Research and Development Toward the Unmanned Operation of Snow Removal Machines and Delivery Vehicles in Snow-Covered Environment

Summary

This research presents the development of technologies to support the automation of snow removal machinery in cold and snowy environments, with particular emphasis on sidewalk maintenance. To address labour shortages and improve operational safety, the researchers developed a real-time pedestrian detection and warning system intended to reduce reliance on human safety guides during snow removal operations. The system combines thermal imaging and 3D LiDAR to detect pedestrians under low-light and snowy conditions, using sensor fusion and onboard real-time processing. The reported results demonstrate the technical feasibility of pedestrian detection in challenging winter environments. The research contributes to the development of safer, more automated winter maintenance operations and provides a foundation for future unmanned snow removal equipment.

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