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Master'sAutonomous, ADAS & Software-Defined Vehicle Applications open

Master’s in AUTOSAR Adaptive, ROS 2 and DDS

Online master's programme of 1,900 hours in AUTOSAR Adaptive, ROS 2 and DDS. 12 modules covering software-defined vehicle architectures, service-oriented middleware, in-vehicle Ethernet and TSN, real-time performance, perception integration, cybersecurity and software validation, with an assigned technical tutor.

Duration12–14 months
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Describe the software architectures of the software-defined vehicle.

02

Develop applications on AUTOSAR Adaptive.

03

Use ROS 2 in automotive environments.

04

Configure DDS and its quality of service.

05

Analyse the performance and real-time behaviour of the middleware.

06

Integrate perception and control modules on the platform.

07

Apply cybersecurity and update requirements to the software.

Profile

Who it's for

  • SDV software architects.
  • AUTOSAR Adaptive engineers.
  • ROS 2 engineers.
  • Middleware engineers.
  • Software integration engineers.
  • Software validation engineers.
  • Engineering or science graduates seeking to enter vehicle manufacturers.
Standards & tools

What you'll work with

  • AUTOSAR Adaptive Platform (service-oriented architecture for high-performance computers)
  • OMG DDS (Data Distribution Service)
  • OMG DDSI-RTPS (DDS interoperability wire protocol)
  • ISO 26262 (functional safety)
  • ISO 21448 (SOTIF)
  • ISO/SAE 21434 (road vehicle cybersecurity)
  • UN Regulation No. 156 (software updates)
  • ROS 2
  • Eclipse Cyclone DDS
  • Vector DaVinci Developer Adaptive
  • Docker
  • Wireshark
Syllabus

12 modules

  1. 1.1From the isolated ECU to the domain computer
  2. 1.2Separation of application, platform and hardware
  3. 1.3Service-oriented versus signal-based model
  4. 1.4Development cycles and continuous deployment
  5. 1.5Real-time and safety requirements
  6. 1.6Coexistence of Classic and Adaptive
  7. 1.7The role of ROS 2 in prototyping and production
  8. 1.8Criteria for choosing each stack
  9. 1.9Migration from legacy architectures
  10. 1.10Workshop: designing a domain architecture
  1. 2.1Manifests and the deployment model
  2. 2.2Execution management and states
  3. 2.3ara::com, proxies and skeletons
  4. 2.4Service discovery and SOME/IP
  5. 2.5Configuration management and persistency
  6. 2.6Adaptive diagnostics and UDS over IP
  7. 2.7Time management and synchronisation
  8. 2.8Functional safety in Adaptive
  9. 2.9Application updates
  10. 2.10Lab: minimal adaptive application
  1. 3.1Nodes, topics, services and actions
  2. 3.2Executors, callbacks and scheduling
  3. 3.3Lifecycle of managed nodes
  4. 3.4In-process composition and zero copy
  5. 3.5Parameters and dynamic reconfiguration
  6. 3.6Introspection and recording tools
  7. 3.7Good practice for embedded systems
  8. 3.8Limitations against production requirements
  9. 3.9Bridges to AUTOSAR and CAN
  10. 3.10Lab: ROS 2 graph for perception
  1. 4.1Data-centric publish-subscribe model
  2. 4.2Domains, partitions and discovery
  3. 4.3Quality of service profiles
  4. 4.4Reliability, durability and deadlines
  5. 4.5History, depth and flow control
  6. 4.6Transports and network configuration
  7. 4.7DDS Security: authentication and encryption
  8. 4.8Performance and resource consumption
  9. 4.9Diagnosing discovery problems
  10. 4.10Lab: QoS tuning for low latency
  1. 5.1Automotive Ethernet and switching
  2. 5.2TSN: synchronisation, shaping and reservations
  3. 5.3SOME/IP: serialisation and signalling
  4. 5.4Coexistence with CAN, CAN FD and LIN
  5. 5.5Gateways and protocol translation
  6. 5.6Bandwidth and traffic scheduling
  7. 5.7End-to-end latency and jitter
  8. 5.8On-board network monitoring
  9. 5.9Load and stress testing
  10. 5.10Lab: latency measurement over TSN
  1. 6.1Timing requirements by function
  2. 6.2Scheduling in Linux and in an RTOS
  3. 6.3CPU isolation and affinity
  4. 6.4Memory management and avoiding page faults
  5. 6.5Measuring latencies and queues
  6. 6.6Application profiling
  7. 6.7Trade-offs between throughput and latency
  8. 6.8Degradation under load
  9. 6.9Timing acceptance criteria
  10. 6.10Lab: characterisation of a data chain
  1. 7.1Data flow from sensors to actuation
  2. 7.2Time synchronisation and timestamps
  3. 7.3Sensor fusion and its deadlines
  4. 7.4Interfaces with planning and control
  5. 7.5Handling sensor failures
  6. 7.6Degraded modes and safety
  7. 7.7Scenario reproducibility
  8. 7.8Simulation in the loop and node substitution
  9. 7.9Validation of the complete chain
  10. 7.10Lab: perception-control integration
  1. 8.1Dependency management and build
  2. 8.2Containers for development and testing
  3. 8.3Continuous integration with hardware in the loop
  4. 8.4Version and branch management
  5. 8.5Code review and standards
  6. 8.6Static analysis and MISRA and AUTOSAR C++ rules
  7. 8.7Generated documentation
  8. 8.8Traceability from requirements to tests
  9. 8.9Quality metrics
  10. 8.10Lab: continuous integration pipeline
  1. 9.1In-vehicle scenario recording
  2. 9.2Logging formats and data volume
  3. 9.3Event extraction and labelling
  4. 9.4Deterministic replay
  5. 9.5Storage infrastructure
  6. 9.6Anonymisation and data protection
  7. 9.7Exploitation of fleet data
  8. 9.8Selecting cases for testing
  9. 9.9Costs of the data chain
  10. 9.10Lab: replaying a journey
  1. 10.1Middleware attack surface
  2. 10.2Authentication between services
  3. 10.3Key management in the vehicle
  4. 10.4Updating applications and the platform
  5. 10.5Rollback and recovery
  6. 10.6Security event logging
  7. 10.7Applicable R155 requirements
  8. 10.8Middleware security testing
  9. 10.9Vulnerability response
  10. 10.10Workshop: hardening a deployment
  1. 11.1Level-based test strategy
  2. 11.2Service integration testing
  3. 11.3Simulation, HIL and vehicle
  4. 11.4Coverage and exit criteria
  5. 11.5Defect management
  6. 11.6Evidence for functional safety
  7. 11.7Traceability for audit
  8. 11.8Release preparation
  9. 11.9Maintenance in the field
  10. 11.10Case study: validation plan
  1. 12.1Definition of the use case and requirements
  2. 12.2Design of the service architecture
  3. 12.3Implementation with Adaptive, ROS 2 and DDS
  4. 12.4Network and QoS configuration
  5. 12.5Latency measurement and tuning
  6. 12.6Security and update plan
  7. 12.7HIL testing and results
  8. 12.8Risk analysis and limitations
  9. 12.9Technical report and defence
  10. 12.10Master's Thesis: final review with the tutor
Methodology, software & labs

