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David Silver,
Thomas Hossler,
Antje Muntzinger,
Andreas Haja,
Aaron Brown,
Munir Jojo Verge,
and
Mathilde Badoual
Path planning routes a vehicle from one point to another, and it handles how to react when emergencies arise. The Mercedes-Benz Vehicle Intelligence team will take you through the three stages of path planning. First, you’ll apply model-driven and data-driven...
Read more
Path planning routes a vehicle from one point to another, and it handles how to react when emergencies arise. The Mercedes-Benz Vehicle Intelligence team will take you through the three stages of path planning. First, you’ll apply model-driven and data-driven...
Read more
Path planning routes a vehicle from one point to another, and it handles how to react when emergencies arise. The Mercedes-Benz Vehicle Intelligence team will take you through the three stages of path planning. First, you’ll apply model-driven and data-driven approaches to predict how other vehicles on the road will
behave. Then you’ll construct a finite state machine to decide which of several maneuvers your own vehicle should undertake. Finally, you’ll generate a safe and comfortable trajectory to execute that maneuver.
Register for this course and see more details by visiting:
OpenCourser.com/course/hv1jxf/plannin
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What's inside
Syllabus
Learn how to think about high-level behavior planning in a self-driving car.
Use C++ and the Eigen linear algebra library to build candidate trajectories for the vehicle to follow.
Read more
Syllabus
Learn how to think about high-level behavior planning in a self-driving car.
Use C++ and the Eigen linear algebra library to build candidate trajectories for the vehicle to follow.
Read more
Motion Planning
Motion Planning and Decision Making for Autonomous Vehicles
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops foundational knowledge of motion planning and maneuver construction, which are essential for autonomous vehicle development
Taught by experienced Mercedes-Benz engineers who are recognized for their expertise in vehicle intelligence
Uses a mix of lecture-based teaching and practical exercises using C++ and Eigen, providing learners with a comprehensive understanding of the topic
Provides a unique perspective on the complex field of autonomous vehicle path planning, examining both model-driven and data-driven approaches
Covers the latest industry standards and best practices for path planning in autonomous vehicles
May require some prior knowledge of programming and linear algebra, which could limit accessibility for some learners
Save this course
Save Planning to your list so you can find it easily later:
Save
Save
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Planning with these
activities:
Compile a Collection of Resources on Path Planning for Autonomous Vehicles
Show steps
Expand your knowledge and create a valuable resource for others by compiling a collection of resources on path planning for autonomous vehicles.
Browse courses on
Path Planning
Show steps
-
Conduct a thorough online search for resources on path planning for autonomous vehicles.
-
Review and select high-quality resources, such as research papers, articles, tutorials, and software tools.
-
Organize and categorize the resources in a logical and accessible manner.
-
Share your compilation with others through a website, blog, or online repository.
Review Motion Planning Techniques
Show steps
Refresh your understanding of motion planning techniques to ensure a strong foundation for this course.
Browse courses on
Motion Planning
Show steps
-
Revise the basics of motion planning algorithms.
-
Practice implementing motion planning algorithms in a simulated environment.
Complete an online tutorial
Show steps
Enhance your understanding of path planning and maneuver selection by following a guided online tutorial.
Show steps
-
Choose an online tutorial that covers a specific topic you want to learn more about.
-
Follow the tutorial step-by-step.
-
Complete all associated exercises or challenges.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Join a study group
Show steps
Discuss concepts, work through problems, and learn from peers by participating in a study group.
Browse courses on
Motion Planning
Show steps
-
Find or form a study group with other students enrolled in this course.
-
Meet regularly to discuss the course material and work on problems together.
-
Share your knowledge and insights with the group and learn from the perspectives of others.
Follow Tutorials on Model-Driven Path Prediction
Show steps
Enhance your understanding of model-driven path prediction by following expert-led tutorials.
Browse courses on
Path Planning
Show steps
-
Identify reputable sources for tutorials on model-driven path prediction.
-
Follow a series of tutorials that cover the fundamentals of model-driven path prediction.
-
Apply the techniques you learn to practical examples.
Write a summary
Show steps
Improve your understanding of the material by summarizing the concepts in your own words.
