Vehicle Cabin Control Using Scenario-Based Safety Constraints
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Solution Overview
Problem
Existing vehicle cabin systems lack efficient integration and intelligent control of multiple components, requiring manual operation by users, leading to a poor user experience due to time-consuming and laborious adjustments, and simple control logic fails to meet diverse user requirements across different scenarios.
Innovation Solution
A method and apparatus for controlling a vehicle cabin that determines candidate configurations based on current scenarios and user input, adjusting them according to safety constraints and user feedback to ensure safety and comfort, using multimodal data from sensors and machine learning models to generate and verify intelligent cabin atmospheres.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual operation is used to adjust cabin components, then users can control each component individually, but the process becomes time-consuming and laborious
Solution Approach 1:
The system enables self-service control by automatically adjusting cabin components based on scenario recognition and user preferences. The control unit autonomously operates components without requiring manual user intervention, allowing the cabin system to serve itself in achieving optimal configurations for different scenarios.
Solution Approach 2:
The control unit serves multiple functions by integrating scenario recognition, configuration determination, safety verification, and component control capabilities. This multi-functional approach consolidates what would otherwise require separate manual operations into a single automated system that handles diverse cabin control tasks.
2Adaptability or versatility
If simple control logic is used, then the system is easy to implement, but it fails to meet diverse user requirements across different scenarios
Solution Approach 1:
The control system dynamically adapts its behavior based on recognized scenarios and user preferences. Rather than using fixed control logic, the system adjusts its control strategies in real-time according to the current scenario (e.g., driving, parking, sleeping) and individual user preferences, enabling it to meet diverse requirements without requiring overly complex predefined rules for every possible situation.
Solution Approach 2:
The system incorporates feedback mechanisms where user inputs and scenario recognition results continuously inform the configuration determination process. The control unit receives feedback from sensors and user interactions, adjusts cabin component configurations accordingly, and verifies safety constraints, creating a closed-loop control system that adapts to diverse user requirements.
3Ease of operation
If multiple cabin components are controlled simultaneously, then the user experience is enhanced, but the integration and coordination complexity increases
Solution Approach 1:
The control system segments the cabin into multiple controllable zones or component groups (e.g., lighting, temperature, entertainment, seating) that can be independently configured. Each component or component group can be controlled according to scenario-specific requirements, allowing simultaneous control of multiple components while managing complexity through modular segmentation of the control architecture.
Solution Approach 2:
The control unit merges multiple control functions and component management tasks into a single integrated control system. By combining scenario recognition, configuration determination, safety verification, and component control in one unified system, the patent reduces the overall integration complexity that would arise from managing multiple separate control systems for different cabin components.
Data Source
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AI summary
The present disclosure relates to a method and an apparatus for controlling a cabin, a device, a vehicle, and a product. The method comprises determining, on the basis of a current scenario of a vehicle, candidate configurations for a plurality of components within the cabin. The method further comprises adjusting the candidate configurations on the basis of safety constraint information of the vehicle and input information from a user. The method further comprises controlling, on the basis of the adjusted candidate configurations, corresponding components within the cabin. In this way, personalized and unified cabin control can be provided to the user while ensuring safety.