EAN: 9783031003745

SYNTHESIS LECTURES ON ADVANCES IN AUTOMOTIVE TE...

The next generation of autonomous vehicles will provide major improvements in traffic flow 
fuel efficiency  and vehicle safety. Several challenges currently prevent the deployment of
autonomous vehicles  one aspect of which is robust and adaptable vehicle control. Designing a
controller for autonomous vehicles capable of providing adequate performance in all driving
scenarios is challenging due to the highly complex environment and inability to test the system
in the wide variety of scenarios which it may encounter after deployment. However  deep
learning methods have shown great promise in not only providing excellent performance for
complex and non-linear control problems  but also in generalizing previously learned rules to
new scenarios. For these reasons  the use of deep neural networks for vehicle control has
gained significant interest. In this book  we introduce relevant deep learning techniques 
discuss recent algorithms applied to autonomous vehicle control  identify strengths and
limitations of available methods  discuss research challenges in the field  and provide
insights into the future trends in this rapidly evolving field.

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