The Introduction to Autonomous Vehicles (AVs) training is a two-day foundational program designed to provide participants with a clear understanding of autonomous driving concepts, technologies, and system architectures. This course explains how autonomous vehicles perceive their environment, make decisions, and control vehicle motion, while also covering safety, regulations, and real-world deployment challenges shaping the future of intelligent transportation.

• Understand the fundamentals, architecture, and operational principles of autonomous vehicle systems.
• Identify key AV components including sensors, controllers, perception systems, communication modules, and actuators.
• Understand perception, localization, mapping, path planning, and decision-making workflows in autonomous driving.
• Work with sensor fusion, computer vision, real-time data processing, and vehicle control mechanisms.
• Analyze safety systems, operational reliability, testing strategies, and real-world deployment challenges.
• Build a strong foundation in autonomous mobility technologies and intelligent vehicle system design principles.

 • Automotive engineers and professionals
 • Robotics and automation engineers
 • Students and fresh graduates exploring AV technologies
 • IT professionals transitioning to intelligent mobility
 • Researchers and professionals interested in autonomous systems

 • Basic understanding of automobiles or transportation systems
 • Familiarity with basic programming or engineering concepts is helpful
 • Awareness of sensors or AI concepts is beneficial
 • No prior experience in autonomous vehicles is required

 • Understanding autonomous vehicle levels and classifications
 • Knowledge of AV system architecture and core components
 • Awareness of perception, localization, and decision-making concepts
 • Understanding safety, validation, and regulatory considerations
 • Familiarity with real-world AV use cases and challenges

By the end of this training, participants will have a solid understanding of autonomous vehicle concepts, system components, and operational challenges. Learners will be able to explain how AVs perceive, plan, and act, understand safety and regulatory considerations, and confidently engage in discussions related to autonomous mobility and intelligent transportation systems.

Introduction to Autonomous Vehicles and Intelligent Mobility
 • Evolution of autonomous driving
 • Difference between driver assistance and autonomy
 • Benefits and challenges of autonomous vehicles
 • Overview of AV ecosystem and stakeholders

Levels of Automation and AV Architecture
 • SAE levels of driving automation
 • End-to-end AV system architecture
 • Hardware and software stack overview
 • Role of onboard computing platforms

Sensors and Perception Systems
 • Cameras, LiDAR, radar, and ultrasonic sensors
 • Sensor characteristics and limitations
 • Sensor fusion concepts
 • Environment perception awareness

Localization and Mapping Concepts
 • Role of localization in autonomous driving
 • GPS and IMU basics
 • High-definition maps overview
 • Localization challenges in real-world scenarios

Planning, Decision-Making, and Control
 • Behavior planning concepts
 • Path planning basics
 • Motion control and vehicle actuation
 • Interaction with dynamic environments

Artificial Intelligence and Machine Learning in AVs
 • Role of AI in perception and decision-making
 • Machine learning and deep learning awareness
 • Training data and model validation basics
 • Limitations and ethical considerations

Safety, Validation, and Regulatory Considerations
 • Functional safety and ISO standards awareness
 • Testing and validation approaches
 • Simulation and real-world testing concepts
 • Regulatory and legal considerations

Autonomous Vehicle Use Cases and Best Practices
 • Passenger vehicles and robotaxis
 • Autonomous delivery and logistics
 • Industrial and off-road autonomous vehicles
 • Best practices and future trends

• Autonomous Vehicle Fundamentals & System Architecture
• Sensors, Perception & Environment Mapping
• Localization, Path Planning & Decision-Making
• Safety Systems, Testing & Performance Analysis
• End-to-End Autonomous Vehicle System Design Project

Participants will be evaluated through conceptual assessments, interactive discussions, and scenario-based exercises conducted during the training. The evaluation focuses on understanding AV fundamentals, system architecture, and the ability to relate autonomous driving concepts to real-world use cases.

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Upon successful completion of the training, participants will receive the AcadNXT Certification for Introduction to Autonomous Vehicles (AVs). This certification validates the learner’s foundational knowledge of autonomous vehicle technologies, system architecture, safety considerations, and intelligent mobility concepts.