This module explores the latest trends in research on autonomous transportation, covering ethical decision-making in autonomous systems, their application in transportation and aviation, levels of autonomy, performance metrics, kinematics, and the dynamics of vehicles. Additionally, the module will delve into automotive and aeronautical sensors, providing an understanding of their classification, design, limitations, and interactions. The module further addresses intelligent control of connected and automated vehicles, visual object detection and recognition for intelligent vehicles, cognition and decision-making in autonomous vehicles, and the development and validation of intelligent vehicle control systems. Moreover, it explores the intricate dynamics of human-technology interaction within the realm of autonomous systems. The module will also provide an in-depth study of PCB design, prototype and manufacture.

A 5000-word individual project report weighted at 100% assessing learning outcomes 1, 2, 3, 4 and 5. Meeting AHEP 4 Outcomes: M1, M2, M4, M5, M17

Professional Body requirements mean that a minimum overall score of 50% is required to pass a module, with each element of assessment requiring a minimum mark of 40% unless otherwise stated.

This module will enable students to gain understanding, apply knowledge, analyse and evaluate problems and create solutions through a variety of activities, including:¿

- Learning on all aspects of the indicative content will be facilitated by classroom-based lectures, tutorials, laboratory-based practical experiments.¿

- Independent study: reading, teamwork activities, information gathering, presentations, student-centred learning, assignment preparation.¿

1. Classify autonomous vehicles by their autonomy levels and elucidate the technical issues that define the autonomy level. (AHEP 4: M1)

Enquiry,

Knowledge and Understanding, Learning

2. Define and explain the features of different sensors commonly used in autonomous intelligent vehicles, evaluate control solutions for these in real-world scenarios. (AHEP 4: M1, M2, M17)

Analysis,

Knowledge and Understanding,

Application

3. Design and manufacture a printed circuit board based prototype and provide its critical analysis. (AHEP 4: M5)

Problem Solving

4. Apply and analyse fundamental methods used in mobile automated systems, such as route planning and obstacle avoidance. (AHEP 4: M1, M5)

Problem Solving,

Reflection

5. Critically appraise research advances in autonomous vehicle technology. (AHEP 4: M4, M17)

Application,

Communication

PCs running MATLAB or equivalent software with Control Toolbox and Robotics Toolbox

Microcontrollers (such as Arduino Nano, ESP32 or equivalent)

Various sensors and other equipment such as Rechargeable Batteries, Motor Drivers, Motors, Camera, PCB Board, Vero Boards etc.

Buehler, M., Iagnemma, K., & Singh, S., (2009); The DARPA Urban Challenge: Autonomous Vehicles in City Traffic, 2010 edn. Springer. ISBN – 13: 978-3642039904

Cheng, H., (2011);¿Autonomous intelligent vehicles: theory, algorithms, and implementation. Springer Science & Business Media. ISBN – 13: 978-1447122791

Du, M., (2022) Autonomous Vehicle Technology: Global Exploration and Chinese Practice. Springer Nature. ISBN- 13: 978-9811941429

Eliot, L., & Eliot M., (2017); Autonomous Vehicle Driverless Self-Driving Cars and Artificial Intelligence: Practical Advances in AI and Machine Learning, 1st edn. LBE Press Publishing. ISBN- 13: 978-0692051023

Liu, S., Li, L., Tang, J., Wu, S., & Gaudiot, J-L., (2017); Creating Autonomous Vehicle Systems. Morgan & Claypool Publishers. ISBN – 13: 978-1681730073

McGrath, M. E., (2018); Autonomous Vehicles: Opportunities, Strategies, and Disruptions. Independently published. ISBN -13: 978-1980313854

Yu, H., Li, X., & Murray, R. M., (2018); Safe, Autonomous and Intelligent Vehicles (Unmanned System Technologies), 1st edn. Springer. ISBN- 13: 978-3319973005

The rapid growth of autonomous vehicles, encompassing drones, driverless cars, and intelligent vehicular functions, presents a significant developmental challenge for industries such as defence, aerospace, automotive, and marine. To support this technological advancement, a deep understanding of key autonomy aspects is essential, including dynamics, control, guidance, navigation, decision-making, sensor and data fusion, communication, and networking. This comprehensive approach ensures the robustness and dependability of electronics, communications (e.g., V-2-V, V-2-I), and control systems, contributing to the success of autonomous technologies. As many electronic products use a Printed Circuit Board (PCB), this module will provide practical experience of how to design and assemble PCBs. You will work on related projects, which will involve defining the problem, identifying appropriate hardware and software, and implementing the entire system.