How you'll learn

A 100% online programme on the SEIUM campus, with downloadable materials, 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, Eclipse Cyclone DDS, Vector DaVinci Developer Adaptive, Docker and Wireshark, in free, academic or evaluation versions. Testing is studied through real procedures for integration on a software-defined vehicle platform, middleware latency measurements and replay of recorded data (rosbag). Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: AUTOSAR Adaptive Platform, OMG DDS, OMG DDSI-RTPS, ISO 26262, ISO 21448 (SOTIF), ISO/SAE 21434 and UN Regulation No. 156.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of AUTOSAR Adaptive Platform, OMG DDS and OMG DDSI-RTPS applied to real cases, not as a theoretical annex.
Industry software:ROS 2, Eclipse Cyclone DDS, Vector DaVinci Developer Adaptive, Docker and Wireshark, in free, academic or evaluation versions.
Master's Thesis with defence:a software-defined vehicle platform for a real use case, implemented with Adaptive, ROS 2 and DDS and validated in HIL, 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.

Domain architecture design
Design a domain computer software architecture for a software-defined vehicle.
ROS 2 perception graph
Build a ROS 2 graph for perception and tune DDS QoS for low latency.
TSN latency measurement
Measure end-to-end latency and jitter of a data chain over TSN Ethernet.
Continuous integration pipeline
Set up a CI pipeline with containers, static analysis and hardware in the loop.
Master's Thesis
Implement and validate an SDV platform for a chosen use case, defended before a panel.
Career opportunities

Where this takes you

SDV software architectAUTOSAR Adaptive engineerROS 2 engineerMiddleware engineerSoftware integration engineerSoftware validation engineer
Admissions & scholarships

Requirements

  • University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
  • 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.

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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 will work with ROS 2, Eclipse Cyclone DDS, Vector DaVinci Developer Adaptive, Docker and Wireshark. Free, academic or evaluation versions are used, and your tutor indicates the free alternative where 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.

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