Road Surface Friction Estimation Using Multi-Source Reliability
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Solution Overview
Problem
Existing road surface friction coefficient estimation methods for vehicles face challenges in accurately estimating friction coefficients during steady driving conditions, where vehicles move at constant speed, as they lack reliable data for accurate estimation.
Innovation Solution
A road surface friction coefficient estimation apparatus and method that combines vehicle information and external information to estimate friction coefficients, using multiple estimators and reliability degree calculations to select the most reliable estimation, incorporating vehicle dynamics and external conditions like weather and road state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only vehicle information is used for estimation, then the estimation can be performed using onboard data, but the estimation accuracy deteriorates during steady driving conditions
Solution Approach 1:
The patent combines vehicle information (from onboard sensors) and external information (from external devices such as infrastructure or other vehicles) to estimate the friction coefficient. By merging multiple information sources, the system achieves high estimation accuracy across various driving conditions including steady driving, where single-source estimation fails.
2Measurement precision
If multiple estimation methods are used, then the estimation accuracy improves, but the system complexity increases
Solution Approach 1:
The patent introduces a reliability calculation unit and a selection unit as intermediaries between multiple estimation methods and the final output. The reliability calculation unit evaluates the trustworthiness of each estimation result based on driving conditions, and the selection unit chooses the most reliable estimation. This intermediary structure manages complexity by systematically selecting among multiple methods rather than combining all of them simultaneously.
3Measurement precision
If external information is acquired from outside the vehicle, then the estimation accuracy improves, but the information acquisition complexity increases
Solution Approach 1:
The patent designs the external information acquisition unit to universally obtain various types of information (road condition data, weather information, traffic conditions) from multiple external sources. This multi-functional capability allows the system to adapt to different driving conditions and select the most relevant information, improving estimation accuracy without requiring separate specialized systems for each information type.
Data Source
AI summary
A road surface friction coefficient estimation apparatus for a vehicle includes: a first estimator; a second estimator; and a third estimator. The first estimator estimates a first road surface friction coefficient on a basis of a vehicle information acquired from the vehicle. The second estimator estimates a second road surface friction coefficient on a basis of an external information acquired from an outside of the vehicle. The third estimator estimates a road surface friction coefficient from the first road surface friction coefficient and the second road surface friction coefficient on a basis of a first reliability degree and a second reliability degree, the first reliability degree indicating a reliability of the first road surface friction coefficient, the second reliability degree indicating a reliability of the second road surface friction coefficient.