External Airbag Deployment Using Velocity-Based Detection Zones
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Solution Overview
Problem
Conventional external airbag deployment systems face challenges in precisely timing deployments to maximize shock absorption and prevent false activations, as they require monitoring a large amount of data and struggle to accurately predict collisions.
Innovation Solution
The method sets a detection area based on the full deployment time and relative velocity of an external airbag, selecting a target object by comparing relative velocity, overlap, and Time To External Airbag (TTE), and deploying the airbag when conditions exceed predetermined levels, while prioritizing objects within the detection area and eliminating those outside it.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large detection area is monitored to improve collision prediction accuracy, then collision detection capability is improved, but data processing complexity and system response time deteriorate
Solution Approach 1:
The detection area is segmented into multiple zones based on collision risk levels. High-risk zones require detailed monitoring while low-risk zones use simplified detection, allowing the system to focus computational resources where they are most needed for accurate collision prediction without processing unnecessary data from all areas equally
Solution Approach 2:
Critical collision prediction parameters are extracted from the full set of detected objects. The system identifies and focuses on objects that meet specific collision criteria (relative velocity, overlap, TTE thresholds) rather than processing data from all detected objects, reducing data processing complexity while maintaining prediction accuracy
2Measurement precision
If comprehensive object detection is performed to improve collision prediction, then detection accuracy is improved, but false deployment risk increases
Solution Approach 1:
The system performs preliminary filtering of detected objects against collision criteria before initiating airbag deployment. Objects are pre-screened based on relative velocity, overlap, and TTE thresholds, ensuring that only objects meeting all collision conditions trigger deployment, thereby reducing false deployments while maintaining accurate detection of genuine collision risks
Solution Approach 2:
The system continuously monitors multiple parameters (relative velocity, overlap, TTE) and uses feedback loops to verify collision conditions before deployment. The control unit repeatedly checks whether detected objects satisfy all deployment criteria, providing multiple verification opportunities to prevent false deployment while ensuring genuine collisions are detected
3Manufacturing precision
If multiple parameters are monitored to improve deployment accuracy, then deployment precision is improved, but system response time deteriorates
Solution Approach 1:
The system monitors multiple collision parameters simultaneously but only triggers deployment when a specific combination of thresholds is exceeded. Rather than requiring all parameters to be perfectly measured before action, the system uses predetermined threshold levels for relative velocity, overlap, and TTE that, when collectively satisfied, guarantee accurate deployment timing without requiring exhaustive analysis of every parameter
Data Source
AI summary
Disclosed herein is an external airbag deployment method of determining whether to deploy an external airbag. The method includes setting, by a controller, a detection area that has a predetermined range and tracking physical characteristics of objects entering the detection area. The detection area is a predetermined area located in front of a vehicle and is set by the controller based on a full deployment time of the external airbag and a relative velocity upon colliding with another object.