Smart Mobility: ADAS, Autonomous, Connected
The automotive industry is transitioning toward an era of intelligent, connected, and automated mobility. Smart Mobility: ADAS, Autonomous, and Connected Vehicles is a comprehensive course designed to provide a deep understanding of the technologies, architectures, and engineering principles behind Advanced Driver Assistance Systems (ADAS) and autonomous driving. This course explores the complete ecosystem of smart mobility—from basic driver-assist functions to fully autonomous systems—covering critical elements such as sensors, perception algorithms, network communication, machine learning, system verification, cybersecurity, and regulatory considerations. Learners will examine how advanced electronics, AI, and connectivity enable vehicles to sense, decide, and act with precision and safety. Through a blend of theoretical foundations and real-world engineering practices, the course equips participants with the knowledge required to design, develop, validate, and integrate ADAS and autonomous features into modern vehicles. It also highlights the key challenges in functional safety, digital transformation, and legal liability, preparing engineers and professionals for the fast-growing smart mobility sector.
₹39999.00
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Program Overview
The course is structured into progressive modules covering hardware, software, algorithms, and system-level integration for ADAS and autonomous vehicles.
Key topics include:
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Introduction & Architectures: Fundamentals of autonomous driving, ADAS safety standards, and vehicle E/E architectures with bus systems like CAN, LIN, and Ethernet.
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Sensors & Perception: Camera, radar, LIDAR, ultrasonic sensors, GPS, and data flow for localization and object detection.
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ADAS Features: Lane-keeping assist, collision warning, adaptive cruise control, cross-traffic alerts, and driver monitoring.
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AI & Data Processing: Machine learning, computer vision, decision-making algorithms, sensor fusion, and model-based development.
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Safety & Cybersecurity: Verification and validation, functional safety (ISO 26262), digital transformation, IoT, and threat mitigation.
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Regulatory & Integration: Legal and liability frameworks, embedded systems, system testing, and vehicle-level validation.
This modular approach builds end-to-end expertise in smart mobility systems.
Program Curriculum
4 Subjects
Course 01 - Foundations of ADAS and Autonomous Mobility
1 Exercises • 27 Learning Materials
Module 01 - Introduction to Autonomous Driving
[Learning Session] Driver Control
[Learning Session] Driver Control & Control Mechanism
[Learning Session] Controllers in Cars and Human Limitations
[Learning Session] Safety and ADAS
[Learning Session] ADAS Standards
[Learning Session] ADAS Features
Summary - Introduction to Autonomous Driving
[Quick Knowledge Check] Driver Control
Module 02 - Vehicle System Architectures, Bus System
[Learning Session] Need of Data Communications and Evolvement of EE Architecture
[Learning Session] Vehicle Bus: LIN, CAN
[Learning Session] Vehicle Bus: Flex Ray, MOST
[Learning Session] Application of Bus System
[Learning Session] Vehicle Bus: Ethernet, Radio Frequency, Bluetooth
Summary - Vehicle System Architectures, Bus System
Module 03 - ADAS Sensors- Introduction
[Learning Session] ADAS Sensors & Features
[Learning Session] ADAS Sensors: CAMERA
[Learning Session] ADAS Sensors: RADAR
Summary - ADAS Sensors- Introduction
Module 04 - LIDAR & Ultrasonic Sensors
[Learning Session] Ultrasonic Sensors Working
[Learning Session] Ultrasonic Sensor Pro and Cons
[Learning Session] Lidar Basics
[Learning Session] Lidar Types & Inertial Measurement Unit
[Learning Session] GPS & Optical Encoders
Summary - LIDAR & Ultrasonic Sensors
Module 05 - Network Organization
[Learning Session] Network Organization: CAN Message Format
[Learning Session] Illustration: Front Lighting
[Learning Session] Illustration: Window Motor
Summary - Network Organization
Course 02 - ADAS Features, Validation, and Digital Transformation
35 Learning Materials
Module 01 - Level of Interventions
[Learning Session] Intelligent Functions & Intelligent Transport
