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CourseDefense, Military Engineering & Land Systems Applications open

Course in Ethics in AI Integration in Land Vehicles

Online course of 300 h in ethics in AI integration in land vehicles. 6 modules with UL 4600 (safety of autonomous products), ISO 26262 (functional safety of vehicles) and ROS 2. Assigned tutor and open enrolment.

Duration300 h
ModeOnline
Start datesSet by the faculty
AwardSEIUM Institute certificate
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Learning outcomes

What you will be able to do

01

Describe AI architectures in unmanned land vehicles.

02

Apply functional safety standards and SOTIF to autonomous functions.

03

Analyse the interaction of the vehicle with people in its environment.

04

Determine legal responsibilities in failures of autonomous systems.

05

Identify data biases and cybersecurity threats.

06

Define scenario-based validation strategies.

07

Develop a responsible AI integration project for a UGV.

Profile

Who it's for

  • Autonomous vehicle engineer who wants to specialise in ethics in AI integration in land vehicles.
  • Functional safety engineer who wants to specialise in ethics in AI integration in land vehicles.
  • AI validation specialist who wants to specialise in ethics in AI integration in land vehicles.
  • Mobile robotics engineer who wants to specialise in ethics in AI integration in land vehicles.
  • Vehicle cybersecurity analyst who wants to specialise in ethics in AI integration in land vehicles.
  • Adviser on ethics of autonomous systems who wants to specialise in ethics in AI integration in land vehicles.
  • Graduates in engineering or science looking to enter the automotive sector.
Standards & tools

What you'll work with

  • UL 4600 (safety of autonomous products)
  • ISO 26262 (functional safety of vehicles)
  • ISO 21448 (SOTIF, safety of the intended functionality)
  • IEC 61508 (functional safety)
  • UN Regulation No. 155 (vehicle cybersecurity)
  • Additional Protocol I, Art. 36 (review of new weapons)
  • ISO/IEC 23894 (AI risk management)
Syllabus

6 modules · 300 h

  1. 1.1SAE J3016 levels of automation
  2. 1.2Unmanned ground vehicles (UGV)
  3. 1.3Perception: cameras, lidar and radar
  4. 1.4Path planning in unstructured terrain
  5. 1.5Teleoperation and supervised autonomy
  6. 1.6Conversion kits for manned vehicles
  7. 1.7Autonomous logistics and convoys
  8. 1.8Civil applications: mining and agriculture
  9. 1.9Status of European UGV programmes
  10. 1.10Workshop: functional architecture of a logistics UGV
  1. 2.1ISO 26262 applied to special vehicles
  2. 2.2ISO 21448 and the intended functionality
  3. 2.3Scenario-based validation
  4. 2.4Simulation and testing on test track
  5. 2.5Detection of pedestrians and people on the terrain
  6. 2.6Behaviour upon sensor failure
  7. 2.7Safe states and emergency stop
  8. 2.8Certification of AI components
  9. 2.9Acceptable residual risk
  10. 2.10Laboratory: catalogue of off-road test scenarios
  1. 3.1Coexistence with troops and civilians
  2. 3.2Signalling vehicle intentions
  3. 3.3Operator trust and overtrust
  4. 3.4Workload in teleoperation
  5. 3.5Human factors in autonomous convoys
  6. 3.6Accessibility and training
  7. 3.7Reaction to population in operating areas
  8. 3.8Communication in noisy environments
  9. 3.9User-centred design
  10. 3.10Practice: human factors assessment of a convoy
  1. 4.1Liability for accidents involving autonomous vehicles
  2. 4.2Liability of the manufacturer and the operator
  3. 4.3DIH and armed autonomous vehicles: debate
  4. 4.4Reviews under Article 36 of Protocol I
  5. 4.5Meaningful human control in vehicles
  6. 4.6Event data recorders
  7. 4.7Product liability directive
  8. 4.8Traffic regulations for military vehicles
  9. 4.9Use on national territory and domestic security
  10. 4.10Case study: accident involving a logistics UGV during an exercise
  1. 5.1Training data across diverse terrains
  2. 5.2Detection bias by clothing and environment
  3. 5.3Cybersecurity under ISO/SAE 21434
  4. 5.4Adversarial attacks on perception
  5. 5.5Remote software updates
  6. 5.6Model lifecycle management
  7. 5.7Privacy of data captured while driving
  8. 5.8Interoperability with allies
  9. 5.9Independent algorithm auditing
  10. 5.10Workshop: bias analysis in a person detector
  1. 6.1Definition of mission and vehicle
  2. 6.2Autonomy architecture
  3. 6.3Functional safety analysis
  4. 6.4Scenario-based validation plan
  5. 6.5Human factors assessment
  6. 6.6Legal and liability analysis
  7. 6.7Cybersecurity plan
  8. 6.8Final ethical assessment
  9. 6.9Report and presentation
  10. 6.10Final review with the tutor
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: students progress at their own pace within the intake, which makes it possible to combine it with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is ROS 2, Gazebo, CARLA, MATLAB/Simulink, in free, academic or evaluation versions. Trials are studied using real procedures for simulating autonomous driving scenarios, test tracks for unmanned vehicles and functional safety analysis. Assessment is continuous per module plus the final integrating project.

Accredited laboratories(EN ISO/IEC 17025) with rotor test rig, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-oriented final project:safety case, test plan, compliance dossier and operational limits.
Industry mentoring:lecturers with experience in training, , eVTOL/UAM and flight test.
Flexible format(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:a safety-by-design approach, ciber-OT, DIH and compliance as its pillars.
Capstone project

Build it end to end

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

Definition of mission and vehicle

Describe AI architectures in unmanned land vehicles.

Autonomy architecture

Apply functional safety standards and SOTIF to autonomous functions.

Functional safety analysis

Analyse the interaction of the vehicle with people in its environment.

Scenario-based validation plan

Determine legal responsibilities in failures of autonomous systems.

Human factors assessment

Identify data biases and cybersecurity threats.

Career opportunities

Where this takes you

Autonomous vehicle engineerFunctional safety engineerAI validation specialistMobile robotics engineerVehicle cybersecurity analystAdviser on ethics of autonomous systems
Admissions & scholarships

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.

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FAQ

Frequently asked questions

The programme is 300 hours in total, spread over 3 to 5 months. That is between 10 and 15 hours a week on average, compatible with a full-time job.

The course uses ROS 2, Gazebo, CARLA, MATLAB/Simulink. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.

An in-house SEIUM diploma upon passing the continuous assessment and the integrating 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 in the advanced programme. Check the recognition policy when enrolling.

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