Autonomous Snowplow Route Planning Using Snow Movement Simulation
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Solution Overview
Problem
Current winter service vehicles rely on human expertise for route planning, which can be inefficient and costly, as they do not optimize routes based on snow movement and distribution of remediation materials, leading to suboptimal service coverage and increased operational costs.
Innovation Solution
Autonomous winter service vehicles equipped with controllers that simulate snow movement and discretize areas into cells to plan optimal routes for plowing and remediation material distribution, minimizing costs such as time, fuel, and vehicle wear, while ensuring effective area clearance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If human operators drive winter service vehicles, then route planning relies on human expertise and experience, but operational costs increase and service optimization is limited
Solution Approach 1:
The system enables autonomous vehicles to self-determine optimal routes by discretizing the service area into cells, simulating snow movement through computational models, and automatically planning paths that minimize operational costs while maximizing service efficiency, eliminating dependence on human operators
Solution Approach 2:
The system performs preliminary simulation of snow movement and route optimization before actual plowing operations begin, allowing the vehicle to pre-determine the most efficient paths based on predicted snow behavior and area characteristics
2Reliability
If traditional route planning is used without snow movement simulation, then vehicle operation is simpler, but service coverage is suboptimal and snow clearance effectiveness is reduced
Solution Approach 1:
The service area is divided into discrete cells that can be individually analyzed for snow accumulation and characteristics, allowing the system to simulate snow movement through each cell and optimize routes based on localized conditions while maintaining manageable computational complexity
Solution Approach 2:
The system creates a virtual simulation model that copies and replicates snow movement behavior, allowing route optimization to be performed on the simulated model before executing the actual plowing operation, thereby improving service coverage without requiring complex real-time adjustments
Data Source
AI summary
An autonomous vehicle can comprise winter servicing equipment, such as a snowplow, salt spreader, etc. A controller can be supported by the vehicle and can be operatively coupled thereto. The controller can be configured to control the vehicle to autonomously move through an area along a planned route to effect servicing (e.g., snow removal or remediation) of the area. For example, the controller can be configured to discretize the area into a plurality of cells and to determine a quantity of snow in each cell. The route through the area can be planned by the controller based at least in part on simulated movements of the snow quantities in the cells.