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.
Department of Mechanical Engineering, University of Minnesota
Taghvaeeyan, Saber; Sun, Zhen; Mott, Michael; Rajamani, Rajesh.
Ultra Reliable Detection of Imminent Collision for Enhanced Occupant Safety.
Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota.
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