Informações sobre o curso
Programa de cursos integrados
100% online

100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Nível avançado

Nível avançado

Idiomas disponíveis

Inglês

Legendas: Inglês
Programa de cursos integrados
100% online

100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Nível avançado

Nível avançado

Idiomas disponíveis

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana
1
Horas para completar
1 hora para concluir

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

This module introduces the richness and challenges of the self-driving motion planning problem, demonstrating a working example that will be built toward throughout this course. The focus will be on defining the primary scenarios encountered in driving, types of loss functions and constraints that affect planning, as well as a common decomposition of the planning problem into behaviour and trajectory planning subproblems. This module introduces a generic, hierarchical motion planning optimization formulation that is further expanded and implemented throughout the subsequent modules....
Reading
3 vídeos (total de (Total 14 mín.) min), 2 leituras
Video3 videos
Meet the Instructor, Steven Waslander5min
Meet the Instructor, Jonathan Kelly2min
Reading2 leituras
How to Use Discussion Forums15min
How to Use Supplementary Readings in This Course15min

Module 1: The Planning Problem

...
Reading
1 teste
Quiz1 exercício prático
Module 1 Summative Quiz
Semana
2
Horas para completar
1 hora para concluir

Module 3: Mission Planning in Driving Environments

This module develops the concepts of shortest path search on graphs in order to find a sequence of road segments in a driving map that will navigate a vehicle from a current location to a destination. The modules covers the definition of a roadmap graph with road segments, intersections and travel times, and presents Dijkstra’s and A* search for identification of the shortest path across the road network. ...
Reading
Semana
3
Horas para completar
7 horas para concluir

Module 7: Putting it all together - Smooth Local Planning

Parameterized curves are widely used to define paths through the environment for self-driving. This module introduces continuous curve path optimization as a two point boundary value problem which minimized deviation from a desired path while satisfying curvature constraints. ...
Reading
1 leitura, 1 teste
Reading1 leituras
CARLA Installation Guide45min

Instrutores

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Steven Waslander

Associate Professor
Aerospace Studies
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Jonathan Kelly

Assistant Professor
Aerospace Studies

Sobre Universidade de 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. ...

Sobre o Programa de cursos integrados Self-Driving Cars

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

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

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