In-Vehicle Gesture Detection With Safety Threshold Validation
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Solution Overview
Problem
Current vehicle control systems face challenges in accurately detecting gestures within vehicles to ensure safe and reliable operation, particularly in distinguishing valid gestures from invalid ones and managing transport operations within safety thresholds.
Innovation Solution
A method and system that utilize sensors to detect movements within vehicles, determine if they constitute valid gestures, and perform corresponding actions, while considering the current transport operation level and occupant status, using a decentralized database and blockchain technology for authorization and data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If gesture detection is implemented in vehicle control systems, then ease of operation is improved, but reliability deteriorates due to difficulty in distinguishing valid gestures from invalid ones
Solution Approach 1:
The gesture recognition process is segmented into multiple independent analysis dimensions: movement trajectory analysis, temporal pattern analysis, spatial location analysis, and confidence threshold analysis. Each dimension independently evaluates the detected movement and contributes to the overall gesture validation decision, improving reliability by breaking down the complex recognition task into manageable, verifiable components.
Solution Approach 2:
The system implements a feedback mechanism where the confidence score from gesture analysis feeds back into the control decision process. When the confidence score falls below the threshold, the system provides feedback by canceling the gesture-triggered action and maintaining the current state, allowing the user to reattempt the gesture with proper form. This feedback loop ensures that only high-confidence gestures execute commands, improving reliability while maintaining ease of operation.
2Productivity
If multiple transport operations are allowed simultaneously, then productivity is improved, but safety deteriorates due to potential exceeding of safe operation levels
Solution Approach 1:
The system performs a preliminary safety assessment before executing any gesture-triggered action. The safety threshold evaluation is conducted in advance by comparing the proposed action against the current transport operation level. This preliminary check prevents unsafe operations from being executed, while still allowing multiple productive operations to proceed when they remain within safe thresholds.
Solution Approach 2:
The system implements a preliminary anti-action mechanism that actively prevents unsafe operations before they can occur. When a detected gesture would cause the transport operation level to exceed the safety threshold, the system preemptively cancels the action and maintains the current safe state. This anti-action approach ensures safety is preserved while allowing maximum productive operations within safe boundaries.
3Reliability
If comprehensive gesture validation is performed, then reliability is improved, but device complexity increases due to multiple validation checks
Solution Approach 1:
The validation system is designed as a universal multi-functional module that handles multiple types of gestures (hand gestures, head gestures, foot gestures) across multiple transport operations (acceleration, braking, navigation, climate control) using a unified framework. The same validation logic, confidence threshold mechanism, and safety threshold evaluation are applied universally to all gesture types and operations, reducing overall system complexity despite comprehensive validation.
Data Source
AI summary
An example operation includes one or more of detecting a movement in a transport, determining whether the movement includes a gesture definition, when the movement includes a gesture definition, identifying a gesture associated with the gesture definition, and performing an action, via the transport, corresponding to the identified gesture.