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Master'sOff-Road, Special Vehicles & Machinery Applications open

Master’s in Autonomous Systems for Off-Highway Engineering

Online master's programme of 1,900 hours in autonomous systems engineering for off-highway machinery, with 12 modules covering systems engineering and SysML, autonomous vehicle architecture, autonomy in mining, agriculture and construction, fleet management, functional safety (ISO 17757, ISO 18497, IEC 61508), cybersecurity, validation and business cases, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Apply systems engineering to autonomous machines.

02

Define the operational design domain and its requirements.

03

Design redundant autonomous vehicle architectures.

04

Analyse applications in mining, agriculture and construction.

05

Develop functional safety and cybersecurity cases.

06

Plan validation and certification.

07

Prepare business cases for deployment.

Profile

Who it's for

  • Autonomous systems engineers working on off-highway machines.
  • Systems architects defining functional and physical architectures with MBSE.
  • Functional safety engineers building safety cases for autonomy.
  • Industrial cybersecurity engineers protecting connected machinery.
  • Autonomous fleet managers in mining, quarrying or agriculture.
  • Autonomy validation engineers planning simulation and field campaigns.
  • Engineering or science graduates looking to enter the mining sector.
Standards & tools

What you'll work with

  • ISO 17757 (safety of autonomous machines in mining)
  • ISO 18497 (safety of autonomous agricultural machines)
  • IEC 61508 (functional safety)
  • UNE-EN ISO 13849-1 (safety of control systems)
  • ISO 21448 (safety of the intended functionality)
  • IEC 62443 (industrial cybersecurity)
  • Regulation (EU) 2024/2847 (Cyber Resilience Act)
  • UNECE Regulation No. 155 (cybersecurity)
  • Cameo Systems Modeler
  • ROS 2
  • MATLAB/Simulink
  • AnyLogic
Syllabus

