Mr. Andrew C. Kim Profile

Andrew C. Kim

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Proceedings Article | 17 May 2005 Paper

Rapid detection and identification of pedestrian impacts using a distributed sensor network

Andrew Kim, Fu-Kuo Chang

Proceedings Volume 5764, (2005) https://doi.org/10.1117/12.600433

KEYWORDS: Sensors, Sensor networks, Head, Safety, Data acquisition, Wave propagation, Injuries, Ferroelectric materials, Fourier transforms, Signal attenuation

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Pedestrian fatalities from automobile accidents often occur as a result of head injuries suffered from impacts with an automobile front end. Active pedestrian protection systems with proper pedestrian recognition algorithms can protect pedestrians from such head trauma. An investigation was conducted to assess the feasibility of using a network of piezoelectric sensors mounted on the front bumper beam of an automobile to discriminate between impacts with “pedestrian” and “non-pedestrian” objects. This information would be used to activate a safety device (e.g., external airbag or pop-up hood) to provide protection for the vulnerable pedestrian. An analytical foundation for the object-bumper impact problem will be presented, as well as the classical beam impact theory. The mechanical waves that propagate in the structure from an external impact contain a wealth of information about the specifics of a particular impact -- object mass, size, impact speed, etc. -- but most notably the object stiffness, which identifies the impacted object. Using the frequency content of the sensor signals, it can be shown that impacts with a “pedestrian” object of varying size, weight, and speed can be easily differentiated from impacts with other “non-pedestrian” objects. Simulation results will illustrate this phenomenon, and experimental tests will verify the results. A comprehensive series of impact tests were performed for validation, using both a stationary front bumper with a drop-pendulum impactor and a moving car with stationary impact objects. Results from both tests will be presented.

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