Vehicle Collision Detection Using Accelerometer Accumulated Data
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Solution Overview
Problem
Existing vehicle collision detection systems using accelerometers struggle to accurately differentiate between collisions and normal driving conditions, particularly at low speeds and on rough roads, due to reliance on integration and threshold calculations that require actual crash data.
Innovation Solution
A method and apparatus that sum acceleration data over a time period to determine accumulated acceleration, using thresholds based on energy changes likely to cause injury or damage, and count acceleration data points exceeding a second threshold to detect collisions, allowing for simpler integer operations and improved detection of low-speed collisions without requiring actual crash data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If integration and threshold calculations based on actual crash data are used, then collision detection accuracy is improved, but device complexity and processing requirements increase
Solution Approach 1:
The patent changes the detection parameter from integrated acceleration (requiring complex threshold calculations) to accumulated acceleration (simple summation). By defining accumulated acceleration as the sum of acceleration samples over a time period and comparing it directly to a fixed threshold, the system achieves accurate collision detection without complex processing. This parameter transformation resolves the contradiction by simplifying the detection mechanism while maintaining effectiveness.
2Loss of information
If integration methods are used to process acceleration data, then velocity signals can be obtained, but computational complexity and processing time increase
Solution Approach 1:
The patent extracts only the essential information needed for collision detection (accumulated acceleration) rather than performing full integration to obtain velocity signals. By taking out only the necessary component (sum of acceleration samples) and comparing it to a threshold, the system avoids the computational burden of complete integration while still detecting collisions effectively. This extraction approach reduces processing time while maintaining detection capability.
3Productivity
If simple threshold comparison is used, then processing speed is improved, but ability to differentiate between rough roads and collisions deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-defining a threshold value for accumulated acceleration that distinguishes collisions from normal driving conditions. Instead of performing complex real-time analysis, the system uses a predetermined threshold that has been established to differentiate between rough roads and actual collisions. This preliminary setup enables fast processing while maintaining discrimination accuracy.
4Reliability
If accelerometer data is continuously monitored with complex algorithms, then detection accuracy is improved, but power consumption and processing load increase
Solution Approach 1:
The patent uses a simple, computationally inexpensive method (accumulated acceleration with threshold comparison) that can be executed frequently with minimal energy cost. Rather than employing complex algorithms that consume significant power, the system uses a lightweight approach that can be continuously monitored without excessive energy expenditure. This disposable-like simplicity in each detection cycle maintains reliability while minimizing power consumption.
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
Enables efficient and accurate detection of collisions using accelerometer data, suitable for devices with limited processing power, and improves detection of low-speed collisions by considering energy changes and relative thresholds, reducing false positives and negatives.
Implementation Method 1
receiving acceleration data from the accelerometer at discrete intervals
Data Source
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AI summary
A collision is detected using an accelerometer attached to a vehicle. Acceleration data is received (100) from the accelerometer at discrete intervals. The acceleration data is summed (106) over a time period to produce an accumulated acceleration. Whether a collision has occurred is determined based at least in part on a comparison (108) of at least one of the accumulated acceleration and a function of the accumulated acceleration to a threshold.