2024/25 Taught Postgraduate Module Catalogue

MECH5170M Connected and Autonomous Vehicles Systems

15 creditsClass Size: 120

Module manager: Dr Krzysztof Kubiak
Email: K.Kubiak@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2024/25

Pre-requisite qualifications

UG Degree in Mechanical Engineering or Automotive Engineering, and basic Programming Skills

This module is not approved as an Elective

Module summary

This module provides comprehensive knowledge of Connected and Autonomous Vehicle technology. It will cover aspects of sensors selection, data acquisition, path planning, localisation, artificial intelligence algorithms, communication, testing and validation.

Objectives

This module aims to provide a comprehensive understanding and in-depth knowledge of connected and autonomous vehicles. On completion of this module, students will be able to:
1. Recognise the distinctions between Advanced Driving Assistance Systems (ADAS), connected and autonomous vehicles, and describe the main system components.
2. Assess and compare the functionality of various automotive sensors, as well as their operating principles, performance, and limitations.
3. Show their understanding of autonomy levels, path planning, and localisation.
4. Assess the performance and security of embedded automotive vehicle control systems.
5. Investigate methods for system validation and testing including hardware/software in the loop.
6. Demonstrate knowledge of the regulatory framework, approval processes, and ethical issues.

Learning outcomes
On successful completion of the module students will have demonstrated the following learning outcomes :

1. Demonstrate in-depth knowledge and understanding of the autonomous vehicle system's design and functions.
2. Critically evaluate and compare different automotive sensors, working principles, performance, limitations, and sensor fusion strategies.
3. Select and analyse path planning algorithms and models, evaluate task allocation and judge its advantages and limitations.
4. Assess and critically evaluate embedded vehicle control systems in the context of connected and autonomous vehicle safety and security risks.
5. Understand and apply testing and validation strategies of sensors, models and programming code of autonomous systems.
6. Demonstrate knowledge and understanding of regulatory requirements, professional responsibilities, and the ethical implications of connected and autonomous vehicles.

Upon successful completion of this module the following Engineering Council Accreditation of Higher Education Programmes (AHEP) learning outcome descriptors (fourth edition) are satisfied:
7. Apply a comprehensive knowledge of mathematics, statistics, natural science and engineering principles to the solution of complex problems. Much of the knowledge will be at the forefront of the particular subject of study and informed by a critical awareness of new developments and the wider context of engineering. (M1)
8. Formulate and analyse complex problems to reach substantiated conclusions. This will involve evaluating ­­­ data using first principles of mathematics, statistics, natural science and engineering principles, and using engineering judgment to work with information that may be uncertain or incomplete, discussing the limitations of the techniques employed. (M2)
9. Select and critically evaluate technical literature and other sources of information to solve complex problems. (M4)

Skills Learning Outcomes

On successful completion of the module students will have demonstrated the following skills:

Problem solving & analytical skills; Critical thinking, Systems thinking, Integrated problem solving, Programming

Syllabus

1. Introduction to levels of autonomy, Advanced Driving Assistance Systems (ADAS), Connected and Autonomous Vehicles (CAV).
2. Sensors, sensor fusion, machine vision, perception, and visualisation.
3. Path planning, localisation, autonomy, decision making, and Artificial Intelligence algorithms.
4. Embedded Vehicle Control Systems, functional safety ISO26262, safety-critical systems including network and communication protocols.
5. Virtual Learning Environment, Software-in-Loop, Hardware-in-Loop Testing and Validation.
6. Regulatory framework and ethical challenges.

Methods of Assessment

We are currently refreshing our modules to make sure students have the best possible experience. Full assessment details for this module are not available before the start of the academic year, at which time details of the assessment(s) will be provided.

Assessment for this module will consist of;

1 x Coursework
1 x In-person closed book exam

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	9	2.00	18.00
Practical	1	2.00	2.00
Tutorial	2	2.00	4.00
Independent online learning hours			11.00
Private study hours			115.00
Total Contact hours			24.00
Total hours (100hr per 10 credits)			150.00

Opportunities for Formative Feedback

Formative feedback will be provided through tutorials and practical sessions where the module leader will be available to discuss the progress with individual students.

Reading list

The reading list is available from the Library website

Last updated: 30/04/2024

Disclaimer

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