12 modules · 1900 h

  1. 1.1Systems engineering applied to autonomy
  2. 1.2Operational design domain
  3. 1.3Use cases and scenarios
  4. 1.4Functional architecture of the system
  5. 1.5Physical architecture of the system
  6. 1.6Interface definition
  7. 1.7Requirements traceability
  8. 1.8Model-based systems engineering
  9. 1.9Modelling with SysML
  10. 1.10Case study: operational domain of an autonomous dump truck
  1. 2.1Drive-by-wire systems
  2. 2.2Redundant steering and braking actuators
  3. 2.3Safety controllers
  4. 2.4Autonomy computing unit
  5. 2.5Redundant electrical power supply
  6. 2.6On-board communications network
  7. 2.7Retrofitting existing machines
  8. 2.8Interfaces with the manufacturer
  9. 2.9Architecture design
  10. 2.10Lab: drive-by-wire interface
  1. 3.1Autonomous open-pit haulage
  2. 3.2Autonomous blast-hole drilling
  3. 3.3Automated loading and unloading
  4. 3.4Mining fleet management systems
  5. 3.5Mine maps and models
  6. 3.6Coexistence with manned vehicles
  7. 3.7Commercial autonomous haulage systems
  8. 3.8Productivity and availability
  9. 3.9Safety in mining operations
  10. 3.10Case study: autonomous haulage cycle
  1. 4.1Precision automatic guidance
  2. 4.2Cabless autonomous tractors
  3. 4.3Lightweight agricultural robots
  4. 4.4Robot swarms
  5. 4.5Integration with ISOBUS
  6. 4.6Autonomous seeding and spraying
  7. 4.7Obstacle detection in the field
  8. 4.8ISO 18497 requirements
  9. 4.9Commercial cases in agriculture
  10. 4.10Case study: weeding robot
  1. 5.1Autonomous compaction of pavements
  2. 5.2Automated trench excavation
  3. 5.3Model-guided earth-moving
  4. 5.4Integration with BIM models
  5. 5.5GNSS machine control
  6. 5.6Drone surveying
  7. 5.7Coordination of equipment on site
  8. 5.8Application cases
  9. 5.9Challenges in changing environments
  10. 5.10Practical: automated excavation from BIM
  1. 6.1Machine dispatching
  2. 6.2Task allocation
  3. 6.3Internal traffic management
  4. 6.4Queueing theory in cycles
  5. 6.5Fleet optimisation
  6. 6.6Management software
  7. 6.7Fleet indicators
  8. 6.8Integration with plant systems
  9. 6.9Fleet simulation
  10. 6.10Lab: dispatch optimisation
  1. 7.1Safety to ISO 13849
  2. 7.2Safety to ISO 25119
  3. 7.3IEC 61508 general framework
  4. 7.4ISO 17757 requirements
  5. 7.5Safety of the intended functionality
  6. 7.6Hazard analysis and risk assessment
  7. 7.7Building the safety case
  8. 7.8Real-time safety monitoring
  9. 7.9Safe stop strategies
  10. 7.10Case study: simplified safety case
  1. 8.1Threats to autonomous machines
  2. 8.2Industrial cybersecurity IEC 62443
  3. 8.3UNECE Regulation No. 155
  4. 8.4European Cyber Resilience Act
  5. 8.5Network segmentation
  6. 8.6Authentication and access control
  7. 8.7Secure software updates
  8. 8.8Security monitoring
  9. 8.9Incident response
  10. 8.10Practical: TARA analysis of a machine
  1. 9.1Validation strategy
  2. 9.2Validation in simulation
  3. 9.3Closed-track testing
  4. 9.4Testing in real operation
  5. 9.5Performance and safety metrics
  6. 9.6Operational domain coverage
  7. 9.7Validation data management
  8. 9.8Third-party certification
  9. 9.9Validation reports
  10. 9.10Lab: validation campaign in a simulator
  1. 10.1Remote fleet supervision
  2. 10.2Supervisor workload
  3. 10.3Interaction with field personnel
  4. 10.4Training for new roles
  5. 10.5Change management
  6. 10.6Labour aspects of automation
  7. 10.7Acceptance by workers
  8. 10.8Ethical considerations of autonomy
  9. 10.9Communication with the community
  10. 10.10Case study: change management plan
  1. 11.1Business case for autonomy
  2. 11.2Total cost of ownership
  3. 11.3Productivity gains
  4. 11.4Investment and financing
  5. 11.5Project risks
  6. 11.6Scaling from pilots to operation
  7. 11.7Contract models
  8. 11.8Supplier selection
  9. 11.9Deployment experiences
  10. 11.10Case study: business case for a quarry
  1. 12.1Definition of the operational domain
  2. 12.2System requirements
  3. 12.3Functional and physical architecture
  4. 12.4Fleet management
  5. 12.5Functional safety analysis
  6. 12.6Cybersecurity analysis
  7. 12.7Validation plan
  8. 12.8Business case
  9. 12.9Thesis report
  10. 12.10Master's Thesis: defence before a panel
Methodology, software & labs

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 you can combine it with your job.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is Cameo Systems Modeler, ROS 2, MATLAB/Simulink and AnyLogic, in free, academic or evaluation versions. Testing is studied through real procedures for validating autonomous systems in a simulator, functional safety analysis and autonomous fleet optimisation. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: ISO 17757, ISO 18497, IEC 61508, UNE-EN ISO 13849-1, ISO 21448, IEC 62443, Regulation (EU) 2024/2847, UNECE Regulation No. 155.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of ISO 17757, ISO 18497 and IEC 61508 applied to real cases, not as a theoretical annex.
Industry software:Cameo Systems Modeler, ROS 2, MATLAB/Simulink and AnyLogic, in free, academic or evaluation versions.
Master's Thesis with defence:A complete autonomous system design, from operational domain and architecture to safety, cybersecurity, validation and business case, defended before a panel.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Operational domain definition
Define the operational design domain of an autonomous dump truck with SysML.
Drive-by-wire architecture
Design a redundant vehicle architecture and its drive-by-wire interface.
Fleet optimisation
Simulate and optimise dispatching for an autonomous fleet.
Safety and cybersecurity cases
Build a simplified safety case and carry out a TARA analysis of a machine.
Master's Thesis
A full autonomous system proposal with validation plan and business case, defended before a panel.
Career opportunities

Where this takes you

Autonomous systems engineerSystems architectFunctional safety engineerIndustrial cybersecurity engineerAutonomous fleet managerAutonomy validation engineer
Admissions & scholarships

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.

Apply now Scholarships
FAQ

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 Cameo Systems Modeler, ROS 2, MATLAB/Simulink and AnyLogic, 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), a computer able to run the programme 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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