Paper
17 May 2005 Rapid detection and identification of pedestrian impacts using a distributed sensor network
Author Affiliations +
Abstract
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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Andrew C. Kim and Fu-Kuo Chang "Rapid detection and identification of pedestrian impacts using a distributed sensor network", Proc. SPIE 5764, Smart Structures and Materials 2005: Smart Structures and Integrated Systems, (17 May 2005); https://doi.org/10.1117/12.600433
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KEYWORDS
Sensors

Data acquisition

Head

Safety

Sensor networks

Wave propagation

Injuries

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