Dynamic Tile Caching for Vehicle Visualization Accuracy
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Solution Overview
Problem
Current tile caching systems in vehicle operations, particularly in agricultural and construction vehicles, face limitations in providing real-time, high-resolution visualizations due to hardware constraints and outdated tile expiration methods, which affect operational efficiency and accuracy.
Innovation Solution
Implementing dynamic tile caching techniques that tag tiles with vehicle and sensor data, allowing tiles to expire and be reconstructed based on operating conditions, such as location and speed, rather than time, and combining raster and vector information to enhance visualization with reduced computing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional time-based tile caching is used, then system simplicity is maintained, but visualization accuracy and timeliness deteriorate due to outdated cache expiration methods
Solution Approach 1:
The patent changes the tile expiration parameter from time-based to condition-based (location and speed thresholds). Tiles are invalidated when the vehicle moves a specific distance or speed threshold is exceeded, ensuring visualization accuracy reflects actual operating conditions rather than arbitrary time intervals.
Solution Approach 2:
The system automatically determines when tiles need updating by monitoring vehicle location and speed data. The caching system self-regulates based on operational conditions without requiring manual intervention or complex centralized control, maintaining simplicity while improving accuracy.
2Measurement precision
If high-resolution real-time visualizations are provided, then operational accuracy is improved, but hardware resource consumption increases beyond vehicle system capabilities
Solution Approach 1:
The system dynamically adjusts tile caching behavior based on vehicle speed and location changes. During high-speed travel, fewer tiles are updated, while during slow operations, more frequent updates occur. This dynamic approach provides high-resolution visualizations only when operationally necessary, reducing overall hardware resource consumption.
Solution Approach 2:
The system applies different caching strategies to different spatial regions based on vehicle activity. Areas where the vehicle is currently operating receive high-resolution updates, while distant areas use coarser caching. This local differentiation provides operational accuracy where needed while conserving hardware resources in inactive regions.
3Loss of time
If tile caching is updated frequently to maintain real-time accuracy, then visualization timeliness is improved, but system processing load increases
Solution Approach 1:
The system implements periodic tile updates triggered by vehicle location and speed thresholds rather than continuous updating. Tiles are refreshed periodically when the vehicle moves significant distances or exceeds speed thresholds, providing timely visualizations without the constant processing load of continuous updates.
Data Source
AI summary
A system includes a vehicle system. The vehicle system includes at least one sensor and a mapping server system communicatively coupled to a mapping client system. The mapping server system is configured to receive a signal from the at least one sensor; update a mapping tile disposed in a tile cache to derive an updated mapping tile based on the signal; and visually display the mapping tile to an operator of the vehicle system.