Artificial Intelligence for Autonomous Vehicles
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Follow on Instagram for UpdatesArtificial Intelligence for Autonomous Vehicles Syllabus — Unit-wise Content
The official GTU curriculum for Artificial Intelligence for Autonomous Vehicles (subject code ME02064071) as prescribed for EVT · Semester 2 divides the course into 4 units, covering 51 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (ME02064071)Unit 1 INTRODUCTION TO AI AND ARTIFICIAL NEURAL NETWORK
- Introduction to AI, Introduction to Expert systems
- History of neural network research
- Basic concepts of Neural Networks
- Human brain
- Model of Artificial Neuron
- Neural Network architectures
- Single layer feed forward Network
- Multi-layer feed forward network
- Recurrent networks
- Feedback networks and Radial Basis Function Networks
- Characteristics of NN, Learning Methods
- Error Correction Learning
- LMS and Back Propagation Algorithm
- Statistical Nature of the Learning Process
- Training Examples of models. 16 Level: PG Branch: Electric Vehicle Technology Subject Code: ME02064071 Subject Name : Artificial Intelligence for Autonomous Vehicles
Unit 2 FUZZY LOGIC SYSTEM
- Comparison between Fuzzy and crisp logic
- Fuzzy sets
- Membership function
- Basic fuzzy set operations
- properties of Fuzzy set, fuzzy relations
- Fuzzy interference system
- Fuzzy rule based system
- Defuzzification methods
- Fuzzy Neural Networks
Unit 3 AI IN EV SAFETY (AUTOMATIVE DIAGNOSTICS AND INTERFACE)
- Various faults in Electric Vehicles
- Battery faults
- motor faults
- mechanical faults
- Wiring faults
- AI application for various fault identification
Unit 4 AUTONOMOUS DRIVER ASSISTANT SYSTEM
- Introduction to Autonomous Driver Assistance System (ADAS)
- Distributed vs Centralized Processing
- Integration of ADAS Technology into Vehicle Electronics
- Sensors and Data acquisition in ADAS
- GNSS, GPS, IMU
- Introduction to Machine Learning and Deep Learning in ADAS Human Machine Interaction
- HMI for Advanced Driver Assistance Systems
- Physical and Cognitive Factors Related with HMI Present ADAS Technology Examples like intelligent head light control
- evasive steering support Adaptive cruise control
- rear cross traffic alert
- front cross traffic alert
- vehicle exit alert
- forward collision warning
- vehicle turn assistance
- blind spot detection
- parking assistance system
- traffic sign recognition lane assist system
- driver monitoring system
- driver drowsiness system
- 360 view system
- intelligent braking systems
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