Levels of Autonomy and its application in transportation.
Performance metrics, kinematics and dynamics of vehicles.
Automotive and Aeronautical Sensors – classification, design, limitations and interactions.
Intelligent control of connected and automated vehicles.
Visual object detection and recognition for intelligent vehicles.
Cognition and decision making in autonomous vehicles.
Developing and validating intelligent vehicle control systems.
Human/Technology interaction in autonomous systems.
Ethical decision making in autonomous systems.
Autonomous systems in transportation and aviation.
Latest trends in research around autonomous transportation.

Lectures / tutorials – 24 hours
Practical laboratory work – 24 hours
The lectures will focus on the knowledge needed and practical application of each new topic. Group learning will be encouraged. ¿
The tutorials will be run as a question answer session where students can ask specific questions or work on example problems.

Buehler, M., Iagnemma, K., & Singh, S. (2009); The DARPA Urban Challenge: Autonomous Vehicles in City Traffic, 2010 edn. Springer
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.
Liu, S., Li, L., Tang, J., Wu, S., & Gaudiot, J-L. (2017); Creating Autonomous Vehicle Systems. Morgan & Claypool Publishers.
McGrath, M. E. (2018); Autonomous Vehicles: Opportunities, Strategies, and Disruptions. Independently published.
Yu, H., Li, X., & Murray, R. M. (2018); Safe, Autonomous and Intelligent Vehicles (Unmanned System Technologies), 1st edn. Springer.

PCs running MATLAB with Control Toolbox and Robotics Toolbox

Library resources (books, journals accessible online, full IEEE Xplore access to academic papers, and various magazines)

None

1. Classify Autonomous Vehicles by their autonomy levels and explain the technical issues that define the autonomy level. (AHEP 3: SM7M, EA5m, P9m, G1)

2. Define and explain the features of different sensors commonly used in autonomous vehicles. Evaluate control solutions for these in real-world scenarios. (AHEP 3: SM7M,EA6M, EA7M, P9m, G1)

3. Apply and analyse fundamental methods used in mobile automated systems, such as route planning and obstacle avoidance. (AHEP 3: SM7M, SM8M,EA6M, EA7M, D9M, D11M, P9m, G1)

4. Critically appraise research advances in autonomous vehicle technology. (AHEP 3:SM8M, EA5m, P9m, G1)

100% Project assessing all learning outcomes. Meeting AHEP Outcomes SM7M, SM8M, EA6M, EA5m, EA7M, D9M, D11M, P9m, G1