Automated Driving - Game Changing Technologies for Our Future

Overview

Explore cutting-edge technologies and development methods shaping automated driving systems, with insights on their transformative impact on future transportation.

Syllabus

• Introduction to Automated Driving
Overview of Automated Driving Systems (ADS)
Levels of Driving Automation (SAE Levels)
Historical Context and Evolution of Driving Technologies
• Sensing and Perception Technologies
Lidar, Radar, and Camera Systems
Sensor Fusion Techniques
Object Detection and Classification
• Localization and Mapping
GPS and GNSS Technologies
SLAM (Simultaneous Localization and Mapping)
High-definition Maps for Automated Driving
• Planning and Decision-Making Algorithms
Path Planning Algorithms
Motion Prediction and Planning
Decision-Making Frameworks
• Control Systems for Automated Vehicles
Vehicle Dynamics and Control Theory
Adaptive Cruise Control and Lane Keeping
Human-Machine Interface (HMI) Designs
• Machine Learning and AI in Automated Driving
Neural Networks and Deep Learning Applications
Reinforcement Learning for Driving Policy
Training and Simulation Environments
• Communication and Connectivity
V2X Communication (Vehicle-to-Everything)
Safety Protocols and Cybersecurity Measures
Role of 5G in Connected Vehicles
• Regulatory and Ethical Considerations
Legal Frameworks and Policies
Ethical Challenges in Autonomous Decisions
Public Perception and Trust in Automated Vehicles
• Case Studies and Industry Applications
Success Stories and Failures in Automated Driving
Analysis of Current Industry Leaders and Technologies
Impact on Urban Mobility and Infrastructure
• Future Trends and Research Directions
Emerging Technologies in Automated Driving
Research Challenges and Opportunities
Societal Impacts and Future Growth of Autonomous Vehicles
• Conclusion and Course Wrap-up
Recap of Key Learning Points
Future Outlook and Personal Reflections
Additional Resources and Further Reading

Subjects

Conference Talks