@conference {470,
	title = {Reinforcement Learning for Autonomous Driving using CAT Vehicle Testbed},
	booktitle = {CAT Vehicle Research Experience for Undergraduates},
	year = {2019},
	month = {08/2019},
	publisher = {The University of Arizona},
	organization = {The University of Arizona},
	type = {Technical Report},
	address = {Tucson},
	abstract = {<p>We discuss a deep reinforcement learning implementation using the CAT Vehicle Testbed and discuss the merits of simulation-based deep reinforcement learning. After implementing a simple 3 layered neural network which learned using deep Q-learning, we found some challenges associated with ROS and Gazebo. In spite of these challenges, we demonstrate that our reinforcement learning architecture can teach a car to avoid obstacles. With these preliminary results, we discuss what new things we can do and how we can implement more advanced methods.</p>
},
	keywords = {Autonomous Systems, Machine Learning},
	url = {http://csl.arizona.edu/content/reinforcement-learning-autonomous-driving-using-cat-vehicle-testbed},
	author = {John Nguyen and Hoang Huynh and Eric Av and Rahul Bhadani and Tamal Bose}
}
