Vehicle Access Gesture Control False Trigger Reduction
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Solution Overview
Problem
Modern vehicle systems that control power-operated components like liftgates face challenges in distinguishing intentional activating gestures from false triggers due to variations in human motion, size, and environmental factors, leading to accidental activations.
Innovation Solution
A vehicle computing system that uses a combination of sensors, including proximity sensors, cameras, and data collectors to identify and authenticate user gestures by comparing image data against stored parameters, reducing false triggers through robust data processing and calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a motion sensor and proximity sensor are used to detect activating gestures, then the system can control power-operated access components, but the system produces false triggers due to variations in human motion and environmental factors
Solution Approach 1:
The patent combines multiple sensors (motion sensor, proximity sensor, and camera) to create a multi-modal detection system. The motion sensor detects foot motion, the proximity sensor detects key fob presence, and the camera captures image data of the gesture, collectively providing more reliable gesture authentication while reducing false triggers.
Solution Approach 2:
The system processes image data from the camera and compares it against stored gesture parameters to authenticate whether a detected motion corresponds to an intentional activating gesture. This feedback mechanism allows the system to distinguish between intentional gestures and false triggers by verifying gesture characteristics.
2Adaptability or versatility
If the system accommodates a wide range of intentional gestures from different users, then it can work with various foot motions and user characteristics, but it becomes difficult to discriminate intentional gestures from false triggers
Solution Approach 1:
The system stores multiple gesture parameters in memory that represent different intentional gestures from various users. These parameters include characteristics such as motion patterns, proximity distances, and image features. By comparing real-time sensor data against these stored parameters, the system can accommodate user variations while maintaining authentication accuracy.
Solution Approach 2:
The patent adds image data capture as an additional dimension to gesture detection. Instead of relying solely on motion detection, the camera captures visual information about the gesture, providing another layer of data for comparison against stored parameters. This dimensional addition enhances the system's ability to distinguish intentional gestures from false triggers.
Data Source
AI summary
A vehicle system includes a computer in a vehicle, and the computer includes a processor and a memory. The computer is configured to determine that a user is located within an operating region for an access component of the vehicle, collect image data of an object in a gesture path for the access component, compare the object image data to activating gesture parameters, and operate the access component when the comparison identifies an activating gesture.