Compressed Road Gradient Prediction for Long-Range Vehicle Altitude
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Solution Overview
Problem
Existing altitude prediction methods for vehicles fail to accurately predict altitudes over long distances due to the inefficiency of storing and transmitting large amounts of altitude information, which can lead to inadequate power management and reduced fuel efficiency.
Innovation Solution
A method for predicting altitudes by estimating the gradient of forward driving using compressed road information, which involves generating two-dimensional and three-dimensional compressed road information through numerical optimization based on original road and altitude data, allowing for accurate prediction of front gradient information over long distances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If large amounts of original altitude information are stored and transmitted, then prediction accuracy is improved, but data storage efficiency and transmission efficiency deteriorate
Solution Approach 1:
The patent extracts only the essential gradient information from the complete altitude data through numerical optimization. Instead of storing and transmitting all original altitude points, the system calculates gradient values that capture the critical altitude changes needed for power management, significantly reducing data quantity while preserving prediction accuracy.
Solution Approach 2:
The patent transforms the raw altitude data into gradient parameters through numerical optimization. By changing the representation from absolute altitude values to gradient changes, the system achieves more efficient data compression while maintaining the predictive capability needed for power management decisions.
2Duration of action of moving object
If gradient information is predicted over long distances, then power management capability is improved, but data transmission burden increases
Solution Approach 1:
The patent extracts only the necessary gradient information for long-distance prediction through numerical optimization. By calculating gradient values at key intervals rather than transmitting continuous altitude data, the system extends prediction range while minimizing transmission energy consumption.
3Quantity of substance
If compressed road information is used, then data storage efficiency is improved, but information completeness may deteriorate
Solution Approach 1:
The patent transforms altitude information into gradient parameters through numerical optimization. This parameter transformation maintains the essential predictive information needed for power management while achieving significant data compression, preventing information loss despite reduced data quantity.
Solution Approach 2:
The gradient calculation acts as an intermediary that preserves the essential altitude information in a compressed form. Rather than directly storing or transmitting raw altitude data, the system uses gradient values as an intermediate representation that maintains information completeness for prediction purposes while reducing data storage requirements.
Data Source
AI summary
A method and apparatus for predicting altitude using compressed road information are provided. The method includes generating two-dimensional compressed road information associated with a designated reference point of each of one or more sections of a road distinguished in a predetermined manner based on two-dimensional original road information. The method also includes generating compressed altitude information corresponding to the designated reference point based on map information including original altitude information. The method additionally includes predicting front gradient information based on three-dimensional compressed road information having the two-dimensional compressed road information and the compressed altitude information, a location of a vehicle, and a driving direction of the vehicle.