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CourseCivil, Rail & Smart Cities Applications open

Autonomous and Driverless Trains Course

Online course of 300 hours in autonomous and driverless trains, structured in 6 modules covering railway automation, environment perception, localisation and control, safety and certification, and driverless operation under IEC 62290-1, IEC 62267 and UNE-EN 50126-1, with an assigned technical tutor.

Duration3 months
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute certificate
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Learning outcomes

What you will be able to do

01

Understand the grades of automation and how they apply to railways.

02

Analyse environment perception technologies for trains.

03

Describe automatic localisation and control systems.

04

Assess the safety and certification of driverless trains.

05

Plan the operation of autonomous services.

06

Identify regulatory and social barriers.

07

Produce a conceptual design of an autonomous train service.

Profile

Who it's for

  • Autonomous systems engineers.
  • Signalling engineers interested in train automation.
  • Computer vision specialists.
  • Functional safety engineers.
  • Railway researchers.
  • Innovation managers at railway operators.
  • Engineering or science graduates looking to enter urban transport.
Standards & tools

What you'll work with

  • IEC 62290-1 (urban guided transport management and command/control systems)
  • IEC 62267 (automated urban guided transport: safety requirements)
  • UNE-EN 50126-1 (railway applications: RAMS)
  • UNE-EN 50129 (safety-related electronic systems for signalling)
  • Implementing Regulation (EU) 402/2013 (common safety method)
  • Regulation (EU) 2024/1689 (Artificial Intelligence Act)
  • Regulation (EU) 2023/1695 (Control-Command and Signalling TSI)
  • ISO/PAS 8800 (road vehicles: safety and artificial intelligence)
  • ROS 2
  • MATLAB/Simulink
  • PyTorch
  • OpenCV
  • OpenTrack
Syllabus

6 modules

  1. 1.1Grades of automation GoA0 to GoA4
  2. 1.2Differences between metro and mainline railways
  3. 1.3Experience with driverless metros
  4. 1.4Autonomous freight train projects
  5. 1.5Autonomous trains in mining
  6. 1.6ATO over ETCS
  7. 1.7Drivers: capacity, cost and energy
  8. 1.8Technical and regulatory barriers
  9. 1.9The Europe's Rail programme
  10. 1.10Case study: Rio Tinto's autonomous railway in the Pilbara
  1. 2.1Sensors: cameras, LiDAR and radar
  2. 2.2Long-range obstacle detection
  3. 2.3Recognition of signals and track elements
  4. 2.4Sensor fusion
  5. 2.5Adverse conditions: fog, rain and tunnels
  6. 2.6Computer vision with deep learning
  7. 2.7Training datasets
  8. 2.8Validation of perception algorithms
  9. 2.9Physical limits of braking
  10. 2.10Lab: obstacle detection in railway video
  1. 3.1Safe train localisation
  2. 3.2Railway GNSS and augmentation
  3. 3.3Odometry and inertial units
  4. 3.4Digital track maps
  5. 3.5Running profile planning
  6. 3.6Automatic traction and brake control
  7. 3.7Precise platform stopping
  8. 3.8High-availability train-to-ground communications
  9. 3.9Remote train supervision
  10. 3.10Practical exercise: simulation of an automatic driving profile
  1. 4.1Risks of removing the driver
  2. 4.2Driver functions that must be automated
  3. 4.3Safety of artificial intelligence
  4. 4.4Safety arguments for autonomous systems
  5. 4.5Common safety method
  6. 4.6Cybersecurity of the autonomous train
  7. 4.7Human factors in remote supervision
  8. 4.8Legal liability and regulation
  9. 4.9Closed-circuit testing
  10. 4.10Case study: hazard analysis of a GoA4 train
  1. 5.1Incident management without staff on board
  2. 5.2Evacuation and passenger assistance
  3. 5.3Remote control centre
  4. 5.4Platform screen doors and station environment
  5. 5.5Sensor maintenance
  6. 5.6Effect on capacity and punctuality
  7. 5.7Energy efficiency of the service
  8. 5.8Social and workforce acceptance
  9. 5.9Business model
  10. 5.10Workshop: operating plan for an autonomous line
  1. 6.1Definition of the service and the line
  2. 6.2Target grade of automation
  3. 6.3Perception architecture
  4. 6.4Localisation and control
  5. 6.5Safety analysis
  6. 6.6Operating plan
  7. 6.7Implementation roadmap
  8. 6.8Cost-benefit estimate
  9. 6.9Report and presentation
  10. 6.10Final project: final review with the tutor
Methodology, software & labs

How you'll learn

The course is delivered 100% online 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 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 ROS 2, MATLAB/Simulink, PyTorch, OpenCV and OpenTrack, in free, academic or evaluation versions. Practical work is based on real procedures for validating railway perception systems, safety analysis of driverless trains and automatic driving simulation. Assessment is continuous by module, plus the final project.

Standards covered: IEC 62290-1, IEC 62267, UNE-EN 50126-1, UNE-EN 50129, Implementing Regulation (EU) 402/2013 (CSM), Regulation (EU) 2024/1689 (AI Act), Regulation (EU) 2023/1695 (CCS TSI), ISO/PAS 8800.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of IEC 62290-1, IEC 62267 and UNE-EN 50126-1 applied to real cases, not as a theoretical annex.
Industry software:ROS 2, MATLAB/Simulink, PyTorch, OpenCV, OpenTrack, in free, academic or evaluation versions.
Final project:the conceptual design of an autonomous train service, from target grade of automation and perception architecture to localisation, safety analysis, operating plan and cost-benefit estimate, reviewed by your tutor.
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.

Obstacle detection
Detect obstacles in railway video using computer vision.
Automatic driving simulation
Simulate an automatic driving profile with precise stopping.
GoA4 hazard analysis
Carry out the hazard analysis of a fully driverless train.
Autonomous line operating plan
Draw up the operating plan for an autonomous line.
Final project
Design an autonomous train service, reviewed by your tutor.
Career opportunities

Where this takes you

Autonomous systems engineerSignalling engineerComputer vision specialistFunctional safety engineerRailway researcherInnovation manager at a railway operator
Admissions & scholarships

Requirements

  • No prior qualification is required.
  • 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.

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FAQ

Frequently asked questions

The programme totals 300 hours over 3 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with ROS 2, MATLAB/Simulink, PyTorch, OpenCV, OpenTrack, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.

A SEIUM Institute certificate, awarded on passing the continuous assessment and the final project. 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 are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.

No prior qualification is required: you only need 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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