Introductory description

Autonomous/Automated Vehicles (AVs) aim to enhance and improve the safety and efficiency of future mobility.
This module introduces and explores key subjects related to AV development, including understanding the complexity of autonomous vehicle systems, human factors influencing the design of future AVs, analysis of key perception sensors, applications of machine learning, and the role of networks and communications in supporting AVs.
These topics are presented from both theoretical and practical perspectives, encouraging independent critical evaluation of the subject matter.
When this module is delivered on DA Programmes, it is delivered in a 1-one-week block with 6 weeks to submit, rather than over 4 weeks.

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

This module covers the topics are related to: system complexity in Automated Vehicles (AVs) Levels of Autonomy • AV testing • Supply chain and business models of mobility as service; Safety standards and analysis techniques; • trust, AV stakeholders, wellbeing and sensing the human • Perception Sensors • Wired(CAN, Lin,...) and wireless (LTE, 5G, DSRC)communication for AVs • Data science basis for machine intelligence and neural network

Learning outcomes

By the end of the module, students should be able to:

• Demonstrate an in-depth knowledge of key principles underpinning human interaction and apply it to compare/criticise the design. [AHEP: M1, M3, M4, M5]
• Evaluate and compare the performance of different automotive perception sensors. [AHEP: M1, M2, M3]
• Demonstrate a critical high-level understanding of challenges associated with data science and machine learning techniques, in the context of safe Automated Vehicles. [AHEP: M1, M2, M3, M6]
• Demonstrate an applied knowledge of automotive system complexity and their testing. [AHEP: M1, M2, M6]
• Critically evaluate wired and wireless communication technologies in the SCAV context. [AHEP: M1, M3, M6]
• Collaborate as a team to apply acquired knowledge in critically evaluating and implementing technical choices in the design of autonomous vehicles (AVs). [AHEP: M1, M4, M5, M16, M17]

Indicative reading list

https://warwick.rl.talis.com/lists/E7D477CC-571D-F7D9-23E9-4206AD1CB56A.html

Subject specific skills

The student will gain many skills relates to autonomous vehicles. They will gain the knowledge on system complexity in AVs and their requirements, get experience and understanding of test techniques for AVS; apply that t understanding to create testing scenarios, also using dedicated simulation software; understand the importance of human factors and how they inform design; knowledge of supply chain in the automotive industry and business model of mobility as services; understand and evaluate different perception sensors; understand AV wireless and wired communications; understanding of data science basis for machine intelligence and the concept of neural network.

Transferable skills

Team work - work effectively in a group or team to achieve goals
Personal motivation, organisation and time management skills
Research and analytical skills
Project and program management skills,
The ability to gather and interpret information
Industry knowledge by guest lecturer