Apply now
Master'sInsurance, Risk & Actuarial Data Applications open

Master’s in Autonomy Risk and Third-Party Liability of Autonomous Vehicles Engineering

Online master's programme of 1,900 hours in Autonomy Risk and Civil Liability Engineering for Autonomous Vehicles, structured in 12 modules covering autonomous vehicle risk, the legal framework of liability, type approval and validation, functional safety and SOTIF, data and attribution, actuarial modelling, insurance products, cybersecurity, claims management, ethics and future regulation, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
Enrol now View syllabus Ask an advisor
Virtual lab · try it before you enrol

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.

SIM · LIVE ●
Learning outcomes

What you will be able to do

01

Analyse the technical risks of automated driving systems.

02

Interpret the legal framework of civil and product liability.

03

Evaluate the type approval and validation of autonomous vehicles.

04

Use vehicle data to attribute liability.

05

Build actuarial models for risks with scarce data.

06

Design insurance products for operators and manufacturers.

07

Assess the ethical and social implications of autonomous driving.

Profile

Who it's for

  • Autonomous vehicle risk analysts in insurers and mobility operators.
  • Product liability underwriters covering manufacturers and technology suppliers.
  • Loss adjusters and expert witnesses working with automated vehicles.
  • Mobility legal advisers dealing with liability in automated driving.
  • Actuaries focused on emerging risks.
  • Autonomous fleet safety managers.
  • Engineering or science graduates aiming to enter motor insurance.
Standards & tools

What you'll work with

  • Directive (EU) 2024/2853 (liability for damage caused by defective products)
  • Implementing Regulation (EU) 2022/1426 (automated driving systems)
  • Directive 2009/103/EC (motor vehicle civil liability insurance)
  • Royal Legislative Decree 8/2004 (Spanish Law on civil liability and insurance for motor vehicles)
  • UN Regulation No. 157 (ALKS)
  • ISO 21448 (safety of the intended functionality, SOTIF)
  • ISO 26262 (functional safety of road vehicles)
  • UN Regulation No. 155 (cybersecurity)
  • CARLA
  • esmini (OpenSCENARIO)
  • PC-Crash
  • Python
  • MATLAB/Simulink
Syllabus

