Magnetic Sensor Systems for Collision Prediction, Traffic Counting, and Other Applications
November 5, 2015
About the Presentation
This presentation reviewed the idea of exploiting the inherent magnetic fields of objects to sense their position. It also discussed a project that used redundant magnetic sensors and adaptive estimation algorithms in the following applications: on a car to predict an imminent collision with another vehicle, on a portable traffic sensor for counting traffic and for differentiating between straight and right-turning cars at an intersection, and for performing nonintrusive real-time position estimation of the piston inside an internal combustion engine cylinder.
The presentation closed with a discussion of collision avoidance systems for bicycles and an exploration of whether magnetic sensors could play a useful role in this application.
About the Speaker
Rajesh Rajamani is a professor of mechanical engineering at the University of Minnesota. His research interests include vehicle dynamics, intelligent transportation systems, microsensors, and control system design. His current research activities in transportation include the development of imminent crash prediction sensors, development of systems for real-time estimation of tire-road friction coefficient on highway vehicles, development of battery-less wireless traffic and weigh-in-motion sensors, and development of electronic stability control systems.