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Engineering in Autonomous Vehicles (Postgraduate Diploma, L9, 60 ECTS)

  • Status: Apply Now

  • Campus: Blended

  • years: 1.5

  • Fees: HCI Funded for 2024. See Fees Section below

Course Overview

The Postgraduate Diploma in Engineering in Autonomous Vehicles Engineering is designed for engineering professionals working or aspiring to work in the mobility industry. Students can broaden their skill set for careers in Autonomous Vehicle Engineering and Technology, Design, Maintenance, Upgrading and Development.

This programme has been developed as a collaboration between TUS (Technological University of the Shannon) and Future Mobility Campus Ireland (FMCI). Students will benefit from in-person laboratory and workshop sessions taking place on both TUS and FMCI campuses. The programme will also benefit from a range of industry experts who will share their in-depth knowledge of this emerging growth market. FMCI is Ireland’s first complete development centre and full-scale test bed, based adjacent to Shannon Airport. The facility focuses on comprehensive mobility technologies that span both ground (autonomous driving, micro-mobility, smart cities, V2X communications) and air (unmanned drones, eVTOL, AAM, UTM) uses.


Contact Details

General Queries

Flexible Learning Office


Telephone: (061) 293802

Academic Queries

Ailbe Burke


What are the entry requirements?

a) A minimum PASS honours bachelor degree (Level 8) in a cognate discipline
(b) A minimum PASS honours bachelor degree (Level 8) in a non-cognate discipline with considerable experience and/or ability evidenced by an RPL portfolio of prior experience and learning
(c) Equivalent Qualifications. Applicants with equivalent qualifications on the European and International frameworks will also be considered. International students must evidence a proficiency in English language (IELTS 6.0).

Recognised Prior Learning (RPL) – Assessment
Please review the academic entry requirements for this programme.
If you do not hold these qualifications but would like your application to be assessed under RPL please select YES on the online application form.

 Applicants who do not have English as their first language must ensure they satisfy English Language requirements. For entry to undergraduate courses, a score of 5.5 in an IELTS or equivalent exam is required. For postgraduate courses, a score of 6.0 in an IELTS or equivalent exam is required. It is the responsibility of the applicant to ensure their English proficiency meets these requirements.

Course Content

  • Hardware and Software Architecture for Autonomous Systems

    In this module, students will delve into ADAS system vehicle layout, components and system architectures. Here the learner will evaluate the role cognitive control units play in perceiving and interacting with the environment, enabling the recognition of fellow vehicles and traffic participants. This advanced level of intelligence facilitates the autonomous operation of vehicles, enhancing safety, security, comfort, energy efficiency, and time management. Students will gain comprehensive insights into the intricate information transfer between vehicle components and also the user, road, infrastructure, and traffic data systems. Through vehicle operation management and embedded software system, they will learn what orchestrates and drives the system for efficiency while being environmentally conscious throughout the driving cycle. The module will also focus on the crucial role of sensors and electromagnetic wave emitters, such as radar and light, in providing detailed information about a vehicle’s status and its surroundings. The learner will explore how mobile perception systems derive information about both static and dynamic objects. Additionally, the module will cover the significance of environmental recognition, drawing on a spectrum of data sources including sensor inputs, car-to-car, car-to-infrastructure, and back-to-back communications, as well as accumulated knowledge from prior journeys. Through an in-depth examination of vehicle hardware and software architecture, students will understand how robust systems facilitate swift and dependable data processing.

