Two-Wheeler Accident Classification Using Roll, Pitch, and Acceleration
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Solution Overview
Problem
Existing methods fail to distinguish between a collision resulting in personal injury and a non-injurious fall of a two-wheeler, such as a bicycle, without direct collision detection.
Innovation Solution
A method involving the integration of acceleration data in orthogonal directions, combined with roll and pitch angle analysis, is used to classify accidents as either collisions with potential injury or non-injurious falls by comparing integration variables against predefined thresholds, and optionally using energy and tilting parameters to differentiate between types of collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple sensors are integrated to detect various parameters (acceleration, rotation, position, etc.), then the reliability and comprehensiveness of accident detection is improved, but the device complexity and cost increase
Solution Approach 1:
The sensor system is segmented into multiple independent sensing units, each dedicated to detecting specific parameters (acceleration, rotation, position, etc.). This segmentation allows for modular design where each sensor can be optimized independently while collectively providing comprehensive accident detection coverage.
Solution Approach 2:
The control unit serves multiple functions: it processes data from all sensor types, performs accident pattern recognition, classifies accident types, and generates appropriate responses. This multi-functionality consolidates what could be separate systems into a single integrated control unit, managing complexity while maintaining comprehensive detection capabilities.
2Measurement precision
If various sensor data are integrated and processed to classify accident types, then the measurement precision and accuracy of accident classification is improved, but the loss of time for data processing increases
Solution Approach 1:
The control unit is pre-programmed with accident patterns and classification algorithms before deployment. When sensors detect an event, the control unit immediately compares sensor data against pre-stored accident patterns, enabling rapid classification without requiring complex real-time analysis of all possible accident scenarios.
Solution Approach 2:
The patent replaces complex mechanical or manual analysis systems with electronic sensor arrays and digital signal processing. The control unit uses electronic pattern recognition algorithms to rapidly classify accidents based on sensor signatures, achieving high precision classification at speeds far exceeding manual or mechanical systems.
3Reliability
If the system provides detailed accident information and notification services, then the usefulness and reliability of the safety system is improved, but the loss of time for communication and notification increases
Solution Approach 1:
The system implements feedback loops where the control unit continuously monitors sensor data, compares it against stored patterns, and immediately triggers notifications when accidents are detected. This feedback mechanism ensures rapid response by automatically initiating notification procedures as soon as an accident pattern is recognized, providing timely safety information without manual intervention delays.
Data Source
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AI summary
The present invention relates to a method for classifying an accident event of a two-wheeled vehicle, in particular a bicycle. The method according to the invention can proceed as an algorithm in a device having an evaluation unit, in order to indicate a collision or falling over of the two-wheeled vehicle to the rider or to a third party by means of information produced and/or transmitted accordingly. The device can be used for a two-wheeled vehicle, such as a bicycle or in particular an electric bicycle. Of course, use for a motorcycle or other single-track vehicle is also possible.