Show steps
-
Identify the key points of the material.
-
Write out the key points in clear and concise language.
-
Review and revise your summary until it is clear and complete.
Attend a Workshop on Motion Planning for Autonomous Vehicles
Show steps
Expand your knowledge and network with experts by attending a workshop on motion planning for autonomous vehicles.
Browse courses on
Motion Planning
Show steps
-
Identify and register for a reputable workshop on motion planning for autonomous vehicles.
-
Attend the workshop and actively participate in discussions and exercises.
-
Network with experts and fellow attendees to exchange ideas and learn from their experiences.
Solve practice problems
Show steps
Reinforce your understanding of trajectory generation and motion planning concepts by solving practice problems.
Browse courses on
Motion Planning
Show steps
-
Identify a practice problem that relates to a specific concept covered in the course.
-
Solve the problem using the techniques you have learned.
-
Check your solution against the provided answer or ask for feedback from a tutor or instructor.
Create a simple path planning algorithm
Show steps
Solidify your understanding of the entire path planning process by building a basic algorithm.
Browse courses on
Path Planning
Show steps
-
Define the problem and determine the necessary inputs and outputs.
-
Design a simple algorithm using the techniques covered in the course.
-
Implement the algorithm in a programming language.
-
Test the algorithm on a variety of scenarios and evaluate its performance.
Practice Designing Trajectories for Autonomous Vehicles
Show steps
Develop your skills in designing safe and efficient trajectories for autonomous vehicles through repetitive exercises.
Browse courses on
Autonomous Vehicles
Show steps
-
Familiarize yourself with the principles of trajectory design for autonomous vehicles.
-
Use software tools to practice designing trajectories in simulated environments.
-
Analyze the performance of your trajectories and identify areas for improvement.
-
Share your designs with others for feedback and collaboration.
Volunteer at a Self-Driving Car Testing Facility
Show steps
Gain hands-on experience and contribute to the development of self-driving cars by volunteering at a testing facility.
Browse courses on
Self-Driving Cars
Show steps
-
Identify and contact self-driving car testing facilities in your area.
-
Inquire about volunteer opportunities and qualifications.
-
Attend a training session and learn about the testing procedures.
-
Assist with data collection, vehicle monitoring, or other tasks as assigned.
-
Share your observations and feedback with the testing team.
Develop a Finite State Machine for Autonomous Vehicle Decision-Making
Show steps
Demonstrate your understanding of finite state machines by creating one for autonomous vehicle decision-making.
Show steps
-
Research different types of finite state machines and their applications in autonomous vehicles.
-
Design a finite state machine that meets the specific requirements of your chosen autonomous vehicle scenario.
-
Implement your finite state machine in a programming language or simulation software.
-
Test and evaluate the performance of your finite state machine.
-
Document your work and share it with others for feedback.
Participate in a path planning competition
Show steps
Challenge yourself and apply your skills in a competitive environment that simulates real-world path planning scenarios.
Browse courses on
Path Planning
Show steps
-
Find and register for a path planning competition.
-
Develop a strategy and implement a path planning algorithm.
-
Submit your algorithm to the competition and evaluate its performance.
Participate in an Autonomous Vehicle Simulation Competition
Show steps
Challenge yourself and showcase your skills by participating in an autonomous vehicle simulation competition.
Browse courses on
Motion Planning
Show steps
-
Research and identify suitable autonomous vehicle simulation competitions.
-
Form a team and develop a strategy for the competition.
-
Design and implement your autonomous vehicle simulation solution.
-
Test and refine your solution through simulations and trials.
-
Compete in the competition and learn from the experience.
Compile a Collection of Resources on Path Planning for Autonomous Vehicles
Show steps
Expand your knowledge and create a valuable resource for others by compiling a collection of resources on path planning for autonomous vehicles.
Browse courses on
Path Planning
Show steps
Show steps
Show steps
- Conduct a thorough online search for resources on path planning for autonomous vehicles.
- Review and select high-quality resources, such as research papers, articles, tutorials, and software tools.
- Organize and categorize the resources in a logical and accessible manner.
- Share your compilation with others through a website, blog, or online repository.
Review Motion Planning Techniques
Show steps
Refresh your understanding of motion planning techniques to ensure a strong foundation for this course.
