|
Date
|
Lecture Notes
|
Topics
|
Additional
Readings (Optional)
|
|
W1
|
L1.1
Introduction and Overview PPTX,
PDF
L1.2 L1.2 AV Sensors V2X HD Maps PPTX, PDF
|
Background,
history, AD processing pipeline, Sensors and
perception, V2X, HD maps
|
What
is an Autonomous Vehicle: A Comprehensive Guide to its Engineering Principles
and Applications
|
|
W2
|
L1.3 HWSW Platforms Ethics PPTX, PDF
|
HW
platforms, SW platforms, Ethical issues
|
The Truth About Self
Driving Cars by New Mind (YouTube)
Self-Driving
Cars, 2022,
Uni Bonn (YouTube)
Self-Driving
Cars, 2022, Uni Tuebingen (YouTube
playlist)
|
|
W2
|
L2
Intro to Machine Learning PPTX, PDF
|
Activation
functions, Cross-Entropy Loss, SoftMax, ROC and AUC, NN training issues
|
A
collection of the latest machine learning and deep learning courses
|
|
W3
|
L3.1
Convolutional Neural Networks PPTX, PDF
|
Intro
to CNN, case studies (LeNet, AlexNet, VGGNet, GooLeNet, ResNet...)
|
UC Berkeley CS231n
Convolutional Neural Networks for Visual Recognition
Introduction
to Convolutional Neural Networks by Animated AI (YouTube)
Convolutional Neural
Networks | CNN | Kernel | Stride | Padding | Pooling | Flatten | Formula
(YouTube)
Essentials
of Object Detection by
Kapil
Sachdeva (YouTube)
|
|
W4
|
L3.2
Adversarial Attacks PPTX,
PDF
|
Adversarial
attacks
|
NeurIPS
2018 tutorial, Adversarial Robustness: Theory and Practice
|
|
W5
|
L4
Object Detection and Segmentation PPTX, PDF
|
Object
detection (R-CNN, Fast R-CNN, Faster R-CNN, Single-Stage Detectors), object
segmentation
|
Deep
Learning for Computer Vision, U Michigan, YouTube
playlist
|
|
W6
|
L5
Planning PPTX, PDF
|
Route
planning, behavior planning, local planning, Responsibility Sensitive Safety
(RSS)
|
Self-Driving
Cars: Planning (Benedikt Mersch 2020) (YouTube)
|
|
W7
|
L6
Control PPTX, PDF
|
PID,
MPC, Udacity racetrack control, PID tuning with twiddle()
|
Controlling Self Driving
Cars PID Control tutorial
PIDs Simplified
Understanding PID Control,
Part 1: What Is PID Control? By MATLAB
|
|
W8
|
L7.1
Markov Decision Process PPTX,
PDF
|
Markov
Decision Process (MDP), Bellman Equations
|
Reinforcement
Learning: An Introduction, Richard S. Sutton and
Andrew G. Barto
Reinforcement Learning MOOC by
Chris G. Willcocks (based on Sutton & Barto book)
|
|
W9
|
L7.2 Q-Learning, PPTX, PDF
L7.3 Policy-based RL, PPTX, PDF, Video
Lecture
|
Value-based RL (Q-learning); Policy-based RL
(Policy Gradient Theorem, MC REINFORCE, Actor-Critic)
|
Reinforcement
Learning: An Introduction
Q-Learning,
let us create an autonomous Taxi
OpenAI Spinning Up
in Deep RL
A friendly introduction to deep reinforcement
learning, Q-networks and policy gradients (YouTube)
|
|
W10
|
Final Exam, Jan. 12, 2024, 15:00-17:30,
Online on Zoom, Sample Exam Questions
|
|
|