  • Modelling and Simulation for Hazard Identification and Risk Analyses

    In this module, students will embark on an in-depth exploration of virtual prototypes and simulation techniques, gaining a robust understanding of their practical applications. With the use of simulation software platforms, this course aims to impart comprehensive knowledge about the principles, characteristics, and benefits of various modelling techniques, emphasising their relevance in contemporary engineering and design disciplines. The module will examine the fundamental concepts underpinning virtual prototypes, providing students with a solid theoretical foundation. Through engaging practical examples and hands-on exercises, participants will learn how to apply these concepts in real-world scenarios, equipping them with a valuable skill set crucial in today’s rapidly evolving technological landscape. Furthermore, the module will introduce a diverse range of cutting-edge tools and software platforms instrumental in implementing virtual prototypes for simulations. Through practical demonstrations and guided exercises, students will become adept at leveraging these tools to conduct precise and reliable simulations across a spectrum of domains. This hands-on experience will empower them to tackle complex engineering challenges with confidence and precision. Throughout the module, students will be encouraged to engage in critical discussions and collaborative projects, fostering a dynamic learning environment that promotes the exchange of ideas and best practices. By the conclusion of this course, participants will possess a comprehensive skill set in virtual prototyping and simulation techniques, positioning them at the forefront of innovation in their respective fields. By successfully completing this module, students will not only gain a deep understanding of virtual prototypes but also acquire the practical proficiency to apply these concepts in a professional setting, making them invaluable assets in the competitive landscape of modern engineering and design industries.

  • Automotive Sensing Technology, Systems and Architecture

    Develop a knowledge of International, European and National Regulations for the development and testing of autonomous systems.

  • Regulations, Standards and Safety for Autonomous Vehicles

    This module can help developers, engineers, and policymakers navigate the complex landscape of regulations, standards, and safety considerations associated with autonomous vehicles. Regulatory Landscape, ISO 26262 – Functional Safety for Road Vehicles, European Commission Regulations, Functional Safety Management, Cybersecurity Standards (ISO/SAE 21434), SOTIF (ISO 21448) – Safety of the Intended Functionality, Communication Protocols and Standards, Human Factors and User Interface Standards, Testing and Validation Standards, Liability and Insurance Compliance, Ethical Considerations and Guidelines.

  • Autonomous Vehicle Embedded Systems

    This module will provide a comprehensive overview of embedded systems within autonomous vehicles. Building from an overview of vehicle electrical and mechanical systems through to the architecture of systems and emerging trends. Vehicle based communication networks will be assessed and the emerging solutions and challenges associated with AV.

  • Vehicle Communication for Intelligent Transport Systems

    The aim of this module is to provide the learner with an up-to-date, comprehensive knowledge of the main wired and wireless communications technologies that are used in current and future production of Autonomous Vehicle systems.

More Information

  • The proposed delivery schedule is subject to change.

    Modules are to be delivered over 1.5 years (3 semesters: Semester 1 September – December 2024, Semester 2 January – April 2025, Semester 3 April – June 2025) in a blended format of online learning and in-person workshops.

    Each semester comprises

    • Online (Live): 2 hours per week per module for 12 weeks (Tuesday and Thursday 7 – 9pm)
    • Online (pre-recorded): 2 hours per week Semester 1 and 2, 3 hours per week Semester 3
    • In-person workshops : 4 Saturdays per semester
  • Each 5 credits will normally equate to approximately 100 Total Learning Hours. Total Learning Hours includes the time you spend in class (lectures, tutorials, practical elements) and the time you spend completing work outside of college.  The balance between these two varies by discipline, and by level of study. You should bear in mind that the workload will increase at particular times e.g. when assignments are due.

  • Students will be assessed on their learning by a variety of strategies, including the use of continuous assessment through projects, coursework, multiple choice questions, activities, presentations and assignments which will reinforce learning through a gradual application of new knowledge and skills. Projects will provide learners with the opportunity to develop new skills and strategies for learning and development to industrial standards.

  • Postgraduate Diploma in Engineering in Autonomous Vehicles (Level9 , 60 Credits)

  • HCI funding available for eligible applicants. Successful applicants in employment qualify for 90% HCI funding & are liable for the balance of the 10% fee of €875. Successful applicants on a qualifying DSP payment qualify for 100% funding.

    Go to for more information on eligibility.

  • Application Deadline: 11 August 2024. Places are allocated on a first come first served basis, prioritizing unemployed and returning applicants. Course will be closed once the maximum number of applicants is reached. Courses run subject to viable numbers.