U of T - Introduction to Self-Driving Cars
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- Public/Government Institute
Introduction to Self-Driving Cars at Coursera Overview
Duration | 35 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Advanced |
Official Website | Explore Free Course  |
Credential | Certificate |
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- Highlights
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- Curriculum
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Introduction to Self-Driving Cars at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 1 of 4 in the Self-Driving Cars Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Advanced Level This is an advanced course, intended for learners with a background in mechanical engineering, computer and electrical engineering, or robotics.
- Approx. 35 hours to complete
- English Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Introduction to Self-Driving Cars at Coursera Course details
- Welcome to Introduction to Self-Driving Cars, the first course in University of Toronto?s Self-Driving Cars Specialization.
- This course will introduce you to the terminology, design considerations and safety assessment of self-driving cars. By the end of this course, you will be able to:
- - Understand commonly used hardware used for self-driving cars
- - Identify the main components of the self-driving software stack
- - Program vehicle modelling and control
- - Analyze the safety frameworks and current industry practices for vehicle development
- For the final project in this course, you will develop control code to navigate a self-driving car around a racetrack in the CARLA simulation environment. You will construct longitudinal and lateral dynamic models for a vehicle and create controllers that regulate speed and path tracking performance using Python. You?ll test the limits of your control design and learn the challenges inherent in driving at the limit of vehicle performance.
- This is an advanced course, intended for learners with a background in mechanical engineering, computer and electrical engineering, or robotics. To succeed in this course, you should have programming experience in Python 3.0, familiarity with Linear Algebra (matrices, vectors, matrix multiplication, rank, Eigenvalues and vectors and inverses), Statistics (Gaussian probability distributions), Calculus and Physics (forces, moments, inertia, Newton's Laws).
- You will also need certain hardware and software specifications in order to effectively run the CARLA simulator: Windows 7 64-bit (or later) or Ubuntu 16.04 (or later), Quad-core Intel or AMD processor (2.5 GHz or faster), NVIDIA GeForce 470 GTX or AMD Radeon 6870 HD series card or higher, 8 GB RAM, and OpenGL 3 or greater (for Linux computers).
Introduction to Self-Driving Cars at Coursera Curriculum
Module 0: Welcome to the Self-Driving Cars Specialization!
Welcome to the Self-Driving Cars Specialization!
Welcome to the Course
The Story of Autonomous Vehicles
Meet the Instructor, Steven Waslander
Meet the Instructor, Jonathan Kelly
Meet Diana, Firmware Engineer
Meet Winston, Software Engineer
Meet Andy, Autonomous Systems Architect
Meet Paul Newman, Founder, Oxbotica & Professor at University of Oxford
Why Should You Take This Course?
Course Prerequisites: Knowledge, Hardware & Software
How to Use Discussion Forums
Glossary of Terms
How to Use Supplementary Readings in This Course
Lesson 1: Taxonomy of Driving
Lesson 2: Requirements for Perception
Lesson 3: Driving Decisions and Actions
Advice for Breaking into the Self-Driving Cars Industry
Lesson 1 Supplementary Reading: Taxonomy of Driving
Lesson 2 Supplementary Reading: Requirements for Perception
Lesson 3 Supplementary Reading: Driving Decisions and Actions
Lesson 1: Practice Quiz
Lesson 2: Practice Quiz
Module 1: Graded Quiz
Module 2: Self-Driving Hardware and Software Architectures
Lesson 1: Sensors and Computing Hardware
Lesson 2: Hardware Configuration Design
Lesson 3: Software Architecture
Lesson 4: Environment Representation
The Future of Autonomous Vehicles
Lesson 1 Supplementary Reading: Sensors and Computing Hardware
Lesson 2 Supplementary Reading: Hardware Configuration Design
Lesson 3 Supplementary Reading: Software Architecture
Lesson 4 Supplementary Reading: Environment Representation
Module 2: Graded Quiz
Module 3: Safety Assurance for Autonomous Vehicles
Lesson 1: Safety Assurance for Self-Driving Vehicles
Lesson 2: Industry Methods for Safety Assurance and Testing
Lesson 3: Safety Frameworks for Self-Driving
Meet Professor Krzysztof Czarnecki, Safety Assurance Expert
Prof. Krzysztof Czarnecki on Assessing and Validating Autonomous Safety: An Impossible Task?
Prof. Krzysztof Czarnecki's Lessons from Aerospace: Can the AV Industry Collaborate on Safety?
Paul Newman on the Trolley Problem
How Companies Approach Autonomous Vehicle Safety
Lesson 1 Supplementary Reading: Safety Assurance for Self-Driving Vehicles
Lesson 2 Supplementary Reading: Industry Methods for Safety Assurance and Testing
Lesson 3 Supplementary Reading: Safety Frameworks for Self-Driving
How Many Miles of Driving Would It Take to Demonstrate Autonomous Vehicle Reliability?
Module 3: Graded Quiz
Module 4: Vehicle Dynamic Modeling
Lesson 1: Kinematic Modeling in 2D
Lesson 2: The Kinematic Bicycle Model
Lesson 3: Dynamic Modeling in 2D
Lesson 4: Longitudinal Vehicle Modeling
Lesson 5: Lateral Dynamics of Bicycle Model
Lesson 6: Vehicle Actuation
Lesson 7: Tire Slip and Modeling
Challenges for the Industry
Supplementary Readings for Module 4
Lesson 2 Supplementary Reading: The Kinematic Bicycle Model
Lesson 3 Supplementary Reading: Dynamic Modeling in 3D
Lesson 4 Supplementary Reading: Longitudinal Vehicle Modeling
Lesson 5 Supplementary Reading: Lateral Dynamics of Bicycle Model
Lesson 6 Supplementary Reading: Vehicle Actuation
Lesson 7 Supplementary Reading: Tire Slip and Modeling
Module 5: Vehicle Longitudinal Control
Lesson 1: Proportional-Integral-Derivative (PID) Control
Lesson 2: Longitudinal Speed Control with PID
Lesson 3: Feedforward Speed Control
Zoox's Approach to Self-Driving Cars
Lesson 1 Supplementary Reading: Proportional-Integral-Derivative (PID) Control
Lesson 2 Supplementary Reading: Longitudinal Speed Control with PID
Lesson 3 Supplementary Reading: Feedforward Speed Control
Module 5 Graded Quiz
Module 6: Vehicle Lateral Control
Lesson 1: Introduction to Lateral Vehicle Control
Lesson 2: Geometric Lateral Control - Pure Pursuit
Lesson 3: Geometric Lateral Control - Stanley
Lesson 4: Advanced Steering Control - MPC
Lesson 1 Supplementary Reading: Introduction to Lateral Vehicle Control
Lesson 2 Supplementary Reading: Geometric Lateral Control - Pure Pursuit
Lesson 3 Supplementary Reading: Geometric Lateral Control - Stanley
Lesson 4 Supplementary Reading: Advanced Steering Control - MPC
Module 6: Graded Quiz
Module 7: Putting it all together
Lesson 1: Carla Overview - Self-Driving Car Simulation
Lesson 2: Final Project Overview
Final Project Solution
Congratulations on Completing Course 1!
Lesson 1 Supplementary Reading: Carla Overview - Self-Driving Car Simulation
CARLA Installation Guide
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