Level of Interventions
Human Performance Capacity
Adaptive Cruise Control
Summary - Level of Interventions
Module 02 - ADAS Features-1
Front & Rear Cross Traffic Alert
Surround View Camera
Summary - ADAS Features-1
Module 03 - ADAS Features-2
Vehicle Exit, Lane Departure Warning
Lane Keeping Assist, Forward Collision Warning
Autonomous Emergency Braking, Electronic Stability Control
Blind Spot Alert, Obstacle Aware Acceleration, Trailer Tow Assist
Antilock Braking System
Summary - ADAS Features-2
Module 04 - ADAS Features-3
Traffic Sign Recognition
Driver Monitoring System
Intelligent Headlight System
Pedestrian Protection System
ADAS Design Consideration: Camera
ADAS Design Consideration RADAR, Ultrasonic sensors
Summary - ADAS Features-3
Module 05 - ADAS: Verification and Validation
Introduction & Need for Verification and Validation
ADAS: V-Model
ADAS: Design Verification and System Validation
ADAS: Integration Level Validation
ADAS: V&V Workflow, Vehicle Level Calibration & Validation
ADAS: Functional Safety
Summary - ADAS: Verification and Validation
Module 06 - Digital Transformation, IOT
ADAS: Digital Transformation
ADAS: Key Drivers and Challenges in Digitalization
ADAS: Industry 4.0
ADAS: Internet of Things
ADAS: Artificial Intelligence
ADAS: Machine Learning
Summary - Digital Transformation, IOT
Course 03 - Intelligence and Fusion in Smart Mobility
32 Learning Materials
AI, ML and DL
Basics of AI, ML and Deep Learning
ML: Data and Data Sampling
Supervised and Unsupervised Machine Learning
Summary - AI, ML and DL
Machine Learning
ML: Data and Data Sampling
ML: Clustering
ML: Neural Networks-1
ML: Neural Networks-2
Summary - Machine Learning
Computer Vision
Random Forest Algorithm
Computer Vision - 1
Computer Vision - 2
Computer Vision - 3: CNN
Computer Vision - Use Cases
Summary - Computer Vision
Decision Arbitration, PAC Learning
Decision Arbitration: Basics and Types
PAC Learning
Illustration: PAC Learning
Reinforcement Learning
Summary - Decision Arbitration, PAC Learning
Levels of Functionality, Multifunctional Architecture
Autonomous Car Sensing System
Levels of Functionality
Multifunctional Architecture
Vehicle & ADAS Architecture
Summary - Levels of Functionality, Multifunctional Architecture
LIDAR, Sensor Fusion, MBD
LIDAR
LIDAR Interface & Function
Sensor Fusion: Types and Level
Sensor Fusion: Architecture
Sensor Fusion: KPIs, Design Considerations & Challenges
Model Based Development
Summary - LIDAR, Sensor Fusion, MBD
Course 04 - Legal Liabilities and Complainces for ADAS
30 Learning Materials
Role of ML in ADAS
Levels of Autonomy - ADAS Features
Motion Planning, Decision Making
Data-Driven Approach
Finite State Machine & Trajectory Generation
Visual Odometry
Summary - Role of ML in ADAS
Automotive Cybersecurity
Automotive Cybersecurity: Introduction
Physical Access Risk and Mitigation
Remote Access Risk
Connected and Automated Vehicle Risks
Telematics Access Risk
EVSE Threats and Vulnerabilities
Summary - Automotive Cybersecurity
ADAS Liabilities & Legal issues
Liabilities and Legal Issues
ADAS: Liabilities
ADAS Certification: Classical Approach
ADAS Certification: 3 Pillars and New Approach
ADAS Cybersecurity Standards and Landscape
Summary - ADAS Liabilities & Legal issues
ADAS Issues System Testing
ADAS Issues: System Issues and Defects
ADAS Issues: Functional Issues and Vehicle Level Testing
ADAS System Testing - 1
ADAS System Testing- Exit Warning, Lane Departure Warning, ACC
ADAS System Testing- Lane Departure & Lane Keep Assist, Rear Cross Traffic
Summary - ADAS Issues System Testing
Embedded Systems, Standards
Embedded System: Introduction and Types
Real-Time Embedded systems
Core of Embedded Systems
ASIC, PLDs, COTS
Standards
Program Instructor
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evACAD
170 Courses • 342 Students
evACAD is a leading e-mobility education platform dedicated to building skilled talent for the electric vehicle and clean energy industry. Backed by pManifold Business Solutions Pvt. Ltd., it offers industry-aligned programs ranging from certificate courses to executive M.Tech degrees, designed in collaboration with top institutions. With a strong focus on hands-on learning, real-world projects, and expert mentorship, evACAD has trained thousands of learners across 50+ countries. Its mission is to accelerate global EV adoption by equipping professionals and students with the latest knowledge and practical skills in e-mobility and sustainability.
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