Master’s in ADAS and Autonomous Driving Engineering
Online master's programme of 1,900 hours in ADAS and autonomous driving engineering, structured in 12 modules covering vehicle sensors, perception, localisation and maps, prediction and planning, vehicle control, ADAS functions, system architectures, safety and validation, human factors and regulation, with an assigned technical tutor.
Master’s in ADAS and Autonomous Driving Engineering — studying from Ireland
Ireland's regulated industries, including aviation, medical devices, energy, transport and food, require rigorous safety, reliability and compliance processes. Engineers in regulation, safety and homologation roles prepare certification evidence, perform reliability and risk analysis and manage conformity assessment. Key regulators such as the Health and Safety Authority, the Irish Aviation Authority and the Health Products Regulatory Authority set requirements that span multiple sectors. National standards are maintained by the National Standards Authority of Ireland, which represents Ireland within European and international standardisation.
Fees for Ireland: €8,920 (Euro), with instalments and employer sponsorship available.
Relevant bodies in Ireland
Typical roles
Questions from Ireland
Which Irish bodies handle regulation and homologation, and does this qualification relate to them?
In Ireland, regulatory and safety matters involve bodies such as the Health and Safety Authority and the National Standards Authority of Ireland for standards work. Professional engineering status is typically pursued through Engineers Ireland. SEIUM's qualifications are private and not accredited by these bodies, so they do not grant registration, approval or homologation rights.
How do Irish employers in RAMS and safety-critical sectors regard private online qualifications?
Employers in safety-critical industries in Ireland usually require verifiable competence and recognised certifications for RAMS and homologation roles. A private online qualification may complement your experience, but whether it counts is entirely at the employer's discretion. There is no guarantee of recognition or of any role.
How much time does the programme take, and can I pay in instalments?
The programme is fully online and taught in English, so you can study from Ireland at your own pace. Durations are 300, 800 or 1,900 hours depending on the course. Fees can be paid in instalments, employer sponsorship is possible if your company agrees, and each student receives an assigned technical tutor.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Understand the levels and architectures of automated driving.
Select and calibrate vehicle sensors.
Develop perception and localisation algorithms.
Implement motion planning and control.
Specify ADAS functions.
Validate systems through scenarios and simulation.
Analyse the regulatory framework for automated driving.
Who it's for
- Autonomous driving engineers at manufacturers and technology suppliers.
- Perception engineers working with cameras, radar and lidar.
- Planning and control engineers.
- ADAS validation engineers.
- Automotive software architects.
- Sensor fusion specialists.
- Engineering or science graduates aiming to enter the automotive industry.
What you'll work with
- SAE J3016:2021 (taxonomy of driving automation)
- ISO 26262:2018 (road vehicle functional safety)
- ISO 21448:2022 (SOTIF, safety of the intended functionality)
- UNECE Regulation No. 157 (Automated Lane Keeping Systems)
- Implementing Regulation (EU) 2022/1426 (type approval of automated driving systems)
- ISO 34502:2022 (scenario-based safety evaluation of automated driving systems)
- UL 4600 (safety evaluation of autonomous products)
- Regulation (EU) 2019/2144 (general vehicle safety)
- CARLA
- ROS 2
- Autoware
- MATLAB/Simulink (Automated Driving Toolbox)
- Python (PyTorch)
12 modules · 1900 h
1.1SAE J3016 levels of automation1.2Difference between ADAS and automated driving1.3Use cases: motorway, city and logistics1.4Industrial state of the art1.5Robotaxis and commercial services1.6Autonomous lorries on motorways1.7Expected safety benefits1.8Risks and limitations1.9Technology roadmaps1.10Case study: analysis of a commercial robotaxi deployment
2.1Cameras and their calibration2.2Millimetre-wave radar2.3Mechanical and solid-state lidar2.4Ultrasonic sensors2.5GNSS and inertial systems2.6High-definition maps2.7Sensor cleaning and degradation2.8Adverse weather conditions2.9Selecting the sensor suite2.10Lab: camera–lidar calibration
