Vehicle Cockpit Screen Interaction for Low-Latency Coordinated Control
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Solution Overview
Problem
Existing vehicle cockpit control systems face high costs and latency issues due to the need for data interfaces and artificial intelligence-based object detection technologies to manage ambient lighting and other sensory interactions, which are resource-intensive and require extensive training data.
Innovation Solution
A method and system that acquires user interaction directly from the application screen within the vehicle cockpit, using templates and user interaction data to determine scenarios and objects without relying on external interfaces or AI-based object detection, enabling independent control of the vehicle cockpit environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If AI-based object detection technology is used to control ambient lighting and sensory interactions, then the system can achieve intelligent and personalized user experience, but the cost and processing time increase significantly
Solution Approach 1:
The system performs preliminary action by capturing and analyzing the application screen content in advance, extracting scenario and object information directly from the visual display before user interaction occurs. This allows the vehicle cockpit control system to pre-process and understand the context, enabling rapid response when user interaction is detected without requiring real-time AI object detection
Solution Approach 2:
The invention extracts only the necessary information (scenario and object) directly from the application screen content using template matching and image processing techniques, rather than using comprehensive AI object detection. This extraction approach removes unnecessary computational overhead while retaining the essential information needed for coordinated control
2Measurement precision
If external data interfaces and AI models are used for scenario and object determination, then the system can achieve accurate object detection, but the system complexity and cost increase
Solution Approach 1:
The system creates a simplified copy of the object detection process by using template matching against the application screen content. Instead of deploying complex AI models, it captures the screen, extracts relevant visual information, and matches it against predefined templates to determine scenarios and objects, achieving sufficient accuracy with much lower complexity
Solution Approach 2:
The application screen itself serves as an intermediary that carries information about the scenario and objects. Rather than directly using AI models to detect objects in the real world, the system uses the screen display as a mediator that already contains the contextual information, making direct analysis of the screen content sufficient for determination
3Adaptability or versatility
If AI-based object detection is implemented in the vehicle cockpit control system, then the system can provide coordinated control based on user operations, but the resource consumption and cost increase
Solution Approach 1:
The system practices self-service by utilizing the existing application screen content that is already being displayed in the vehicle cockpit. Instead of deploying additional sensors or external detection systems, it analyzes the information already present on the screen, thereby achieving coordinated control capability without additional resource consumption
Data Source
AI summary
The present disclosure relates to a method for vehicle cockpit coordinated control, a device, a medium, and a computer program product. The method comprises: acquiring user interaction for an application screen displayed within the vehicle cockpit; and triggering the vehicle cockpit coordinated control on the basis of the application screen and the user interaction.