Browse courses on
Motion Planning
Show steps
Show steps
Show steps
- Revise the basics of motion planning algorithms.
- Practice implementing motion planning algorithms in a simulated environment.
Complete an online tutorial
Show steps
Enhance your understanding of path planning and maneuver selection by following a guided online tutorial.
Show steps
Show steps
Show steps
- Choose an online tutorial that covers a specific topic you want to learn more about.
- Follow the tutorial step-by-step.
- Complete all associated exercises or challenges.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Join a study group
Show steps
Discuss concepts, work through problems, and learn from peers by participating in a study group.
Browse courses on
Motion Planning
Show steps
Show steps
Show steps
- Find or form a study group with other students enrolled in this course.
- Meet regularly to discuss the course material and work on problems together.
- Share your knowledge and insights with the group and learn from the perspectives of others.
Follow Tutorials on Model-Driven Path Prediction
Show steps
Enhance your understanding of model-driven path prediction by following expert-led tutorials.
Browse courses on
Path Planning
Show steps
Show steps
Show steps
- Identify reputable sources for tutorials on model-driven path prediction.
- Follow a series of tutorials that cover the fundamentals of model-driven path prediction.
- Apply the techniques you learn to practical examples.
Write a summary
Show steps
Improve your understanding of the material by summarizing the concepts in your own words.
Show steps
Show steps
Show steps
- Identify the key points of the material.
- Write out the key points in clear and concise language.
- Review and revise your summary until it is clear and complete.
Attend a Workshop on Motion Planning for Autonomous Vehicles
Show steps
Expand your knowledge and network with experts by attending a workshop on motion planning for autonomous vehicles.
Browse courses on
Motion Planning
Show steps
Show steps
Show steps
- Identify and register for a reputable workshop on motion planning for autonomous vehicles.
- Attend the workshop and actively participate in discussions and exercises.
- Network with experts and fellow attendees to exchange ideas and learn from their experiences.
Solve practice problems
Show steps
Reinforce your understanding of trajectory generation and motion planning concepts by solving practice problems.
Browse courses on
Motion Planning
Show steps
Show steps
Show steps
- Identify a practice problem that relates to a specific concept covered in the course.
- Solve the problem using the techniques you have learned.
- Check your solution against the provided answer or ask for feedback from a tutor or instructor.
Create a simple path planning algorithm
Show steps
Solidify your understanding of the entire path planning process by building a basic algorithm.
Browse courses on
Path Planning
Show steps
Show steps
Show steps
- Define the problem and determine the necessary inputs and outputs.
- Design a simple algorithm using the techniques covered in the course.
- Implement the algorithm in a programming language.
- Test the algorithm on a variety of scenarios and evaluate its performance.
Practice Designing Trajectories for Autonomous Vehicles
Show steps
Develop your skills in designing safe and efficient trajectories for autonomous vehicles through repetitive exercises.
Browse courses on
Autonomous Vehicles
Show steps
Show steps
Show steps
- Familiarize yourself with the principles of trajectory design for autonomous vehicles.
- Use software tools to practice designing trajectories in simulated environments.
- Analyze the performance of your trajectories and identify areas for improvement.
- Share your designs with others for feedback and collaboration.
Volunteer at a Self-Driving Car Testing Facility
Show steps
Gain hands-on experience and contribute to the development of self-driving cars by volunteering at a testing facility.
Browse courses on
Self-Driving Cars
Show steps
Show steps
Show steps
- Identify and contact self-driving car testing facilities in your area.
- Inquire about volunteer opportunities and qualifications.
- Attend a training session and learn about the testing procedures.
- Assist with data collection, vehicle monitoring, or other tasks as assigned.
- Share your observations and feedback with the testing team.
Develop a Finite State Machine for Autonomous Vehicle Decision-Making
Show steps
Demonstrate your understanding of finite state machines by creating one for autonomous vehicle decision-making.
Show steps
Show steps
Show steps
- Research different types of finite state machines and their applications in autonomous vehicles.
- Design a finite state machine that meets the specific requirements of your chosen autonomous vehicle scenario.
- Implement your finite state machine in a programming language or simulation software.
