Master’s in Human Factors Engineering for Autonomous Systems and ADAS
Online master's programme of 1,900 hours in Human Factors Engineering for Autonomous Systems and ADAS, with 12 modules covering automation and the human role, ADAS, situation awareness, takeover, driver monitoring, vehicle HMI, experimental methods, SOTIF and regulation, with 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
Analyse the interaction between humans and automated systems.
Evaluate ADAS and their modes from the driver's perspective.
Design safe transfer-of-control strategies.
Apply driver monitoring systems that comply with regulations.
Design human-machine interfaces for automated vehicles.
Conduct simulator experiments with methodological rigour.
Integrate human factors into SOTIF and functional safety analyses.
Who it's for
- Automotive human factors engineers looking to deepen their expertise in automation and ADAS.
- Vehicle HMI specialists.
- Researchers in automated driving.
- Functional safety and SOTIF engineers who need to account for driver behaviour.
- ADAS validation engineers.
- Designers of teleoperation workstations.
- Engineering or science graduates looking to move into the automotive sector.
What you'll work with
- SAE J3016 (levels of driving automation)
- ISO 21448 (safety of the intended functionality, SOTIF)
- ISO 26262 (functional safety of road vehicles)
- Regulation (EU) 2019/2144 (general vehicle safety)
- UN Regulation No. 157 (automated lane keeping systems)
- ISO 15007 (measurement of driver visual behaviour)
- ISO 16673 (occlusion method)
- UL 4600 (safety evaluation of autonomous products)
- SCANeR Studio
- CARLA
- Tobii Pro Lab
- MATLAB
- Python
12 modules · 1900 h
1.1Sheridan's levels of automation1.2SAE J3016 levels of driving automation1.3Bainbridge's ironies of automation1.4Adaptable and adaptive automation1.5Calibrated trust in automation1.6Complacency and automation bias1.7Operator deskilling1.8Shared human-machine responsibility1.9Lessons from aviation for the automotive sector1.10Case study: analysis of an autopilot-related accident
2.1Adaptive cruise control and lane keeping assist2.2Autonomous emergency braking2.3Blind-spot and cross-traffic detection2.4Intelligent speed assistance (ISA)2.5Sensors: camera, radar and lidar2.6Limits of the operational design domain2.7Failure modes as perceived by the driver2.8Regulation (EU) 2019/2144 and mandatory ADAS2.9Euro NCAP assistance protocols2.10Practical exercise: mode and transition matrix of an ACC
3.1Endsley's situation awareness model3.2Mode confusion and associated errors3.3Mental models of the automated system3.4Displaying the automation status3.5System capability indicators3.6Measurement with SAGAT and SART3.7Divided attention and monitoring3.8Hands-free driving and visual monitoring3.9Haptic and auditory feedback3.10Lab: SAGAT measurement in a simulator
4.1Takeover requests4.2Reaction times and time budget4.3Takeover quality4.4UN Regulation No. 157 ALKS4.5Alert escalation strategies4.6Minimal risk manoeuvres4.7Intentional and unintentional disengagement4.8Effect of secondary tasks on takeover4.9Design of multimodal alerts4.10Practical exercise: takeover experiment protocol
5.1Gaze- and head-based DMS5.2Drowsiness and distraction detection5.3Delegated Regulation (EU) 2021/1341 on DDAW5.4Delegated Regulation (EU) 2023/2590 on ADDW5.5PERCLOS and fixation metrics5.6Steering-wheel and seat sensors5.7Privacy of in-cabin biometric data5.8Validation with diverse populations5.9Integration with alert strategies5.10Lab: PERCLOS algorithm with an infrared camera
6.1In-cabin HMI architecture6.2Head-up displays and augmented reality6.3Central displays and visual load6.4NHTSA visual-manual distraction guidelines6.5Voice control and its limitations6.6System communication with pedestrians (eHMI)6.7Iconography design for assistance systems6.8Consistency across manufacturers6.9ISO 16673 occlusion testing6.10Workshop: HMI prototype for Level 3 driving
7.1Remote supervision of autonomous vehicles7.2Teleoperation and latency7.3Drones and unmanned aircraft systems7.4Mobile robots in warehouses7.5Autonomous ships and shore-based control7.6GoA 3 and GoA 4 automatic trains7.7Mixed teams of humans and autonomous agents7.8Explainability for operators7.9Ethics of automated decisions7.10Case study: teleoperation workstation for a fleet
8.1Fixed-base and motion-base driving simulators8.2Test-track and open-road studies8.3Naturalistic driving studies8.4Wizard of Oz to simulate autonomy8.5In-cabin eye tracking8.6Driver heart rate and pupillometry8.7Experimental design and statistical power8.8Ethics and participant safety8.9Driving data analysis8.10Lab: distraction study in a simulator
9.1ISO 26262 and the role of the driver9.2ISO 21448 SOTIF and foreseeable misuse9.3Controllability in HARA9.4Triggering conditions from human behaviour9.5UL 4600 and safety cases9.6Scenario-based validation9.7Scenario databases and PEGASUS9.8Driver models in simulation9.9Reasonably foreseeable misuse9.10Workshop: controllability analysis of an assistance system
10.1Technology acceptance models10.2Expectations and the marketing of autonomy10.3Driver training in ADAS10.4Manuals and learning the system10.5Behavioural adaptation and risk compensation10.6Older and novice users10.7Professional transport and fleets10.8Public opinion and communication10.9Real-world use and system deactivation10.10Case study: ADAS training programme for fleets
11.1Regulation (EU) 2022/1426 for automated systems11.2UN WP.29 regulations11.3Traffic law and automated driving11.4Euro NCAP and HMI assessment11.5Investigation of accidents involving automation11.6Liability and insurance11.7Event data recorder (EDR)11.8SAE standards on interfaces11.9International regulatory trends11.10Practical exercise: human factors dossier for type approval
12.1Selection of the automated system12.2Task analysis and operating modes12.3Hypotheses on operator behaviour12.4Design of the interface or strategy12.5Simulator experiment12.6Data analysis and results12.7Functional safety implications12.8Design recommendations12.9Master's Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
100% online learning on the SEIUM campus, with downloadable materials, recorded classes and an assigned technical tutor. No fixed timetables: you progress at your own pace within each intake, so it fits around your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is SCANeR Studio, CARLA, Tobii Pro Lab, MATLAB and Python, in free, academic or evaluation versions. Testing is studied through real procedures: takeover experiments in a simulator, distraction studies with eye tracking and controllability analyses in functional safety projects. Assessment is continuous for each module, plus the final Master's Thesis.
Standards covered: SAE J3016, ISO 21448 (SOTIF), ISO 26262, Regulation (EU) 2019/2144, UN Regulation No. 157, ISO 15007, ISO 16673, UL 4600.
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
- University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- Internet connection and a computer capable of running the programme's 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 SCANeR Studio, CARLA, Tobii Pro Lab, MATLAB and Python, 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 university degree in engineering, science or architecture (or equivalent professional experience), a computer able to run the programme's software 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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