Adaptive Stability Control Using Camera and GPS Road Friction Data
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Solution Overview
Problem
Existing systems for electronic stability control in vehicles do not effectively adapt to varying weather and road conditions, leading to potential instability and safety risks.
Innovation Solution
A system that utilizes video data from a camera and GPS data to determine road conditions and weather, adjusting vehicle operation by switching between standard and restrictive thresholds for stability control, including engine and brake control, to ensure safe operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If electronic stability control uses fixed thresholds for vehicle operation, then the control system is simple and reliable, but it cannot adapt to varying weather and road conditions leading to potential instability
Solution Approach 1:
The stability control system dynamically adjusts thresholds based on real-time camera analysis of road conditions and weather. The system transitions from static fixed thresholds to dynamic adaptive thresholds that automatically modify control parameters according to detected conditions such as wet roads, fog, or adverse weather, resolving the contradiction between adaptability and complexity
Solution Approach 2:
The system incorporates feedback loops where camera data is continuously processed to detect road and weather conditions, which then feed back to adjust the stability control thresholds. This closed-loop feedback mechanism enables the system to adapt to varying conditions while maintaining manageable complexity through automated decision-making algorithms
2Reliability
If the system processes video data and GPS data in real-time to determine road conditions, then vehicle stability is enhanced, but computational resources and processing time increase
Solution Approach 1:
The system pre-processes and categorizes road conditions and weather patterns based on historical data and real-time camera input. By preparing threshold adjustments in advance based on detected conditions, the system reduces real-time processing requirements while maintaining high reliability in stability control responses
Solution Approach 2:
The patent replaces complex real-time computational analysis with pattern recognition algorithms that match camera-derived images against pre-established road condition templates. This substitution reduces computational burden and processing time while maintaining accurate condition detection and reliable stability control
Data Source
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AI summary
An adaptive control adjusts thresholds in a vehicle stability control in response to video camera data and GPS weather data indicating that vehicle road conditions are not ideal. Video data determines mue (coefficient of friction) and type of road. GPS weather data includes temperature, visibility, precipitation and wind velocity, along with vehicle location. A human machine interface manually overrides the adaptive control in response to a user input.