- Test and evaluate the performance of your finite state machine.
- Document your work and share it with others for feedback.
Participate in a path planning competition
Show steps
Challenge yourself and apply your skills in a competitive environment that simulates real-world path planning scenarios.
Browse courses on
Path Planning
Show steps
Show steps
Show steps
- Find and register for a path planning competition.
- Develop a strategy and implement a path planning algorithm.
- Submit your algorithm to the competition and evaluate its performance.
Participate in an Autonomous Vehicle Simulation Competition
Show steps
Challenge yourself and showcase your skills by participating in an autonomous vehicle simulation competition.
Browse courses on
Motion Planning
Show steps
Show steps
Show steps
- Research and identify suitable autonomous vehicle simulation competitions.
- Form a team and develop a strategy for the competition.
- Design and implement your autonomous vehicle simulation solution.
- Test and refine your solution through simulations and trials.
- Compete in the competition and learn from the experience.
Career center
Learners who complete Planning will develop knowledge and skills
that may be useful to these careers:
Robotics Engineer
Robotics Engineer
Robotics Engineers perform a variety of tasks to bring robots to life, from pre-production design to user training and maintenance. They work in a variety of domains, including self-driving cars. Mercedes-Benz has a distinguished history of manufacturing automated vehicles; a Robotics Engineer working for their Vehicle Intelligence team will have the opportunity to help shape tomorrow's transportation technologies.
Control Systems Engineer
Control Systems Engineer
Control Systems Engineers design, test, and maintain controllers. They work in a variety of industries, including automotive. Unlike other domains, control systems in self-driving cars must account for very complex traffic patterns and potentially dangerous scenarios. The Mercedes-Benz team behind the production of autonomous vehicles is focused on safety. A Control Systems Engineer building control systems for their vehicles will develop skills that translate well to any number of domains where advanced control systems are used.
Applications Engineer
Applications Engineer
Applications Engineers perform a technical sales role. That may mean working for an OEM, such as Mercedes-Benz, or working for a tier one supplier that sells products to OEMs. They convey engineering information about products to potential buyers. An Applications Engineer working for a company developing self-driving technologies can expect that their customers will have lots of questions about how automated vehicle systems operate. A skilled Applications Engineer will be comfortable with both the technical details of their product as well as the business reasons for why a customer might be interested in the product.
Software Engineer
Software Engineer
Software Engineers design, develop, and deploy software. Many Software Engineers work on projects related to autonomous vehicles. They may work on software for ADAS features on production vehicles or on next-generation self-driving software. The Mercedes-Benz team behind their intelligent vehicles works with ROS, Autoware, and Apollo. Software Engineers working on this team will be able to help advance the state of the art for self-driving software.
Product Manager
Product Manager
Product Managers coordinate the development and launch of new products. They work with engineering, marketing, and sales to ensure that products meet customer needs. As self-driving technology evolves, the role of the Product Manager will become increasingly important. Product Managers will help define, launch, and iterate on emergent products and services related to autonomous vehicles. Someone who wants to build a career in this field should take this course to get a basic understanding of how path planning works as well as the challenges associated with it.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers research, develop, and deploy machine learning solutions. They work with data scientists to determine which techniques to use and how best to implement them. Many Machine Learning Engineers work on projects related to self-driving cars. They develop algorithms for perception, path planning, and other tasks. This course can help someone interested in a Machine Learning engineering career because it introduces several advanced techniques that are used in robotics and autonomous vehicle development.
Quality Assurance Analyst
Quality Assurance Analyst
Quality Assurance (QA) Analysts test software for quality. They write test plans, execute tests, and report defects. QA Analysts work in a variety of domains, including automotive. As driver assistance systems become more self-driving, the role of the QA Analyst will become increasingly important. QA Analysts will play a key role in ensuring the safety of self-driving cars. Someone with a background in autonomous vehicles will be well prepared for a role as a Quality Assurance Analyst in this domain.
Automotive Engineer
Automotive Engineer
Automotive Engineers research, develop, and test vehicles. They work on a variety of projects, including the development of autonomous driving systems. This course may be useful for someone interested in automotive engineering, as it covers some of the technical challenges associated with developing self-driving cars. It also introduces model-driven and data-driven approaches, which are commonly used by automotive engineers.
