Anticipatory Crash Classification Using Closing Velocity Sensor
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Solution Overview
Problem
Current supplemental restraint deployment methods, such as airbag deployment, rely heavily on vehicle acceleration and speed, making it difficult to discriminate between potentially severe and non-severe collisions, leading to inefficiencies and increased costs with the use of multiple sensors.
Innovation Solution
A method utilizing measured vehicle speed and acceleration in conjunction with a closing velocity sensor to classify crash events, determining the severity and deploying restraints accordingly, with deployment options varying based on crash classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple remote acceleration sensors are added to improve crash discrimination timeliness, then the detection accuracy and response time improve, but the system cost increases considerably
Solution Approach 1:
The patent combines the functions of multiple sensors into a single closing velocity sensor that provides both anticipatory crash detection and severity classification. This merging approach achieves improved crash discrimination without the cost penalty of multiple separate sensors, directly resolving the technical contradiction between measurement precision and device complexity.
Solution Approach 2:
The closing velocity sensor performs preliminary detection of approaching objects before actual collision occurs. By detecting closing velocity in advance, the system can classify the impending crash severity and prepare appropriate responses, improving both detection timeliness and accuracy without requiring multiple remote sensors.
2Loss of time
If an anticipatory closing velocity sensor is used to detect approaching objects, then the crash detection timeliness improves, but the ability to discriminate between severe and non-severe collisions deteriorates
Solution Approach 1:
The patent utilizes closing velocity as an additional parameter alongside traditional acceleration and delta-velocity measurements. By incorporating closing velocity into the crash classification algorithm, the system can distinguish between severe and non-severe collisions with high accuracy, resolving the contradiction between early detection and severity discrimination.
Solution Approach 2:
The system continuously monitors closing velocity and uses this information to dynamically adjust crash classification decisions. The feedback loop allows the system to differentiate between objects that pose serious danger versus those that pose little or no danger, maintaining both timeliness and discrimination accuracy.
3Device complexity
If traditional acceleration-based deployment algorithms are used, then the system simplicity is maintained, but the timeliness and accuracy of deployment decisions deteriorate
Solution Approach 1:
The closing velocity sensor performs preliminary assessment of impending crashes before actual impact occurs. This advance detection allows the deployment algorithm to be activated earlier and make more accurate deployment decisions, improving response timeliness without significantly increasing system complexity.
Solution Approach 2:
The patent implements a dynamic deployment algorithm that adapts its behavior based on real-time closing velocity measurements. The system can adjust deployment thresholds and timing dynamically according to the classified crash severity, improving both timeliness and accuracy while maintaining reasonable system simplicity through software-based adaptation.
Data Source
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AI summary
A supplemental restraint deployment method utilizes measured vehicle speed (16) and acceleration (14) and the output of a closing velocity sensor (18) that detects the presence and closing rate of an approaching object prior to contact with the vehicle (10). The closing velocity and vehicle speed are utilized for classification of an impending crash event (40-54), where the deployment options vary depending on the crash classification. In the ensuing crash event, a classification-dependent algorithm (56/60-74/90-122) is executed to determine if, when and what level of restraint deployment is warranted based on measures of actual crash severity. Additionally, the algorithm is reset when the calculated change in vehicle velocity reaches the initial closing velocity (64-65/94-95).