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Postgraduate DiplomaAutonomous, ADAS & Software-Defined Vehicle Applications open

Diploma in Urban Operation and Integration with TMS/ATMS

Online postgraduate diploma of 800 hours in urban operation and TMS/ATMS integration. 8 modules covering urban traffic management, autonomous fleets in the city, city–vehicle data exchange, traffic signal integration, dynamic kerbside management, incident management and governance, with Directive (EU) 2023/2661, CEN/TS 16157 DATEX II and NTCIP 1202, with an assigned technical tutor.

Duration6–8 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

Understand how urban traffic management systems work.

02

Analyse the impact of autonomous fleets on the city.

03

Design data exchange between the city and the vehicle.

04

Integrate autonomous vehicles with traffic signal infrastructure.

05

Manage urban space and the kerbside dynamically.

06

Coordinate incident management involving autonomous vehicles.

07

Establish municipal governance and evaluation frameworks.

Profile

Who it's for

  • Traffic management engineers preparing their networks for autonomous services.
  • Urban mobility managers in local government.
  • ITS systems engineers working on traffic centres and connected infrastructure.
  • Autonomous fleet operations managers who deal with city authorities.
  • Mobility data analysts handling traffic and trajectory data.
  • Smart city consultants advising public administrations.
  • Engineering or science graduates looking to enter local government mobility departments.
Standards & tools

What you'll work with

  • Directive (EU) 2023/2661 (intelligent transport systems framework)
  • CEN/TS 16157 DATEX II (traffic data exchange)
  • NTCIP 1202 (actuated signal controller objects)
  • ETSI TS 103 301 (C-ITS facilities: SPATEM, MAPEM, IVIM)
  • ETSI EN 302 637-2 (cooperative awareness basic service)
  • ISO 14813-1 (ITS reference architecture)
  • Regulation (EU) 2022/1426 (type approval of automated driving systems)
  • Regulation (EU) 2016/679 (General Data Protection Regulation)
  • SUMO
  • Aimsun Next
  • PTV Optima
  • QGIS
  • Python with GeoPandas
Syllabus