12 modules · 1900 h

  1. 1.1SAE J3016 levels of automation
  2. 1.2Architecture of the automated driving system
  3. 1.3Operational design domain
  4. 1.4Perception failure modes
  5. 1.5Planning and prediction errors
  6. 1.6Interaction with other road users
  7. 1.7Robotaxi fleet operation
  8. 1.8Shuttles and autonomous public transport
  9. 1.9Autonomous trucks and logistics
  10. 1.10Case study: risk profile of an autonomous shuttle service
  1. 2.1Fault-based and strict liability
  2. 2.2Spanish Law on civil liability and insurance for motor vehicles
  3. 2.3Directive 2009/103/EC on motor insurance
  4. 2.4Directive (EU) 2024/2853 on defective products
  5. 2.5Liability of the system manufacturer
  6. 2.6Liability of the fleet operator
  7. 2.7Liability of the software provider
  8. 2.8The concept of driver in automated systems
  9. 2.9Comparative law: United Kingdom, Germany and the USA
  10. 2.10Workshop: analysis of the UK Automated Vehicles Act
  1. 3.1Regulation (EU) 2022/1426 on automated systems
  2. 3.2UN Regulation 157
  3. 3.3Scenario-based validation
  4. 3.4Scenario databases and OpenSCENARIO
  5. 3.5Simulation, track and open roads
  6. 3.6System safety metrics
  7. 3.7Safety cases and UL 4600
  8. 3.8In-service monitoring
  9. 3.9Incident reporting
  10. 3.10Practical exercise: scenario-based validation plan
  1. 4.1ISO 26262 applied to automated driving
  2. 4.2Hazard and risk analysis
  3. 4.3ISO 21448 and performance limitations
  4. 4.4Artificial intelligence in safety functions
  5. 4.5ISO/PAS 8800 on AI in vehicles
  6. 4.6Redundancy and safe degradation
  7. 4.7Minimal risk manoeuvre
  8. 4.8Evidence for the safety case
  9. 4.9Liability arising from design defects
  10. 4.10Case study: SOTIF analysis of a perception system
  1. 5.1Data storage system for automated driving (DSSAD)
  2. 5.2EDR recorders
  3. 5.3Data chain of custody
  4. 5.4Insurer access to data
  5. 5.5Reconstruction of automated-vehicle accidents
  6. 5.6Causal attribution between human and system
  7. 5.7Forensic log analysis
  8. 5.8Expert witness work on autonomous vehicles
  9. 5.9The Data Act and vehicle data
  10. 5.10Lab: analysis of a DSSAD record
  1. 6.1Scarcity of claims data
  2. 6.2Use of disengagement-free kilometre data
  3. 6.3Comparison with human drivers
  4. 6.4Frequency models by ODD
  5. 6.5Severity and new damage patterns
  6. 6.6Systemic risk from common-mode failure
  7. 6.7Accumulation from software updates
  8. 6.8Technology penetration scenarios
  9. 6.9Uncertainty and expert judgement
  10. 6.10Practical exercise: frequency model for an autonomous fleet
  1. 7.1Liability insurance for operators
  2. 7.2Manufacturers' product liability insurance
  3. 7.3Hybrid human-system policies
  4. 7.4Cyber risk covers
  5. 7.5Autonomous fleet insurance
  6. 7.6Insurance for testing on public roads
  7. 7.7Manufacturer warranties and extensions
  8. 7.8Insurance embedded in the vehicle
  9. 7.9Recovery mechanisms
  10. 7.10Case study: designing a policy for robotaxis
  1. 8.1UN Regulation 155 and the management system
  2. 8.2UN Regulation 156 on updates
  3. 8.3ISO/SAE 21434
  4. 8.4Attacks on sensors and communications
  5. 8.5Liability after a cyberattack
  6. 8.6Over-the-air updates and new risks
  7. 8.7Vulnerability management across the fleet
  8. 8.8Cyber risk accumulation
  9. 8.9Cyber exclusions and covers
  10. 8.10Workshop: scenario of a mass attack on a fleet
  1. 9.1Notification and first response
  2. 9.2Technical accident investigation
  3. 9.3Coordination with manufacturer and operator
  4. 9.4Loss adjustment of sensor damage
  5. 9.5ADAS repair and recalibration
  6. 9.6Repair costs of new technologies
  7. 9.7Recoveries and litigation
  8. 9.8Injury claims
  9. 9.9Communication and reputation
  10. 9.10Practical exercise: handling an automated-vehicle claim
  1. 10.1Ethical dilemmas in algorithmic decision-making
  2. 10.2Ethics recommendations of the European Commission
  3. 10.3Transparency and explainability
  4. 10.4Fairness in detecting vulnerable road users
  5. 10.5Public trust
  6. 10.6Incident communication
  7. 10.7Impact on employment
  8. 10.8Accessibility and inclusive mobility
  9. 10.9AI governance
  10. 10.10Case study: ethical analysis of a high-profile incident
  1. 11.1EU automation roadmap
  2. 11.2International commercial deployments
  3. 11.3Autonomous mobility business models
  4. 11.4Evolution of motor insurance
  5. 11.5Role of the Consorcio de Compensación de Seguros and guarantee funds
  6. 11.6Cooperation between industry and insurers
  7. 11.7The AI Act and vehicles
  8. 11.8Long-term scenarios
  9. 11.9Regulatory recommendations
  10. 11.10Workshop: insurance market scenarios to 2035
  1. 12.1Framing the liability problem
  2. 12.2Technical analysis of the system
  3. 12.3Applicable legal framework
  4. 12.4Risk modelling
  5. 12.5Product or regulatory proposal
  6. 12.6Scenario analysis
  7. 12.7Ethical implications
  8. 12.8Conclusions
  9. 12.9Master's Thesis 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. 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 CARLA, esmini (OpenSCENARIO), PC-Crash, Python and MATLAB/Simulink, in free, academic or evaluation versions. Testing is studied through real procedures: attribution of liability in accidents using DSSAD data, actuarial modelling of autonomous fleets and scenario-based validation of automated systems. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: Directive (EU) 2024/2853, Implementing Regulation (EU) 2022/1426, Directive 2009/103/EC, Royal Legislative Decree 8/2004, UN Regulation No. 157 (ALKS), ISO 21448 (SOTIF), ISO 26262 and UN Regulation No. 155.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of Directive (EU) 2024/2853, Implementing Regulation (EU) 2022/1426 and Directive 2009/103/EC applied to real cases, not as a theoretical annex.
Industry software:CARLA, esmini (OpenSCENARIO), PC-Crash, Python and MATLAB/Simulink, in free, academic or evaluation versions.
Master's Thesis with defence:A liability project combining technical system analysis, legal framework, risk modelling and a product or regulatory proposal, 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.

