About this Course
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Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Advanced Level

Approx. 18 hours to complete

Suggested: 7 hours/week...

English

Subtitles: English

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Advanced Level

Approx. 18 hours to complete

Suggested: 7 hours/week...

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
1 hour to complete

Welcome to Course 4: Motion Planning for Self-Driving Cars

4 videos (Total 18 min), 3 readings
4 videos
Welcome to the Course3m
Meet the Instructor, Steven Waslander5m
Meet the Instructor, Jonathan Kelly2m
3 readings
Course Readings10m
How to Use Discussion Forums15m
How to Use Supplementary Readings in This Course15m
2 hours to complete

Module 1: The Planning Problem

4 videos (Total 54 min), 1 reading, 1 quiz
4 videos
Lesson 2: Motion Planning Constraints13m
Lesson 3: Objective Functions for Autonomous Driving9m
Lesson 4: Hierarchical Motion Planning17m
1 reading
Module 1 Supplementary Reading10m
1 practice exercise
Module 1 Graded Quiz50m
Week
2
6 hours to complete

Module 2: Mapping for Planning

5 videos (Total 50 min), 1 reading, 1 quiz
5 videos
Lesson 2: Populating Occupancy Grids from LIDAR Scan Data (Part 1)9m
Lesson 2: Populating Occupancy Grids from LIDAR Scan Data (Part 2)9m
Lesson 3: Occupancy Grid Updates for Self-Driving Cars9m
Lesson 4: High Definition Road Maps11m
1 reading
Module 2 Supplementary Reading1h
Week
3
4 hours to complete

Module 3: Mission Planning in Driving Environments

3 videos (Total 35 min), 1 reading, 1 quiz
3 videos
Lesson 2: Dijkstra's Shortest Path Search10m
Lesson 3: A* Shortest Path Search13m
1 reading
Module 3 Supplementary Reading1h
1 practice exercise
Module 3 Graded Quiz50m
Week
4
2 hours to complete

Module 4: Dynamic Object Interactions

3 videos (Total 36 min), 1 reading, 1 quiz
3 videos
Lesson 2: Map-Aware Motion Prediction11m
Lesson 3: Time to Collision12m
1 reading
Module 4 Supplementary Reading1h
1 practice exercise
Module 4 Graded Quiz50m
4.8
9 ReviewsChevron Right

Top reviews from Motion Planning for Self-Driving Cars

By IKSep 14th 2019

I think it is one of the best courses for learning the motion planning algorithms for Autonomous driving. The concepts are well explained with lots of examples.

Instructors

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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.

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