ET3 From Optimization to Autonomous Driving


Mathematical research is supposedly always operated in secret. Tonight we want to pull the math, especially the discipline of optimization, into the light and directly see, how mathematical algorithms can be applied to the real life application of autonomous driving.
My colleagues are working on the research project AO-Car, where we explore what is necessary to teach a car how to drive autonomously and optimally. Using standard and additional sensors of the car, we create a map with environment data. If we state the correctly formulated question, our algorithms tell us how to park a car or keep the lane. Is this solution just more data, or can we extract some insight from the data?
Having been in touch with basic and advanced concepts of optimization, the audience is invited to think of applying these techniques to their projects.


Optimization is your friend. How to bring maths to an application.


C. Büskens, D. Wassel. 
The ESA NLP Solver WORHP. 
Modeling and Optimization in Space Engineering, J. D. Pintér (Hrsg.), Springer Optimization and Its Applications, Vol. 73, Springer Verlag, 2013.
DOI: 10.1007/978-1-4614-4469-5

M. Knauer, C. Büskens. 
Processing User Input in Tracking Problems using Model Predictive Control. 
IFAC-PapersOnLine, 50(1):9846-9851, 2017.
DOI: 10.1016/j.ifacol.2017.08.905

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Matthias Knauer


University of Bremen


Matthias Knauer works as a research assistant at the Center for Industrial Mathematics (ZeTeM) at the University of Bremen. In the working group “Optimization and Optimal Control”, he optimizes wherever something is moving: cranes, spaceships, robots and cars. To make everyone understand how beautiful and useful mathematics can be, he creates interactive exhibits and offers mathematical city tours through Bremen.