Autonomous risk profile
Build the risk profile of an autonomous shuttle service and its validation plan.
Data-based attribution
Analyse a DSSAD record to attribute causes between human and system.
Actuarial fleet model
Develop a frequency model for an autonomous fleet with scarce claims data.
Robotaxi policy design
Design an insurance policy for robotaxis, including cyber covers and recovery mechanisms.
Master's Thesis
Liability project with risk modelling and a product or regulatory proposal, defended before a panel.
Career opportunities

Where this takes you

Autonomous vehicle risk analystProduct liability underwriterAutomated vehicle loss adjusterMobility legal adviserEmerging risks actuaryAutonomous fleet safety manager
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'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.

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 CARLA, esmini (OpenSCENARIO), PC-Crash, Python and MATLAB/Simulink, 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.

Keep exploring

Related programmes

See all in Insurance, Risk & Actuarial Data
Master's8,850 $

Master’s in Compliance and Technical Auditing Engineering

Online master's programme of 1,900 hours in Compliance and Technical Audit Engineering, structured in 12 modules covering technical audit fundamentals, compliance in insurers, underwriting, claims and…

1900 hOnlineInsurance, Risk & Actuarial Data
Master's8,850 $

Master’s in Geospatial Analytics and Remote Sensing for Risk and Claims Engineering

Online master's programme of 1,900 hours in Geospatial Analytics and Remote Sensing Engineering for Risk and Claims. 12 modules covering geographic information for insurance, remote sensing,…

1900 hOnlineInsurance, Risk & Actuarial Data
Master's8,850 $

Master’s in Credit, Leasing and Residual Value in Mobility Engineering

Online master's programme of 1,900 hours in credit, leasing and residual value engineering in mobility, structured in 12 modules covering mobility finance, regulation and accounting, credit…

1900 hOnlineInsurance, Risk & Actuarial Data
Master’s in Autonomy Risk and Third-Party Liability of Autonomous Vehicles EngineeringEnrol
Related programmes

More in Insurance, Risk & Actuarial Data

Master’s in Data Governance and MLOps for Actuaries EngineeringView programme →Master’s in Compliance, Solvency & International Regulation EngineeringView programme →Master’s in Technology, Autonomy & Road Safety EngineeringView programme →Master’s in Technical Risk and Insurance in Transport EngineeringView programme →Master’s in Telematics and Actuarial Pricing of Connected Mobility EngineeringView programme →Master’s in Multimodal Transport Underwriting EngineeringView programme →

All Insurance, Risk & Actuarial Data programmes → · How to apply · Fees & financing · Scholarships

Scroll to Top
SEIUM – Institute of Advanced Engineering
Powered by  GDPR Cookie Compliance
Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.