thermal supply effect and snow-covering depth predicted by micro-regional weather forecasts within the expected operating period to adjust the amount. Secondly, it coordinates the spraying amount with the operating speed, achieving quantitative and uniform spraying of snow-melting agents on specific road segments. In addition, a novel form of snow removal based on autonomous driving is designed, which can move smoothly on particular road segments in multiple scenarios at a speed that matches the amount of snow-melting agent sprayed. Numerical experiments were conducted on the overall approach to verify its feasibility, adaptability, and economic and environmental sustainability in complex and extensive areas. The proposed approach is beneficial for exploring new fields of uncrewed operations. It promotes safe, efficient, and environmental clearance of ice-covered or snow-covered roads.