Introduction to Autonomous Vehicles: Concepts and Applications

• Basic understanding of vehicle mechanics (recommended but not required)
• Interest in self-driving technology and intelligent transportation systems

Audience

• Business leaders and decision-makers exploring autonomous mobility solutions
• Professionals new to autonomous technology
• General enthusiasts interested in self-driving vehicles

Autonomous vehicles are self-driving systems that integrate artificial intelligence, sensors, and real-time computing to navigate without human intervention.

This instructor-led, live training (online or onsite) is aimed at beginner-level professionals and enthusiasts who wish to understand the fundamental concepts, technologies, and applications of autonomous vehicles.

By the end of this training, participants will be able to:

• Understand the key components and working principles of autonomous vehicles.
• Explore the role of AI, sensors, and real-time data processing in self-driving systems.
• Analyze different levels of vehicle autonomy and their real-world applications.
• Examine the ethical, legal, and regulatory aspects of autonomous mobility.
• Gain hands-on exposure to autonomous vehicle simulations.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to Autonomous Vehicles

• Definition and history of self-driving technology
• Key advantages and challenges of autonomous vehicles
• Industry trends and major players in the autonomous vehicle ecosystem

Levels of Vehicle Autonomy

• SAE automation levels (0-5)
• Comparison between ADAS (Advanced Driver Assistance Systems) and full autonomy
• Real-world examples of autonomous vehicle deployment

Core Technologies Behind Autonomous Vehicles

• Artificial intelligence and machine learning in self-driving cars
• Sensor technologies: LiDAR, radar, cameras, and ultrasonic sensors
• Fusion of sensor data for perception and decision-making

Autonomous Vehicle Control and Navigation

• How self-driving cars perceive their environment
• Path planning and decision-making algorithms
• Real-time vehicle control and motion planning

Communication and Connectivity in Self-Driving Cars

• Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication
• Role of 5G and cloud computing in autonomous mobility
• Autonomous vehicle cybersecurity challenges

Ethics, Safety, and Regulations

• Ethical considerations in self-driving car decision-making
• Legal frameworks and government regulations for autonomous vehicles
• Ensuring safety and reliability in autonomous driving

Hands-on Simulations

• Introduction to CARLA and ROS for autonomous vehicle testing
• Simulating object detection and obstacle avoidance
• Analyzing self-driving car performance in virtual environments

Future of Autonomous Mobility

• Innovations in AI-powered transportation
• Impact of autonomous vehicles on industries and society
• Next steps for learning and specialization in autonomous vehicle technology

Summary and Next Steps