Caching Map Data for Vehicle Range Projection

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Solution Overview

Problem

Current methods for determining a vehicle's range are inaccurate, and electric vehicle operators face challenges in locating charging stations and assessing if they can reach them due to limited infrastructure.

Innovation Solution

A system that receives vehicle data to determine a polygon indicating the range it can travel on available pathways until fuel is exhausted, using a storage element, map evaluation, and processing to project the range, and provides a user-friendly map-based interface.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If map data is retrieved and processed in real-time for range projection, then the accuracy of range estimation is improved, but the computational time and processing complexity increase

Engineering Contradiction:
Improverange estimation accuracyVSAvoidcomputational time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The patent pre-processes map data during off-line periods to create a cached representation of the geographic area. This cached map data includes pre-calculated path information and geographic features that can be quickly retrieved during real-time range projection operations, eliminating the need for time-consuming real-time map processing while maintaining accuracy.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent divides the geographic area into discrete map tiles that can be independently processed and cached. This segmentation allows the system to retrieve only the specific tiles needed for the current vehicle position and range calculation, reducing the amount of data that needs to be processed in real-time while maintaining comprehensive coverage for accurate range estimation.

Inventive Principle:
Principle #1Segmentation

2Measurement precision

If comprehensive map data is retrieved for accurate range projection, then the precision of range determination is improved, but the data retrieval time and system complexity increase

Engineering Contradiction:
Improverange determination precisionVSAvoidsystem complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The system performs preliminary evaluation of map data during off-line periods, pre-processing geographic information into a cached format that is optimized for real-time queries. This pre-evaluation creates a simplified data structure that maintains all necessary geographic features and path information while reducing the computational complexity of real-time range projection operations.

Inventive Principle:
Principle #10Preliminary action

3Measurement precision

If real-time map evaluation is performed for range projection, then the accuracy of vehicle range prediction is improved, but the processing time increases

Engineering Contradiction:
Improvevehicle range prediction accuracyVSAvoidprocessing speed
Core Design Contradiction:
Measurement precisionVSProductivity

Solution Approach 1:

The patent implements an off-line map evaluation process that pre-processes geographic data and caches the results for rapid retrieval during real-time operations. This approach separates the computationally intensive map evaluation from the time-critical range projection calculation, allowing accurate range predictions to be generated quickly by querying pre-evaluated map data rather than performing real-time map analysis.

Inventive Principle:
Principle #10Preliminary action

Data Source

PatentUS10151596B2Caching map data for efficient vehicle range projection
Publication Date: 2018.12.11 ABALTA TECHNOLOGIES INC
  • US10151596B2 patent drawing
  • US10151596B2 patent drawing
  • US10151596B2 patent drawing

AI summary

An automated method of caching map data for vehicle range projection using a computer system including a processor and a storage includes: retrieving, from the storage to the processor, data corresponding to an area of a map, wherein the retrieved data includes multiple links and multiple nodes; dividing, at the processor, the area of the map into a set of tiles; associating, at the processor, a portion of the retrieved data with each tile in the set of tiles; evaluating, at the processor, each particular link to determine whether the particular link spans multiple tiles from the set of tiles; and dividing, at the processor, the particular link into at least two sub-links if the particular link spans multiple tiles by adding a node at each point the particular link crosses a boundary between two tiles.