Autonomous Vehicles (H7122)
Autonomous Vehicles
Module H7122
Module details for 2022/23.
15 credits
FHEQ Level 6
Module Outline
This module introduces the concepts and operating principles along with challenges and technology of autonomous vehicles with the focus on the planar vehicles. Topics to be covered will include:
• A systematic understanding and practical experiments of vehicle dynamics focusing on kinematics and dynamics of unicycle robots for modelling, simulation and control of the longitudinal and lateral motions.
• A systematic understanding and practical experiments of vision-based perception including sensors, image processing techniques to percept the surrounding environment, and different techniques to represent the precepted maps.
• A systematic understanding and practical experiments of the mapping and Localisation algorithms including odometric and simultaneous mapping and localisation (SLAM).
• A systematic understanding and practical experiments of the potential field and search-based motion planning algorithms to achieve a destination while avoiding obstacles.
• A systematic understanding of advanced estimation and control techniques for autonomous vehicles.
The syllabus covers the following AHEP4 learning outcomes: C1, C2, C3, C6, C12, C13, C16, C17, M1, M2, M3, M6, M12, M13, M16, M17
Module learning outcomes
A systematic understanding of operating principles of autonomous vehicles including interpreting main concepts, challenges and state-of-the-art technology
A systematic understanding of modern algorithms for perception, mapping, path planning and control of autonomous vehicles using visual and depth cameras and other sensors
Application of the mathematical theories to design and real-time implementation of complex algorithms for autonomous vehicles
Analysis of performance of autonomous vehicle algorithms by practical experiments using robots and MATLAB/SIMULINK tools in laboratory
| Type | Timing | Weighting |
|---|---|---|
| Coursework | 50.00% | |
| Coursework components. Weighted as shown below. | ||
| Group written submission | T2 Week 10 | 100.00% |
| Computer Based Exam | Semester 2 Assessment | 50.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
| Term | Method | Duration | Week pattern |
|---|---|---|---|
| Spring Semester | Lecture | 2 hours | 11010101011 |
| Spring Semester | Workshop | 1 hour | 11010101011 |
| Spring Semester | Laboratory | 3 hours | 00101010100 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
Dr Arash Moradinegade Dizqah
Assess convenor
/profiles/449994
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