Course 4 falls under the workshop series Self-driving Cars & AI and focuses on the analysis, explanation and synthesis of algorithms for: 

  1. Basic automations in road networks
  2. Recognition of traffic signs using neural networks and visual data
  3. Autonomous navigation with obstacle avoidance
  4. Expert systems for decision-making in road networks

Note: Participation in Cycle 4 does not require completion of the other cycles of the project.

Course 4 consists of the following sessions: 

Seminar 1: General Cycle Description and Introduction to Basic Automations

General description of Cycle 4. Brief introduction to the Python programming language. Description of the problem of autonomous navigation in a controlled road network. Explanation and implementation of basic automations in controlled road networks. 

Seminar 2: Recognition of Traffic Signs Using Neural Networks

Introduction to the artificial neuron (perceptron) and multilayer neural networks. Methodology for training a neural network using camera data. Implementation of a neural network for recognizing traffic signs and traffic lights using TensorFlow/Keras libraries. Testing the neural network in a simulated environment. 

Seminar 3: Algorithms for Autonomous Navigation and Obstacle Avoidance

Introduction to grid-based maps and optimal route-finding. Basics of obstacle detection and avoidance using camera data. Programming and implementation of an intelligent algorithm for safe autonomous navigation. 

Seminar 4: Autonomous Navigation in Road Networks

Introduction to expert systems. Design of an expert system for decision-making in road networks. Implementation and experimental testing of the expert system. 

Seminar 5: Experimental Operation of the Complete System

Integration of the expert system with the autonomous navigation algorithm. Testing the complete system in a simulated environment. Experimental trials of the complete system. 

References - Supplementary Material 

  1. https://www.python.org/
  2. https://jupyter.org/
  3. https://www.tensorflow.org/
  4. https://www.w3schools.com/python/
  5. https://www.learnpython.org/
  6. https://www.pythontutorial.net/
  7. Neural Network
  8. Graph_Theory
  9. D3 Grath Theory
  10. Algorithm Α*
  11. Python Eperta
  12. CoppeliaSim Manual

 

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