Postgraduate Diploma in Simulator Testing and ODD Methodologies
Online 800-hour Postgraduate Diploma in Simulator Testing and ODD Methodologies. 8 modules covering ISO 34503 (operational design domain taxonomy), ISO 21448 (SOTIF) and CARLA. Dedicated tutor and enrolment open.
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
Define the operational design domain of an automated system.
Build test scenarios using OpenSCENARIO and OpenDRIVE formats.
Configure driving simulators for studies with users.
Integrate MIL, SIL, HIL and VIL tests into a validation chain.
Design experiments with statistical rigour and variable control.
Apply scenario-based validation in accordance with SOTIF.
Execute and document a complete simulator test.
Who it's for
- Automated driving validation engineer looking to specialise in Simulator Testing and ODD Methodologies.
- Scenario simulation engineer looking to specialise in Simulator Testing and ODD Methodologies.
- SOTIF safety engineer looking to specialise in Simulator Testing and ODD Methodologies.
- X-in-the-loop test engineer looking to specialise in Simulator Testing and ODD Methodologies.
- Driving data analyst looking to specialise in Simulator Testing and ODD Methodologies.
- ADAS systems engineer looking to specialise in Simulator Testing and ODD Methodologies.
- Engineering or science graduates looking to enter the automotive sector.
What you'll work with
- ISO 34503 (operational design domain taxonomy)
- ISO 21448 (SOTIF)
- ISO 26262 (functional safety in vehicles)
- ASAM OpenSCENARIO
- ASAM OpenDRIVE
- UN Regulation No. 157 (ALKS)
- Implementing Regulation (EU) 2022/1426 (automated driving systems)
- BSI PAS 1883 (ODD specification)
8 modules · 800 h
1.1ODD concept in SAE J30161.2ODD taxonomy according to BSI PAS 18831.3ISO 34503 ODD definition1.4Attributes: scenario, environment and dynamics1.5ODD entry and exit conditions1.6Real-time ODD monitoring1.7ODD and minimum risk manoeuvre1.8Relationship between ODD and use cases1.9ODD specification languages1.10Case study: ODD of an urban robotaxi
2.1Functional, logical and concrete scenarios2.2ISO 34501 and 34502 standards2.3Scenario databases2.4ASAM OpenSCENARIO and OpenDRIVE2.5Generation of critical scenarios2.6Scenarios based on accident data2.7ODD coverage2.8Parameterisation and variable distribution2.9Criticality metrics: TTC and PET2.10Lab: defining a scenario in OpenSCENARIO
3.1Types of simulators: fixed-base and dynamic3.2Motion platforms and washout algorithms3.3Visual systems and latency3.4Software: CARLA, IPG CarMaker and VTD3.5Vehicle and sensor models3.6Traffic simulation with SUMO3.7Simulator sickness3.8Physical and psychological fidelity3.9Simulator validation3.10Practice: configuring a scenario in CARLA
4.1Model-in-the-loop and software-in-the-loop4.2Hardware-in-the-loop4.3Vehicle-in-the-loop4.4Driver-in-the-loop4.5Co-simulation and FMI4.6Synchronisation and real time4.7Sensor simulation: camera, radar and lidar4.8The simulation-to-reality gap4.9Simulation credibility4.10Lab: HIL test of an ADAS function
5.1Research questions and hypotheses5.2Within- and between-subjects design5.3Sample selection and size5.4Driver and vehicle dependent variables5.5Protocols and consent5.6Training and familiarisation5.7Control of confounding variables5.8Mixed-effects model analysis5.9Reporting and reproducibility5.10Practice: protocol for a simulator study
6.1UNECE NATM approach6.2Pillars: simulation, track and road6.3Track testing: Euro NCAP AEB and LSS6.4Open-road testing6.5Acceptance criteria and residual risk6.6Safety arguments with scenarios6.7ISO 21448 and unknown scenarios6.8Test data management6.9Traceability between requirements and tests6.10Case study: validation plan for an ALKS
7.1Naturalistic data: highD and nuScenes7.2Scenario extraction from real data7.3Statistical coverage analysis7.4Optimisation and search for corner cases7.5Large-scale cloud testing7.6Results management and dashboards7.7Continuous integration of tests7.8ASAM OSI tools7.9Sensor data quality7.10Workshop: extracting lane-change scenarios from highD
8.1Definition of the function and its ODD8.2Scenario catalogue8.3Simulator configuration8.4Experimental design8.5Test execution8.6Results analysis8.7ODD coverage assessment8.8Safety conclusions8.9Report and presentation8.10Final review with the tutor
How you'll learn
Training 100% online on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: students progress at their own pace within the intake, which makes it compatible with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is CARLA, IPG CarMaker, dSPACE (SCALEXIO/ModelDesk), MATLAB/Simulink (Automated Driving Toolbox), esmini, in free, academic or evaluation versions. Tests are studied using real driving simulator procedures with the driver in the loop, hardware-in-the-loop and software-in-the-loop tests, and scenario-based validation on track. Assessment is continuous per module plus the final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Define the operational design domain of an automated system.
Build test scenarios using OpenSCENARIO and OpenDRIVE formats.
Configure driving simulators for studies with users.
Integrate MIL, SIL, HIL and VIL tests into a validation chain.
Design experiments with statistical rigour and variable control.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. A university degree is not required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient Spanish to follow the reading of 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 consists of 800 hours in total, spread over 6 to 8 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.
The work uses CARLA, IPG CarMaker, dSPACE (SCALEXIO/ModelDesk), MATLAB/Simulink (Automated Driving Toolbox) and esmini. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
A SEIUM Institute diploma upon passing continuous assessment and the integrating project. It is in-house training, not an official qualification from the Ministry.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised towards the higher programme. Check the recognition policy when enrolling.
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