Vehicle Collision Detection Using Image Comparison
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Solution Overview
Problem
Existing vehicle collision sensors are not always reliable, as they may fail to detect serious collisions from all directions and can issue false notifications due to braking or centrifugal forces, and they often send unnecessary alerts, wasting resources and causing trouble.
Innovation Solution
A vehicle collision event announcing system that includes an image capturing unit, a collision sensing unit, and a feature image comparison unit, which captures and compares vehicle images before and after a potential collision to determine if damage has occurred, thereby confirming the severity of the collision and preventing unnecessary alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If collision sensors are used to detect collisions, then collision detection capability is provided, but false notifications occur due to braking forces and centrifugal forces
Solution Approach 1:
The patent combines multiple sensing units (collision sensor, brake sensor, steering sensor) and image capturing units into an integrated system. The processor analyzes data from all sensors simultaneously and compares images before and after potential collisions, requiring consistent evidence across multiple sources before triggering an alarm, thereby reducing false notifications while maintaining detection reliability
Solution Approach 2:
The system continuously monitors sensor inputs and image data, comparing pre-collision and post-collision states. The processor provides feedback by analyzing whether the detected event matches the actual collision scenario based on image changes and sensor consistency, allowing the system to correct false detections and maintain reliable operation
2Measurement precision
If collision sensors trigger alarms for all detected forces, then collision detection sensitivity is improved, but unnecessary notifications increase wasting social resources
Solution Approach 1:
The system merges data from multiple sensor types (collision, brake, steering) and image capturing units, requiring corroboration across all sources. This multi-source verification maintains high detection sensitivity for actual collisions while filtering out false alarms from braking or steering maneuvers, thereby preventing waste of social resources on unnecessary notifications
Solution Approach 2:
The system captures images before a potential collision event occurs and stores them for later comparison. When a sensor detects a potential collision, the system already has the pre-collision image ready for immediate comparison with the post-collision image, enabling rapid verification and preventing unnecessary resource allocation to false alarms
3Adaptability or versatility
If collision sensors detect forces from all directions, then detection coverage is improved, but the system becomes more complex
Solution Approach 1:
The patent employs a multi-functional integrated system where image capturing units serve dual purposes: documenting collision evidence and providing pre-collision baseline data. The processor performs multiple functions including analyzing sensor data, comparing images, determining collision validity, and controlling alarm activation. This multi-functionality achieves comprehensive detection coverage while managing system complexity through unified processing
Data Source
AI summary
A vehicle collision event announcing system is provided. The system includes: a processor; an image capturing unit, coupled to the processor, for capturing vehicle images from at least a part of the vehicle; a collision sensing unit, for detecting whether the vehicle is running into a probable collision event; and a feature image comparison unit, coupled to the processor, for when the collision sensing unit detects the probable collision event, comparing the vehicle images before and after the probable collision event to determine whether the probable collision event is a real collision event which causes damage to the vehicle and/or the seriousness of the damage of the real collision event.