Algorithms for Automated Driving
Algorithms for Automated Driving¶
Each chapter of this (mini-)book guides you in programming one important software component for automated driving. Currently, this book contains three chapters: Lane Detection, Control and Camera Calibration. You will implement software that
detects lane boundaries from a camera image using deep learning
controls steering wheel and throttle to keep the vehicle within the detected lane at the desired speed
determines how the camera is positioned and oriented with respect to the vehicle (a prerequisite to properly join the lane detection and the control module)
The software you will write is in python, and you will apply it in the open-source driving simulator CARLA. Ideally, your computer is powerful enough to run CARLA, but if it is not, you can still work through the exercises. For the exercise on control there is a simplistic simulator that comes with this course. We recommend to work through the chapters in order, but if you want to, you can read the Control chapter, before the Lane Detection chapter.
To work through this book, you
should understand the following math and physics concepts: derivative, integral, trigonometry, sine/cosine of an angle, matrix, vector, coordinate system, velocity, acceleration, angular velocity, cross product, rotation matrix
should be familiar with programming in python. In particular, you should be comfortable with multidimensional arrays in numpy. You do not need a powerful computer (see Exercise Setup)
need to know what supervised learning is, and how to train a neural network with a deep learning framework like pytorch, fastai, tensorflow, keras, or something similar. This prerequisite is only necessary for the chapter on lane detection. If you do not fulfill it, you can skip this chapter, or study one of the courses I recommend and then come back here.
If you find a bug in the exercise code or some confusing explanations in the book, please raise an issue on github. If you have questions about the material or want to connect with me or other students, please use github discussions. Once you finish the book or decide to stop working through it, please consider giving some feedback by filling out this questionnaire (If you open the link in your browser’s incognito mode, the questionnaire should be anonymous).
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Are you interested in contributing to the book by adding a new chapter? Or do you have other ideas for improvements? Please let us know by joining the discussion on github!