Vehicle Occupant Age Detection for Adaptive Airbag Deployment
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Solution Overview
Problem
Current airbag systems are designed for average adult body sizes and do not account for variations in occupants, posing a risk to children and young drivers, as they cannot be adjusted to ensure safety due to lack of knowledge about the occupants within the vehicle.
Innovation Solution
Implementing a computer vision system using interior cameras to detect and analyze occupants, determining their age and body characteristics to adjust airbag deployment and provide warnings or notifications for safety, utilizing convolutional neural networks and sensor fusion for accurate object detection and classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If air bags are designed for average adult body sizes, then air bag deployment is standardized and simple to manufacture, but safety is compromised for children and small occupants
Solution Approach 1:
The system performs preliminary detection of occupant characteristics (age, size, position) using computer vision and sensors before air bag deployment is triggered. This allows the system to pre-determine the appropriate air bag configuration and deployment parameters, ensuring safety for different occupant types without requiring complex real-time adjustments during deployment
Solution Approach 2:
The air bag system transitions from a static, one-size-fits-all design to a dynamic system that adjusts deployment characteristics based on detected occupant properties. The system modifies deployment force, inflation timing, and air bag activation based on real-time occupant classification, enabling safe operation across diverse occupant populations
2Reliability
If weight-based switches are used to disable passenger air bags, then child safety is improved, but adult safety is compromised when the switch is incorrectly activated
Solution Approach 1:
The system merges multiple detection methods (computer vision, weight sensors, position sensors) into a unified occupant classification system. This combination allows for more accurate determination of occupant type (child vs. adult) and intent (accidental presence vs. intentional placement), reducing false activations while maintaining child safety protection
Solution Approach 2:
The system implements feedback mechanisms where detection results are continuously monitored and used to adjust air bag deployment decisions. The system provides feedback loops that verify occupant characteristics and can alert drivers to potential misconfigurations, ensuring that air bag suppression only occurs when confidently determined to be safe
3Ease of operation
If manual switches are provided for air bag disabling, then occupant control is improved, but system reliability deteriorates due to user error and misuse
Solution Approach 1:
The system replaces manual user operation with automated self-service detection and decision-making. The computer vision and sensor system automatically identifies occupants, determines appropriate air bag configuration, and configures the system without requiring user intervention, thereby eliminating user error while maintaining ease of use through automatic adaptation
4Measurement precision
If computer vision systems are implemented to detect occupant characteristics, then safety is improved through accurate age and size detection, but device complexity increases
Solution Approach 1:
The computer vision system is designed to perform multiple functions simultaneously: detecting occupant presence, determining age group, estimating body size, and identifying seat position. This multi-functionality consolidates what could be multiple separate systems into a single integrated solution, reducing overall complexity while maintaining high measurement precision for safety-critical parameters
Data Source
AI summary
An apparatus includes a capture device and a processor. The capture device may be configured to generate a plurality of video frames corresponding to an interior view of a vehicle. The processor may be configured to perform operations to detect objects in the video frames, detect occupants of the vehicle and seats of the vehicle based on the objects detected in the video frames, determine an age of the occupants based on characteristics of the occupants and select a reaction if the age of the occupant is below a threshold for the seat. The threshold may be based on a location of the seat within the vehicle. The characteristics may be determined by performing the operations on each of the occupants.