Aerospace Engineer
Aerospace Engineer
Aerospace Engineers design, build, and test aircraft, spacecraft, and other aerospace vehicles. They use their knowledge of physics and engineering to solve complex problems. Some Aerospace Engineers work on projects related to self-driving aircraft. This course may be useful for someone interested in aerospace engineering who wants to work on autonomous vehicle technologies.
Mechanical Engineer
Mechanical Engineer
Mechanical Engineers design, build, and maintain machines. They use their knowledge of physics and engineering to solve complex problems. Some Mechanical Engineers work on projects related to self-driving cars. This course may be useful for someone interested in mechanical engineering who wants to work on autonomous vehicle technologies.
Electrical Engineer
Electrical Engineer
Electrical Engineers design, build, and maintain electrical systems. They use their knowledge of physics and engineering to solve complex problems. Some Electrical Engineers work on projects related to self-driving cars. This course may be useful for someone interested in electrical engineering who wants to work on autonomous vehicle technologies.
Computer Engineer
Computer Engineer
Computer Engineers design, build, and maintain computer systems. They use their knowledge of physics and engineering to solve complex problems. Some Computer Engineers work on projects related to self-driving cars. This course may be useful for someone interested in computer engineering who wants to work on autonomous vehicle technologies.
Industrial Engineer
Industrial Engineer
Industrial Engineers design, build, and maintain industrial systems. They use their knowledge of physics and engineering to solve complex problems. Some Industrial Engineers work on projects related to self-driving cars. This course may be useful for someone interested in industrial engineering who wants to work on autonomous vehicle technologies.
Biomedical Engineer
Biomedical Engineer
Biomedical Engineers design, build, and maintain medical devices. They use their knowledge of physics and engineering to solve complex problems. Some Biomedical Engineers work on projects related to self-driving cars. This course may be useful for someone interested in biomedical engineering who wants to work on autonomous vehicle technologies.
Civil Engineer
Civil Engineer
Civil Engineers design, build, and maintain infrastructure. They use their knowledge of physics and engineering to solve complex problems. Some Civil Engineers work on projects related to self-driving cars. This course may be useful for someone interested in civil engineering who wants to work on autonomous vehicle technologies.
For more career information including salaries, visit:
OpenCourser.com/course/hv1jxf/plannin
Reading list
We've selected five books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Planning.
Save
Introduces a wide range of planning algorithms, including path planning, motion planning, and task planning. It provides a theoretical foundation for planning algorithms and discusses their applications in various domains, including robotics, computer graphics, and artificial intelligence.
Provides a comprehensive treatment of robot motion planning, covering both theoretical foundations and practical applications. It is suitable for both students and researchers in the field of robotics.
Provides a comprehensive overview of planning with Markov decision processes. It covers a wide range of topics, including modeling, solution methods, and applications, and provides insights into the challenges and opportunities of this rapidly developing field.
Provides a comprehensive overview of reinforcement learning. It covers a wide range of topics, including modeling, algorithms, and applications, and provides insights into the challenges and opportunities of this rapidly developing field.
Provides a comprehensive overview of deep learning for computer vision. It covers a wide range of topics, including image processing, object detection, and scene understanding, and provides insights into the challenges and opportunities of this rapidly developing field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/hv1jxf/plannin
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Time
40320 hours
Level
Advanced
Via
Udacity
Instructors
David Silver
Thomas Hossler
Antje Muntzinger
Andreas Haja
Aaron Brown
Munir Jojo Verge
Mathilde Badoual
Language
English
Good to know
Develops foundational knowledge of motion planning and maneuver construction, which are essential for autonomous vehicle development
Taught by experienced Mercedes-Benz engineers who are recognized for their expertise in vehicle intelligence
Uses a mix of lecture-based teaching and practical exercises using C++ and Eigen, providing learners with a comprehensive understanding of the topic
Provides a unique perspective on the complex field of autonomous vehicle path planning, examining both model-driven and data-driven approaches
Covers the latest industry standards and best practices for path planning in autonomous vehicles
May require some prior knowledge of programming and linear algebra, which could limit accessibility for some learners
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