Course description
Connected and Autonomous Vehicles: Computer Vision and AI
This course covers a number of key topics in Computer Vision, Machine Learning, Deep Learning, and Artificial Intelligence. It provides a general overview of the key challenges faced when applying such techniques to Connected Autonomous Vehicles, starting with fundamental concepts and techniques. This includes topics such as CAV routing, game theory and coordination. The course also shows how a variety of AI techniques can be combined to solve particular use-cases of CAVs.
Level: Technical
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Upcoming start dates
Suitability - Who should attend?
This course is for Junior/Senior Engineers, (Civil, Transportation, Computing, Electronic), Mid-level to Senior Management.
Outcome / Qualification etc.
- Discuss the key challenges and benefits of applying AI, Machine Learning, and Computer Vision in CAV applications
- Select and apply a variety of AI, Machine Learning, and Computer Vision techniques to CAV applications
- Model CAV coordination and routing problems
- Identify ethical and social impacts of CAVs
Training Course Content
Units included in this course
- Unit 1 - Overview of the Challenges
- Unit 2 - Machine Vision
- Unit 3 - Deep Learning
- Unit 4 - Deep Learning for Machine Vision
- Unit 5 - Reinforcement Learning
- Unit 6 - CAV Routing
- Unit 7 - CAV Coordination
- Unit 8 - Game Theory and Mechanism Design
- Unit 9 - Final Assessment
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