Driver Override Feedback for Personalized Driving Assistance
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Solution Overview
Problem
Existing driving assistance functions in vehicles are not tailored to individual driver preferences, leading to unnecessary activation or deactivation of functions, which can disrupt the driving experience.
Innovation Solution
A recommendation system that detects driver override operations, selects appropriate driving assistance functions based on the override scene, and proposes activation or deactivation of these functions to the driver, including adjustments to the assistance content for better alignment with the driver's intentions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If driving assistance functions are uniformly activated or inactivated, then the system operation is simplified, but the driver's individual needs and preferences are not met
Solution Approach 1:
The system detects override operations performed by the driver on driving assistance functions and uses this feedback to generate personalized recommendations. The operation detection unit monitors when drivers manually override automated functions, and this information is fed back to the recommendation generation unit to tailor future recommendations to the specific driver's preferences and behaviors.
Solution Approach 2:
The system proactively generates recommendations for driving assistance function activation or deactivation based on detected override patterns before the driver needs to manually adjust settings. By analyzing override operations in real-time and generating preliminary recommendations, the system anticipates driver preferences and suggests optimal configurations in advance.
2Device complexity
If driving assistance functions are activated based on uniform criteria, then the activation logic is simplified, but unnecessary functions may be activated or necessary functions may be inactivated
Solution Approach 1:
The system uses feedback from detected override operations to improve the reliability of function activation recommendations. By monitoring when drivers override specific functions and incorporating this information into personalized recommendation profiles, the system learns which functions are actually needed by each driver, thereby reducing inappropriate activations and deactivations.
Solution Approach 2:
The system changes the parameters of recommendation generation from uniform, one-size-fits-all criteria to personalized parameters based on individual driver behavior patterns. By analyzing override operations and creating driver-specific profiles, the system adapts activation recommendations to match each driver's unique preferences and driving style, improving overall appropriateness.
3Measurement precision
If the system monitors and analyzes driver operations to provide personalized recommendations, then the recommendation accuracy is improved, but the system complexity increases
Solution Approach 1:
The system extracts only the essential information needed for personalization—specifically, override operation data—from the complex stream of driver interactions. By focusing on extracting and analyzing only the relevant override events rather than all possible driver actions, the system achieves accurate recommendations while minimizing the complexity of data processing and system architecture.
Data Source
AI summary
A recommendation system includes an operation detection unit configured to detect an override operation by a driver; a scene acquisition unit configured to acquire an override scene when the override operation is detected; a function selection unit configured to select a driving assistance function corresponding to the override scene among driving assistance functions not activated, based on the acquired override scene; and a proposal unit configured to propose to the driver whether or not to activate the selected driving assistance function.