8 modules

  1. 1.1Functions of a traffic management centre
  2. 1.2TMS and ATMS systems
  3. 1.3Adaptive traffic signal control: SCOOT and SCATS
  4. 1.4Detection: inductive loops, cameras and floating car data
  5. 1.5Incident and event management
  6. 1.6Traveller information
  7. 1.7ITS architecture according to ISO 14813
  8. 1.8Directive (EU) 2023/2661 on intelligent transport systems
  9. 1.9Role of the public administration versus private operators
  10. 1.10Case study: analysis of a municipal traffic management centre
  1. 2.1Robotaxi and urban delivery services
  2. 2.2Operational requirements of fleets
  3. 2.3Authorised geographical zones
  4. 2.4Interaction with public transport
  5. 2.5Pick-up points and kerbside use
  6. 2.6Impact on congestion and parking
  7. 2.7Data the fleet can provide to the city
  8. 2.8Data the city can provide to the fleet
  9. 2.9Agreements between operators and city councils
  10. 2.10Workshop: impact analysis of a robotaxi fleet
  1. 3.1The DATEX II model according to CEN/TS 16157
  2. 3.2The MDS mobility data specification
  3. 3.3C-ITS in-vehicle information messages
  4. 3.4National access points for data
  5. 3.5APIs for access restrictions and roadworks
  6. 3.6Data quality and latency
  7. 3.7Data governance and licensing
  8. 3.8Privacy of trajectory data
  9. 3.9Delegated regulations under the ITS Directive
  10. 3.10Practical exercise: publishing traffic restrictions in DATEX II
  1. 4.1Controllers and the NTCIP 1202 protocol
  2. 4.2SPATEM and MAPEM messages to the vehicle
  3. 4.3Signal phase prediction
  4. 4.4Recommended green wave speed
  5. 4.5Connected vehicle detection in adaptive control
  6. 4.6Priority for autonomous services
  7. 4.7Roadside units and deployment
  8. 4.8Maintenance and signal quality
  9. 4.9Cybersecurity of traffic signal infrastructure
  10. 4.10Laboratory: traffic signal control with connected vehicle data in SUMO
  1. 5.1Geofences and dynamic operating zones
  2. 5.2Kerbside management and loading zones
  3. 5.3Temporary restrictions for events
  4. 5.4Low-emission zones and access
  5. 5.5Dynamic speed limits
  6. 5.6Emergency and clearance routes
  7. 5.7Communicating changes to the autonomous vehicle
  8. 5.8Verifying fleet compliance
  9. 5.9Digital planning tools
  10. 5.10Case study: dynamic geofences for a sporting event
  1. 6.1Protocols for stopped vehicles
  2. 6.2Interaction with police and emergency services
  3. 6.3Instructions from traffic officers
  4. 6.4Communication between the control centre and the fleet
  5. 6.5Removal and recovery of vehicles
  6. 6.6Incident logging and analysis
  7. 6.7Notification to the authorities
  8. 6.8Lessons from incidents in San Francisco
  9. 6.9Joint drills
  10. 6.10Practical exercise: joint protocol for an immobilised autonomous vehicle
  1. 7.1Municipal authorisation frameworks
  2. 7.2Fleet performance indicators
  3. 7.3Urban road safety assessment
  4. 7.4Mobility impact assessment
  5. 7.5Equity in access to the service
  6. 7.6Public participation
  7. 7.7Contracts and data agreements
  8. 7.8Scaling up pilot projects
  9. 7.9European city experiences
  10. 7.10Workshop: municipal indicator dashboard for autonomous fleets
  1. 8.1Diagnosis of the urban area
  2. 8.2Definition of the autonomous service
  3. 8.3Data exchange architecture
  4. 8.4Traffic signal integration
  5. 8.5Dynamic space management
  6. 8.6Incident protocol
  7. 8.7Evaluation indicators
  8. 8.8Governance plan
  9. 8.9Report and presentation
  10. 8.10Final project: final review with the tutor
Methodology, software & labs

How you'll learn

The programme 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. You work with SUMO, Aimsun Next, PTV Optima, QGIS and Python with GeoPandas, in free, academic or evaluation versions. Testing is studied through real procedures: microsimulation of autonomous fleets on an urban network, publication and integration of traffic data, and incident drills with emergency services. Assessment is continuous by module, plus the final project.

Standards covered: Directive (EU) 2023/2661, CEN/TS 16157 DATEX II, NTCIP 1202, ETSI TS 103 301, ETSI EN 302 637-2, ISO 14813-1, Regulation (EU) 2022/1426, Regulation (EU) 2016/679.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of Directive (EU) 2023/2661, CEN/TS 16157 DATEX II and NTCIP 1202 applied to real cases, not as a theoretical annex.
Industry software:SUMO, Aimsun Next, PTV Optima, QGIS and Python with GeoPandas, in free, academic or evaluation versions.
Final project:An urban integration plan for an autonomous service, covering data exchange, traffic signal integration, incident protocol and governance, 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.

Urban area diagnosis
Diagnose the urban area and define the autonomous service to be deployed.
Data exchange architecture
Design the city–vehicle data exchange using DATEX II and C-ITS messages.
Signal and space integration
Plan traffic signal integration and dynamic management of kerbside and operating zones.
Incident protocol and indicators
Define the joint incident protocol and the evaluation indicators for the fleet.
Final project
Present the complete urban integration plan with its governance framework.
Career opportunities

Where this takes you

Traffic management engineerUrban mobility managerITS systems engineerAutonomous fleet operations managerMobility data analystSmart city consultant
Admissions & scholarships

Requirements

  • Prior technical training or professional experience in the sector. A university degree is not 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 800 hours over 6–8 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with SUMO, Aimsun Next, PTV Optima, QGIS and Python with GeoPandas, 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 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.

Prior technical training or professional experience in the sector (no university degree required), a computer able to run the 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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