About this Course
4.9
23 ratings
5 reviews

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Start instantly and learn at your own schedule.

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. 20 hours to complete

Suggested: 7 weeks of study, 5-6 hours per week...

English

Subtitles: English

What you will learn

  • Check

    Understand commonly used hardware used for self-driving cars

  • Check

    Identify the main components of the self-driving software stack

  • Check

    Program vehicle modelling and control

  • Check

    Analyze the safety frameworks and current industry practices for vehicle development

100% online

Start instantly and learn at your own schedule.

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. 20 hours to complete

Suggested: 7 weeks of study, 5-6 hours per week...

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
2 hours to complete

Module 0: Welcome to the Self-Driving Cars Specialization!

This module will introduce you to the main concepts and layout of the specialization and discusses the major advances made in the field over the last two decades, highlighting the most recent progress made by major players in terms of safety and performance metrics, where available. ...
10 videos (Total 45 min), 4 readings
10 videos
Welcome to the Course2m
The Story of Autonomous Vehicles12m
Meet the Instructor, Steven Waslander5m
Meet the Instructor, Jonathan Kelly2m
Meet Diana, Firmware Engineer2m
Meet Winston, Software Engineer3m
Meet Andy, Autonomous Systems Architect2m
Meet Paul Newman, Founder, Oxbotica & Professor at University of Oxford5m
Why Should You Take This Course?2m
4 readings
Course Prerequisites: Knowledge, Hardware & Software15m
How to Use Discussion Forums15m
Glossary of Terms10m
How to Use Supplementary Readings in This Course15m
4 hours to complete

Module 1: The Requirements for Autonomy

Self-driving cars present an extremely rich and inter-disciplinary problem. This module introduces the language and structure of the problem definition, defining the most salient elements of the driving task and the driving environment....
4 videos (Total 37 min), 3 readings, 3 quizzes
4 videos
Lesson 2: Requirements for Perception8m
Lesson 3: Driving Decisions and Actions9m
Advice for Breaking into the Self-Driving Cars Industry6m
3 readings
Lesson 1 Supplementary Reading: Taxonomy of Driving30m
Lesson 2 Supplementary Reading: Requirements for Perception15m
Lesson 3 Supplementary Reading: Driving Decisions and Actions30m
3 practice exercises
Lesson 1: Practice Quiz30m
Lesson 2: Practice Quiz30m
Module 1: Graded Quiz50m
Week
2
3 hours to complete

Module 2: Self-Driving Hardware and Software Architectures

System architectures for self-driving vehicles are extremely diverse, as no standardized solution has yet emerged. This module describes both the hardware and software architectures commonly used and some of the tradeoffs in terms of cost, reliability, performance and complexity that constrain autonomous vehicle design....
5 videos (Total 51 min), 4 readings, 1 quiz
5 videos
Lesson 2: Hardware Configuration Design10m
Lesson 3: Software Architecture13m
Lesson 4: Environment Representation8m
The Future of Autonomous Vehicles6m
4 readings
Lesson 1 Supplementary Reading: Sensors and Computing Hardware15m
Lesson 2 Supplementary Reading: Hardware Configuration Design30m
Lesson 3 Supplementary Reading: Software Architecture30m
Lesson 4 Supplementary Reading: Environment Representation15m
1 practice exercise
Module 2: Graded Quiz50m
Week
3
5 hours to complete

Module 3: Safety Assurance for Autonomous Vehicles

As the self-driving domain matures, the requirement for safety assurance on public roads become more critical to self-driving developers. You will evaluate the challenges and approaches employed to date to tackle the immense challenge of assuring the safe operation of autonomous vehicles in an uncontrolled public road driving environment. ...
8 videos (Total 71 min), 4 readings, 1 quiz
8 videos
Lesson 2: Industry Methods for Safety Assurance and Testing17m
Lesson 3: Safety Frameworks for Self-Driving18m
Meet Professor Krzysztof Czarnecki, Safety Assurance Expert1m
Prof. Krzysztof Czarnecki on Assessing and Validating Autonomous Safety: An Impossible Task?3m
Prof. Krzysztof Czarnecki's Lessons from Aerospace: Can the AV Industry Collaborate on Safety?4m
Paul Newman on the Trolley Problem3m
How Companies Approach Autonomous Vehicle Safety5m
4 readings
Lesson 1 Supplementary Reading: Safety Assurance for Self-Driving Vehicless
Lesson 2 Supplementary Reading: Industry Methods for Safety Assurance and Testings
Lesson 3 Supplementary Reading: Safety Frameworks for Self-Driving30m
How Many Miles of Driving Would It Take to Demonstrate Autonomous Vehicle Reliability?15m
1 practice exercise
Module 3: Graded Quiz50m
Week
4
9 hours to complete

Module 4: Vehicle Dynamic Modeling

The first task for automating an driverless vehicle is to define a model for how the vehicle moves given steering, throttle and brake commands. This module progresses through a sequence of increasing fidelity physics-based models that are used to design vehicle controllers and motion planners that adhere to the limits of vehicle capabilities. ...
8 videos (Total 74 min), 7 readings, 2 quizzes
8 videos
Lesson 2: The Kinematic Bicycle Model8m
Lesson 3: Dynamic Modeling in 2D10m
Lesson 4: Longitudinal Vehicle Modeling11m
Lesson 5: Lateral Dynamics of Bicycle Model7m
Lesson 6: Vehicle Actuation9m
Lesson 7: Tire Slip and Modeling10m
Challenges for the Industry4m
7 readings
Supplementary Readings for Module 430m
Lesson 2 Supplementary Reading: The Kinematic Bicycle Model30m
Lesson 3 Supplementary Reading: Dynamic Modeling in 3D30m
Lesson 4 Supplementary Reading: Longitudinal Vehicle Modeling30m
Lesson 5 Supplementary Reading: Lateral Dynamics of Bicycle Model30m
Lesson 6 Supplementary Reading: Vehicle Actuation45m
Lesson 7 Supplementary Reading: Tire Slip and Modeling30m
4.9
5 ReviewsChevron Right

Top Reviews

By CGFeb 4th 2019

clear, easy to follow. I would say that needs to speed up a bit

By SSFeb 9th 2019

Wow!. Thanks a lot to Coursera for offering. Too Good

Instructors

Avatar

Steven Waslander

Associate Professor
Aerospace Studies
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Jonathan Kelly

Assistant Professor
Aerospace Studies

About University of Toronto

Established in 1827, the University of Toronto is one of the world’s leading universities, renowned for its excellence in teaching, research, innovation and entrepreneurship, as well as its impact on economic prosperity and social well-being around the globe. ...

About the Self-Driving Cars Specialization

Be at the forefront of the autonomous driving industry. With market researchers predicting a $42-billion market and more than 20 million self-driving cars on the road by 2025, the next big job boom is right around the corner. This Specialization gives you a comprehensive understanding of state-of-the-art engineering practices used in the self-driving car industry. You'll get to interact with real data sets from an autonomous vehicle (AV)―all through hands-on projects using the open source simulator CARLA. Throughout your courses, you’ll hear from industry experts who work at companies like Oxbotica and Zoox as they share insights about autonomous technology and how that is powering job growth within the field. You’ll learn from a highly realistic driving environment that features 3D pedestrian modelling and environmental conditions. When you complete the Specialization successfully, you’ll be able to build your own self-driving software stack and be ready to apply for jobs in the autonomous vehicle industry. It is recommended that you have some background in linear algebra, probability, statistics, calculus, physics, control theory, and Python programming. You will need these 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)....
Self-Driving Cars

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.