Parallel Tile Processing for Vehicle Navigation Response Time
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Solution Overview
Problem
Existing navigation systems face prolonged response times when calculating and displaying a vehicle's travelable range on a map, particularly when connected to cloud servers via networks, due to the need to process entire map images at once.
Innovation Solution
The method involves dividing the map image into tiles based on zoom levels, acquiring and processing requests for each tile in parallel, extracting planimetric feature information, calculating geographic features, and determining reachability based on energy information, thereby reducing response time by processing each tile independently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the entire map image is processed at once to calculate travelable range, then the completeness of the travelable range display is improved, but the response time is prolonged
Solution Approach 1:
The map image is divided into multiple tiles, and the travelable range calculation is performed separately for each tile. This segmentation allows parallel processing of different tiles, reducing the overall response time while maintaining the completeness of the travelable range display across the entire map area.
2Loss of time
If parallel processing of multiple tiles is implemented, then the response time is shortened, but the system complexity increases
Solution Approach 1:
The system divides the map into tiles and processes each tile independently in parallel. This segmentation enables the use of standard parallel computing techniques and existing tile-based map storage formats, implementing parallel processing without requiring complex custom system architecture.
Solution Approach 2:
The parallel processing framework is designed to handle multiple tiles simultaneously using a unified approach. The same calculation logic is applied to each tile, allowing the system to process different regions of the map with a single multi-functional processing unit, reducing overall system complexity.
3Productivity
If only necessary tiles are processed, then the processing efficiency is improved, but the accuracy of geographic feature calculation may be compromised
Solution Approach 1:
The map is divided into tiles that are processed independently. For each tile, the system calculates geographic features only for the specific planimetric features within that tile's boundaries, rather than calculating features for the entire map. This localized calculation maintains accuracy for displayed features while improving processing efficiency.
Solution Approach 2:
The system applies different processing levels to different tiles based on their relevance. Tiles containing planimetric features are processed with full accuracy, while tiles without features require minimal processing. This local quality approach ensures measurement precision is maintained where needed while improving overall processing efficiency.
Data Source
AI summary
An information processing device includes an acquisition unit that acquires a plurality of requests, and a parallel processing unit that executes, in parallel, a plurality of pieces of response processing corresponding to a plurality of acquired requests. In each piece of the response processing, planimetric feature information corresponding to a tile ID included in a request is extracted from a planimetric feature database, a geographic feature amount between a current position and a planimetric feature indicated by the extracted planimetric feature information is calculated based on the extracted planimetric feature information, reachability by a vehicle to the planimetric feature is determined based on the calculated geographic feature amount and remaining energy information, and the determined reachability and the extracted planimetric feature information are output to a display device.