3.1Object detection with deep learning3.2Semantic image segmentation3.3Point cloud perception3.4Early and late sensor fusion3.5Multi-object tracking3.6Depth estimation3.7Lane and sign detection3.8Public datasets3.9Perception metrics3.10Practical exercise: object detection with a YOLO model
4.1GNSS-RTK localisation4.2GNSS-IMU fusion with Kalman filters4.3Visual and lidar SLAM4.4Localisation in HD maps4.5Map maintenance4.6Map formats4.7Required position accuracy4.8Localisation integrity4.9Failures and degradation4.10Lab: localisation with an extended Kalman filter
5.1Agent trajectory prediction5.2Route planning5.3Behaviour planning5.4Motion planning5.5Trajectory optimisation5.6Model predictive control5.7Interaction with other road users5.8End-to-end planning5.9Comfort and safety constraints5.10Practical exercise: lattice trajectory planner in Python
6.1Vehicle dynamic models6.2Lateral vehicle control6.3Longitudinal speed control6.4Drive-by-wire6.5Actuator redundancy6.6Stability and grip limits6.7Controller tuning6.8In-vehicle validation6.9Integration with ADAS6.10Lab: lateral control with Stanley and Pure Pursuit
7.1Autonomous emergency braking7.2Adaptive cruise control7.3Lane keeping assist7.4Lane change assist7.5Traffic sign recognition7.6Traffic jam assist7.7Remote automated parking7.8Driver monitoring7.9Euro NCAP assessment7.10Case study: functional specification of a motorway assistant
8.1Centralised and zonal architectures8.2High-performance computers8.3ROS 2 and AUTOSAR Adaptive middleware8.4Redundancy and graceful degradation8.5In-vehicle communications8.6Software-defined vehicle8.7Thermal management and power consumption8.8Hardware and software integration8.9Software updates8.10Practical exercise: functional architecture of a Level 3 system
9.1ISO 26262 functional safety9.2ISO 21448 SOTIF9.3Scenario-based validation9.4Large-scale simulation9.5Track testing9.6Public road testing9.7Safety metrics9.8System safety case9.9UL 4600 standard9.10Lab: scenario validation in CARLA
10.1Driver–system interaction10.2Transition of control10.3Driver situational awareness10.4Overreliance10.5Driver monitoring10.6Communication with pedestrians10.7External human–machine interfaces10.8Acceptance and trust10.9User training10.10Workshop: designing a transition-of-control interface
11.1UNECE Regulation R157 ALKS11.2Regulation (EU) 2022/1426 for automated driving systems11.3Spanish testing regulations11.4Regulation in Germany, the United Kingdom and the US11.5Civil liability and insurance11.6Data protection11.7Ethics of automated driving11.8Mandatory cybersecurity under R15511.9Expected regulatory developments11.10Case study: comparative analysis of regulatory frameworks
12.1Defining the function and ODD12.2System architecture12.3Perception and localisation12.4Planning and control12.5Safety analysis12.6Validation in simulation12.7Regulatory fit of the function12.8Conclusions and future work12.9Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within the intake, so the programme can be combined with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is CARLA, ROS 2, Autoware, MATLAB/Simulink (Automated Driving Toolbox) and Python (PyTorch), in free, academic or evaluation versions. Exercises are based on real procedures for developing perception and planning algorithms, scenario-based validation in simulation and sensor calibration. Assessment is continuous by module, plus the final Master's Thesis.
Standards covered: SAE J3016:2021 (taxonomy of driving automation), ISO 26262:2018, ISO 21448:2022 (SOTIF), UNECE Regulation No. 157 (ALKS), Implementing Regulation (EU) 2022/1426 (automated driving systems), ISO 34502:2022 (scenarios for automated driving systems), UL 4600 (safety evaluation of autonomous products), Regulation (EU) 2019/2144.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- A university degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- An internet connection and a computer capable of running the programme software.
- English sufficient to read technical standards.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with CARLA, ROS 2, Autoware, MATLAB/Simulink (Automated Driving Toolbox) and Python (PyTorch), using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.
A degree in engineering, science or architecture, or equivalent professional experience, plus a suitable computer, an internet connection and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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