What started as a distant vision just a few decades ago is quickly becoming reality. Autonomous vehicles are about to be deployed on a large scale and will fundamentally change our transportation behavior. In this particular application, extreme demands on reliability and quality give rise to numerous problems and open issues that need to be jointly identified and addressed by both academia and industry. In this article, we present an overview of the current state-of-the-art in the field of intelligent autonomous vehicles. We further discuss open problems and current research directions.
About the author
Markus Enzweiler received the MSc degree in computer science from the University of Ulm, Germany (2005), and the PhD degree in computer science from the University of Heidelberg, Germany (2011). Since 2010, he has been a research scientist at Daimler AG Research & Development in Sindelfingen, Germany, where he co-developed the Daimler vision-based pedestrian detection system which is available in Mercedes-Benz cars. His current research focuses on statistical models of object appearance with application to object recognition, scene understanding and autonomous driving in the domain of intelligent vehicles. He held graduate and PhD scholarships from the Studienstiftung des deutschen Volkes (German National Academic Foundation). In 2012, he received both the IEEE Intelligent Transportation Systems Society Best PhD Dissertation Award and the Uni-DAS Research Award for his work on vision-based pedestrian recognition. He is part of the team that won the 2014 IEEE Intelligent Transportation Systems Outstanding Application Award. In 2014, he was honored with a Junior-Fellowship of the Gesellschaft für Informatik.
Daimler AG Research & Development, Environment Perception, 71059 Sindelfingen, Germany
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