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Motion Planning for Self-Driving Cars

Self-Driving Cars,

Welcome to Motion Planning for Self-Driving Cars, the fourth course in University of Toronto’s Self-Driving Cars Specialization. This course will introduce you to the main planning tasks in autonomous driving, including mission planning, behavior planning and local planning. By the end of this course, you will be able to find the shortest path over a graph or road network using Dijkstra's and the A* algorithm, use finite state machines to select safe behaviors to execute, and design optimal, smooth paths and velocity profiles to navigate safely around obstacles while obeying traffic laws. You'll also build occupancy grid maps of static elements in the environment and learn how to use them for efficient collision checking. This course will give you the ability to construct a full self-driving planning solution, to take you from home to work while behaving like a typical driving and keeping the vehicle safe at all times. For the final project in this course, you will implement a hierarchical motion planner to navigate through a sequence of scenarios in the CARLA simulator, including avoiding a vehicle parked in your lane, following a lead vehicle and safely navigating an intersection. You'll face real-world randomness and need to work to ensure your solution is robust to changes in the environment. This is an intermediate course, intended for learners with some background in robotics, and it builds on the models and controllers devised in Course 1 of this specialization. To succeed in this course, you should have programming experience in Python 3.0, and familiarity with Linear Algebra (matrices, vectors, matrix multiplication, rank, Eigenvalues and vectors and inverses) and calculus (ordinary differential equations, integration).

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Rating 4.8 based on 15 ratings
Length 8 weeks
Starts Dec 7 (7 weeks ago)
Cost $49
From University of Toronto via Coursera
Instructors Steven Waslander, Jonathan Kelly
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Art & Design
Tags Computer Science Design And Product Software Development

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What people are saying

do feel much better

Valuable survey course summarizing the high level architecture of motion planning, from high-level map planning, down to path lattices.Note: this is not going to make you an expert (unless you really go above and beyond and try to re-build the project) but it's very well structured and I do feel much better prepared to dive deeper.

high standard on content

I has the same high standard on content, presentation and assignments as the other courses, The final project is absolutely gorgeous as you make your car drive around a parking other car, follow a lead vehicles and halt at a stop sign.

many errors in slides

Too many errors in slides and a little bit easy.

keep learning additional material

Content is very advanced and this course is a good introduction to the topic, but it would require to keep learning additional material to go deeper into Motion Planning.

performed with carla simulator

The final project is complex but interesting at the same time as it is performed with Carla simulator which is fun.

projects were really helped

It was really well informative course and the assignments and projects were really helped me to understand the in real scenario implementation.Thanks.

deeper into motion planning

amazing journey came

Amazing journey came to an end.

little bit easy

real scenario implementation.thanks

can highly recommend

Again a course from the specialization that I can highly recommend.

high level architecture

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Rating 4.8 based on 15 ratings
Length 8 weeks
Starts Dec 7 (7 weeks ago)
Cost $49
From University of Toronto via Coursera
Instructors Steven Waslander, Jonathan Kelly
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Art & Design
Tags Computer Science Design And Product Software Development

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