Adaptive Motorcycle Accident Detection Threshold
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Solution Overview
Problem
Existing systems for detecting accidents in motorized two-wheelers face challenges due to complex driving and accident dynamics, leading to a higher risk of false alarms and failure to detect actual accidents.
Innovation Solution
A procedure for detecting accidents in power bikes involves reading the recorded power speed, selecting a threshold for sensor values based on the bike's speed, and recognizing an accident when the sensed sensor value reaches or exceeds the selected threshold. This method can be implemented in a control unit using software, hardware, or a combination of both.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed acceleration thresholds are used for accident detection, then the detection system is simple to implement, but false alarms increase due to inability to adapt to varying motorcycle speeds and driving conditions
Solution Approach 1:
The patent applies dynamics by making the acceleration threshold adaptive rather than fixed. The threshold is dynamically adjusted based on the motorcycle's current speed, leaning angle, and pitch angle. This allows the system to distinguish between normal riding variations and actual accidents, reducing false alarms while maintaining detection accuracy across different operating conditions.
Solution Approach 2:
The patent changes the threshold parameter based on multiple operational parameters including speed, lean angle, and pitch angle. By modifying the threshold value according to these changing parameters, the system achieves reliable accident detection without requiring complex hardware modifications, thus improving reliability while keeping the device relatively simple.
2Reliability
If the detection system is highly sensitive to detect all possible accidents, then detection capability improves, but false triggering increases during normal motorcycle maneuvers and wheelies
Solution Approach 1:
The patent employs feedback mechanisms by continuously monitoring multiple parameters (speed, lean angle, pitch angle) and using this information to adjust the detection threshold. This feedback loop allows the system to learn the rider's normal operating patterns and distinguish them from actual accidents, thereby reducing false triggering while maintaining high detection capability for real accidents.
Solution Approach 2:
The patent applies local quality by considering the specific local conditions of each sensor measurement. Instead of using a uniform threshold for all accelerations, the system applies different threshold criteria based on the specific context (e.g., during high-speed maneuvers vs. low-speed parking). This contextualized approach reduces false alarms during normal maneuvers while maintaining sensitivity for actual accidents.
3Reliability
If the motorcycle speed is used to dynamically adjust the detection threshold, then false alarms are reduced, but the computational complexity and processing time increase
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing threshold values in lookup tables or data structures that can be quickly accessed during accident detection. Instead of performing complex real-time calculations, the system retrieves pre-computed threshold values based on current operating conditions, significantly reducing processing time while maintaining the benefits of adaptive threshold adjustment.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The proposed solution effectively detects accidents in power bikes, reducing the likelihood of false alarms and improving the accuracy of accident recognition, even in complex driving scenarios.
Implementation Method 1
a sensed sensor value of a sensor of the motorcycle is selected
Data Source
Figure 1
Figure 2~3
AI summary
The present invention relates to a method for detecting an accident of a motorcycle (100). The method includes a reading step, a selection step and a detection step. In the reading step, a detected motorcycle velocity (125) of the motorcycle (100) is read in. In the selection step, a threshold value for at least one detected sensor value (130) of a sensor of the motorcycle (100) is selected using the motorcycle velocity (125). In the detection step, the accident of the motorcycle (100) is detected when the detected sensor value (130) reaches or exceeds the threshold value selected in the selection step.