Road Adhesion Coefficient Estimation Using Multi-State Vehicle Data
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Solution Overview
Problem
Existing technologies face challenges in accurately estimating road surface adhesion coefficients, which are crucial for improving the safety of autonomous driving vehicles by providing early warnings for wet and slippery road conditions.
Innovation Solution
A method and apparatus that determine road surface adhesion coefficients by obtaining multiple estimation results based on various vehicle state parameters, selecting relevant results based on the vehicle's traveling work condition, and calculating a final coefficient using weight factors, ensuring accuracy under different conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple estimation results are obtained based on different vehicle state parameters, then the measurement precision of road surface adhesion coefficient is improved, but the device complexity increases
Solution Approach 1:
The patent segments the road surface adhesion coefficient determination into multiple independent estimation paths, each based on different vehicle state parameters (longitudinal acceleration, lateral acceleration, steering angle, wheel speed). Each estimator independently calculates an adhesion coefficient, and then a selection module chooses the most appropriate estimation result based on current driving conditions, thereby improving precision without requiring a completely complex integrated system
Solution Approach 2:
The system dynamically selects which estimation result to use based on real-time driving conditions. The selection module adjusts the source of adhesion coefficient information according to the vehicle's operating state (acceleration, deceleration, steering, cornering), making the system adaptable and accurate across different scenarios without fixed complexity
2Adaptability or versatility
If multiple estimation results are selected and processed based on traveling work condition, then the adaptability to different driving conditions is improved, but the loss of time in processing increases
Solution Approach 1:
The system pre-establishes multiple estimation models and selection criteria for different driving conditions. The selection module has predefined rules for choosing appropriate estimation results based on vehicle state parameters, so no complex real-time analysis is needed - the system simply matches current conditions to pre-determined selection criteria, reducing processing time while maintaining adaptability
Solution Approach 2:
The system continuously monitors vehicle state parameters and provides feedback to the selection module, which adjusts the source of adhesion coefficient information in real-time. This closed-loop feedback mechanism ensures the system adapts to changing driving conditions automatically without requiring manual intervention or complex processing
Data Source
AI summary
A method and an apparatus for determining a road surface adhesion coefficient are provided. The method includes: determining, based on M state parameters of a vehicle on a target road section, M road surface adhesion coefficient estimation results respectively corresponding to the M state parameters, M being an integer greater than 1; selecting N road surface adhesion coefficient estimation results from the M road surface adhesion coefficient estimation results according to a traveling work condition of the vehicle on the target road section, N being a positive integer smaller than or equal to M; and determining a road surface adhesion coefficient of the target road section based on the N road surface adhesion coefficient estimation results.