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.
Diploma in Urban Operation and Integration with TMS/ATMS — studying from the United States
The United States is a major center for autonomous driving and advanced driver assistance systems, with significant activity in California, Michigan, Pennsylvania and Texas. Automakers, technology firms and specialized startups develop sensor fusion, perception, planning and vehicle software platforms. The shift toward software-defined vehicles is reshaping traditional engineering roles and increasing demand for embedded software, cybersecurity and systems engineering talent. Federal and state rules on testing and safety create a demanding environment where validation and standards expertise is highly valued.
Fees for the United States: US$2,000 (US Dollars), with instalments and employer sponsorship available.
Relevant bodies in the United States
Typical roles
Questions from the United States
What US bodies and rules govern autonomous and ADAS vehicle engineering?
In the US, NHTSA sets federal vehicle safety standards and has issued guidance on automated driving systems, while states regulate testing and operation on public roads. SAE International's levels of driving automation are the common industry reference. Professional engineering licensure is handled by state boards. SEIUM's qualifications are private and not accredited by any national body, so their recognition is for employers or relevant bodies to decide.
Do US employers in autonomous driving and software-defined vehicles recognize private engineering qualifications?
US companies working on ADAS and software-defined vehicles, including automakers, Tier 1 suppliers and technology firms, mainly look for software, controls and safety-engineering experience. A private qualification can document specialist study, but it is not a standard hiring requirement and its value is assessed by each employer. Projects, code samples and relevant prior roles usually carry more weight.
Can I study autonomous and software-defined vehicle topics from the US alongside my job?
Yes. The programmes are online and taught in English, so you can study from home without a student visa. Expect a significant time commitment: about 1,900 hours for a master's, 800 hours for a postgraduate diploma, or 300 hours for a specialist course. Each student receives an assigned technical tutor. Fees may be paid in instalments, and some employers fund training, which you should discuss with your employer.
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.
What you will be able to do
Understand how urban traffic management systems work.
Analyse the impact of autonomous fleets on the city.
Design data exchange between the city and the vehicle.
Integrate autonomous vehicles with traffic signal infrastructure.
Manage urban space and the kerbside dynamically.
Coordinate incident management involving autonomous vehicles.
Establish municipal governance and evaluation frameworks.
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.
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
8 modules
1.1Functions of a traffic management centre1.2TMS and ATMS systems1.3Adaptive traffic signal control: SCOOT and SCATS1.4Detection: inductive loops, cameras and floating car data1.5Incident and event management1.6Traveller information1.7ITS architecture according to ISO 148131.8Directive (EU) 2023/2661 on intelligent transport systems1.9Role of the public administration versus private operators1.10Case study: analysis of a municipal traffic management centre
2.1Robotaxi and urban delivery services2.2Operational requirements of fleets2.3Authorised geographical zones2.4Interaction with public transport2.5Pick-up points and kerbside use2.6Impact on congestion and parking2.7Data the fleet can provide to the city2.8Data the city can provide to the fleet2.9Agreements between operators and city councils2.10Workshop: impact analysis of a robotaxi fleet
3.1The DATEX II model according to CEN/TS 161573.2The MDS mobility data specification3.3C-ITS in-vehicle information messages3.4National access points for data3.5APIs for access restrictions and roadworks3.6Data quality and latency3.7Data governance and licensing3.8Privacy of trajectory data3.9Delegated regulations under the ITS Directive3.10Practical exercise: publishing traffic restrictions in DATEX II
4.1Controllers and the NTCIP 1202 protocol4.2SPATEM and MAPEM messages to the vehicle4.3Signal phase prediction4.4Recommended green wave speed4.5Connected vehicle detection in adaptive control4.6Priority for autonomous services4.7Roadside units and deployment4.8Maintenance and signal quality4.9Cybersecurity of traffic signal infrastructure4.10Laboratory: traffic signal control with connected vehicle data in SUMO
5.1Geofences and dynamic operating zones5.2Kerbside management and loading zones5.3Temporary restrictions for events5.4Low-emission zones and access5.5Dynamic speed limits5.6Emergency and clearance routes5.7Communicating changes to the autonomous vehicle5.8Verifying fleet compliance5.9Digital planning tools5.10Case study: dynamic geofences for a sporting event
6.1Protocols for stopped vehicles6.2Interaction with police and emergency services6.3Instructions from traffic officers6.4Communication between the control centre and the fleet6.5Removal and recovery of vehicles6.6Incident logging and analysis6.7Notification to the authorities6.8Lessons from incidents in San Francisco6.9Joint drills6.10Practical exercise: joint protocol for an immobilised autonomous vehicle
7.1Municipal authorisation frameworks7.2Fleet performance indicators7.3Urban road safety assessment7.4Mobility impact assessment7.5Equity in access to the service7.6Public participation7.7Contracts and data agreements7.8Scaling up pilot projects7.9European city experiences7.10Workshop: municipal indicator dashboard for autonomous fleets
8.1Diagnosis of the urban area8.2Definition of the autonomous service8.3Data exchange architecture8.4Traffic signal integration8.5Dynamic space management8.6Incident protocol8.7Evaluation indicators8.8Governance plan8.9Report and presentation8.10Final project: final review with the tutor
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.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
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.
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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