| METHOD FOR CLASSIFICATION OF FRONTAL COLLISION EVENTS IN PASSENGER CARS BASED ON MEASUREMENT OF LOCAL COMPONENT-SPECIFIC DECELERATIONS |
| André Leschke1, Florian Weinert1, Maximillian Obermeier1, Stefan Kubica2, Vincenzo Bonaiuto3 |
1Volkswagen AG
2University of Applied Sciences Wildau
3University of Rome Tor Vergata |
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| ABSTRACT |
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The detection of accident scenarios is essential for a timely deployment of restraint devices and therefore for optimum protection of the vehicle occupants. Based on an innovative concept for crash detection, which involves measuring component-related local decelerations, this paper presents an entirely new method for the simulation and evaluation and estimates this with of a comprehensive set of crash load cases. With this approach, decelerations are detected directly at numerous individual components in the vehicle front end and are integrated in a velocity reduction using small time intervals.An evaluation based on multivariate statistical methods shows that the information content which results from exceedance of one defined velocity reduction threshold per measuring point is sufficient to safely distinguish between and classify all relevant load cases with a high level of independence. The concept has therefore proven to be functional and will be transferred to initial test series. |
| Key Words:
Accident detection, Crash detection, RFID based crash sensing, Load case separation |
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Corresponding Author.
Florian Weinert , Email. 
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