Stochastic Models for Human Driving Behavior and Applications to Semi-autonomous Safety Systems

Monday, February 8, 2016 - 2:25pm - 3:25pm
Lind 305
Daniel Hoehener (Massachusetts Institute of Technology)
In this talk I present a stochastic model for human driving behavior and a general (model-based) approach to design a so-called safety supervisor which can override the human driver if otherwise a collision would occur. The main property of our approach is that it provides formal guarantees for the correctness of the safety supervisor. I will illustrate the theory with two application examples.
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