Course in Trust and Explainability Regulations in ADAS
Online 300 h course in trust and explainability regulations in ADAS. 6 modules covering Regulation (EU) 2019/2144 (general vehicle safety), UN Regulation No. 171 (DCAS) and Python (SHAP). Assigned tutor and open enrolment.
Course in Trust and Explainability Regulations in ADAS — studying from Australia
Regulation, safety and reliability engineering are essential across Australian industries, particularly in transport, energy, defence and mining. RAMS (reliability, availability, maintainability and safety) practices support asset integrity and regulatory compliance. Vehicle and product homologation is governed by national standards and the Infrastructure department, while work health and safety laws are harmonised across most jurisdictions. Engineers work on safety cases, certification, failure analysis and compliance documentation. Employers include regulators, certification bodies, asset owners and consultancies.
Fees for Australia: A$868 (AUD), with instalments and employer sponsorship available.
Relevant bodies in Australia
Typical roles
Questions from Australia
Does SEIUM's qualification satisfy Australian regulatory or homologation requirements?
No. SEIUM qualifications are private and are not official state degrees or accredited by national bodies. Homologation and safety regulation in Australia, such as vehicle standards administered by the Department of Infrastructure, Transport, Regional Development, Communications and the Arts, set their own requirements. Confirm with the relevant authority which competencies apply.
Which Australian employers and bodies might value this training in RAMS and regulation?
Consultancies, infrastructure and rail operators, regulators' contractors, and industrial safety teams in Australia may hire people with RAMS and compliance skills. Whether they value a private qualification depends on each employer. Demonstrated competence and project experience usually carry significant weight.
Is the course manageable alongside work, and how is payment handled?
The programmes are online, taught in English, and include an assigned technical tutor, so you can study from Australia around your job. Fees are payable in instalments, and employers may sponsor you. Confirm the programme length and the time you can realistically commit each week.
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
Explain the factors that determine driver trust in ADAS.
Apply explainability techniques to perception and decision functions.
Interpret the regulations applicable to ADAS and AI systems.
Measure trust and misuse through user studies.
Design strategies for communicating the system status.
Assess risks of overtrust or undertrust.
Develop a concept for an explainable ADAS.
Who it's for
- ADAS systems engineer who wants to specialise in Trust and Explainability Regulations in ADAS.
- Human factors specialist who wants to specialise in Trust and Explainability Regulations in ADAS.
- Explainable AI researcher who wants to specialise in Trust and Explainability Regulations in ADAS.
- User experience engineer who wants to specialise in Trust and Explainability Regulations in ADAS.
- ADAS regulatory analyst who wants to specialise in Trust and Explainability Regulations in ADAS.
- Validation engineer who wants to specialise in Trust and Explainability Regulations in ADAS.
- Engineering or science graduates looking to enter the automotive industry.
What you'll work with
- Regulation (EU) 2019/2144 (general vehicle safety)
- UN Regulation No. 171 (DCAS)
- UN Regulation No. 157 (ALKS)
- SAE J3016 (levels of automation)
- Regulation (EU) 2024/1689 (AI Act)
- ISO 21448 (SOTIF)
6 modules · 300 h
1.1Calibrated trust, overtrust and undertrust1.2Trust models in automation1.3Overconfidence and misuse of ADAS1.4Commercial names and expectations1.5NHTSA and NTSB investigations1.6Driver situational awareness1.7Human factors in Level 2 and 3 systems1.8Measuring user trust1.9Manufacturer communication1.10Case study: analysis of a Level 2 accident
2.1What explaining means in an ADAS2.2Explainability of perception networks2.3Interpretability of decision modules2.4Post hoc methods and their limits2.5Uncertainty and model confidence2.6Explanations in the driver HMI2.7DSSAD records and reconstruction2.8ISO/PAS 8800 and AI in automotive2.9Technical documentation for type approval2.10Laboratory: visualising uncertainty in perception
3.1UNECE R79 and steering functions3.2UNECE R171 DCAS Regulation3.3UNECE R157 ALKS Regulation3.4Driver monitoring requirements3.5Regulation (EU) 2024/1689 on AI3.6Product liability for defective products Directive3.7Advertising and communication requirements3.8Euro NCAP Assisted Driving3.9ISO 21448 and foreseeable misuse3.10Practice: regulatory matrix for a DCAS system
4.1Driving simulator studies4.2On-road trials with users4.3Trust and acceptance scales4.4Takeover time metrics4.5Gaze and distraction analysis4.6Assessment of reported failure modes4.7Designing tests with novice users4.8Ethics of human trials4.9Statistical analysis of results4.10Workshop: designing a simulator study
5.1System status indicators5.2Graduated warnings and escalation5.3User training and manuals5.4In-vehicle onboarding5.5Transparency of ODD limitations5.6Communicating updates5.7Managing expectations in marketing5.8Fleet feedback and continuous improvement5.9Shared driver-system responsibility5.10Case study: redesigning Level 2 warnings
6.1Selecting the ADAS system6.2Regulatory requirements analysis6.3Identifying misuse risks6.4Proposing explanations6.5HMI design6.6User evaluation plan6.7Documentation plan6.8Final recommendations6.9Report and presentation6.10Final review with the tutor
How you'll learn
100 % online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetable: students progress at their own pace within the intake, which makes it possible to combine with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Python (SHAP), CARLA, MATLAB, Tobii Pro Lab, in free, academic or evaluation versions. Assignments are based on real procedures for driving simulator studies, user trust surveys and assessment of explanations in the interface. Assessment is continuous by module, plus the final integrative project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Explain the factors that determine driver trust in ADAS.
Apply explainability techniques to perception and decision functions.
Interpret the regulations applicable to ADAS and AI systems.
Measure trust and misuse through user studies.
Design strategies for communicating the system status.
Where this takes you
Requirements
- No prior degree is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient Spanish to follow technical regulatory texts.
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 300 hours spread over 3 to 5 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.
The work uses Python (SHAP), CARLA, MATLAB and Tobii Pro Lab. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
A SEIUM own diploma upon passing the continuous assessment and the integrative project. It is in-house training, not an official Ministry qualification.
Yes. Modules passed in a Course or Postgraduate Diploma in the same area are recognised towards the higher programme. Check the recognition policy when you enrol.
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