Vehicle Component Control Using Adaptive Driver Behavior Models
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Solution Overview
Problem
Existing vehicle control systems struggle to adapt to new users or changing driving conditions, leading to inefficient operation of vehicle components due to reliance on historical data that may be inaccurate.
Innovation Solution
A method that compares current user behavior with predicted behavior, forming new user behavior when a threshold difference is detected, and controls vehicle components based on this new behavior, removing historical data to ensure accurate operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the vehicle control system uses historical data to predict user behavior for controlling vehicle components, then the operation of vehicle components can be optimized for the typical user, but the system fails to adapt quickly when a new user or new operating conditions are detected
Solution Approach 1:
The system dynamically adjusts the user behavior model by detecting changes in operating conditions and transitioning from a static historical data-based model to a dynamic adaptive model. When a new user or new operating conditions are detected through comparison with predicted behavior, the system updates the user behavior data structure to reflect current patterns, enabling rapid adaptation without manual reconfiguration.
Solution Approach 2:
The system implements continuous feedback by comparing actual user behavior with predicted behavior based on historical data. This feedback loop detects deviations that indicate new users or changed conditions, triggering an update of the user behavior model. The feedback mechanism enables the system to self-correct and adapt to new operating conditions automatically.
2Reliability
If the vehicle control system continues to use outdated historical data for controlling vehicle components, then the control logic remains simple, but the system controls components at inappropriate times when operating conditions have changed
Solution Approach 1:
The system applies partial action by selectively updating only the necessary portions of the user behavior model when changes are detected. Rather than completely reconfiguring the control system, it updates specific behavior patterns and parameters that are relevant to the new user or conditions, maintaining simplicity while improving reliability.
Solution Approach 2:
The system changes parameters of the user behavior model based on detected operating conditions. By adjusting behavior parameters such as typical operating hours, routes, and component usage patterns to match actual current behavior, the system maintains reliable control decisions without requiring complete system redesign.
Data Source
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AI summary
The present invention relates to a computer implemented method of controlling a vehicle operation of a vehicle, the vehicle comprising vehicle components operable by processing circuitry based on predicted user behaviour, the method comprising receiving, by the processing circuitry, a signal indicative of a current user behaviour for a user currently operating the vehicle; comparing, by the processing circuitry, the current user behaviour with a predicted user behaviour; and when a difference between the current user behaviour and the predicted user behaviour is above a predetermined threshold limit: forming, by the processing circuitry, new user behaviour based on the current user behaviour; and controlling, by the processing circuitry, operation of at least one of the vehicle components using the new user behaviour.