Ultra Reliable Detection of Imminent Collision for Enhanced Occupant Safety

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Ultra Reliable Detection of Imminent Collision for Enhanced Occupant Safety

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Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota




This project focuses on the use of anisotropic magnetoresisitve (AMR) sensors for detection of an imminent unavoidable collision. An analytical formulation is developed for the variation of the magnetic field around a car as a function of position. Based on magnetic field measurements using AMR sensors, the position and velocity of any other car can be estimated and an imminent collision detected just prior to collision. The developed AMR sensor system has very high refresh rates, works at very small distances down to zero meters and is highly inexpensive. A variety of experimental results are presented to demonstrate the performance of the system for both one-dimensional and two-dimensional relative motion between cars. The second part of the project conducts simulations to show the benefits of detecting an imminent collision using the developed AMR sensors. An occupant model is developed to analyze occupant motion inside a car during a frontal collision. Analytical formulations and simulations are used to show how occupant safety can be enhanced when knowledge of an imminent collision is available.


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Department of Mechanical Engineering, University of Minnesota

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Taghvaeeyan, Saber; Sun, Zhen; Mott, Michael; Rajamani, Rajesh. (2012). Ultra Reliable Detection of Imminent Collision for Enhanced Occupant Safety. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/127345.

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