Postgraduate Diploma in Semantic Cartography and Risk-Prioritised Maps
Online Postgraduate Diploma of 800 hours in Semantic Cartography and Risk-Prioritised Maps. 8 modules covering Directive (EU) 2019/1936, Directive 2008/96/CE and QGIS. Dedicated tutor and enrolment open.
Postgraduate Diploma in Semantic Cartography and Risk-Prioritised Maps — studying from Malta
Malta is developing a niche in digital and software-intensive technologies, including connected mobility and vehicle-related software. The island's strong information technology and telecommunications base provides a natural foundation for work on advanced driver assistance, vehicle data and embedded software. Opportunities tend to arise with software houses, technology consultancies and multinational companies with engineering centres on the island. Professionals working in this area benefit from familiarity with functional safety standards and the software development practices used across the automotive value chain.
Fees for Malta: €1,490 (Euro), with instalments and employer sponsorship available.
Relevant bodies in Malta
Typical roles
Questions from Malta
Who regulates engineering practice and vehicle safety relevant to ADAS in Malta?
Engineering as a profession in Malta is regulated through the Chamber of Engineers (KSU) under the Engineering Profession Act, which governs the use of the title 'engineer'. Vehicle type approval and roadworthiness are handled by Transport Malta, and EU-level vehicle regulations apply. A SEIUM qualification is a private one and is not accredited by a national body, so its recognition depends on employers or the relevant authority.
Which Maltese employers could use ADAS or software-defined vehicle skills?
Demand in Malta is mainly from software, electronics and digital engineering firms, some serving automotive clients abroad, along with vehicle service and fleet operators. Large autonomous-vehicle deployment is not a major local sector, so roles are often remote or international. Employers will assess your portfolio, experience and any formal credentials, so present the qualification alongside concrete project work.
Can I study this at my own pace from Malta, and what language and workload should I expect?
Yes. Programmes are 100% online and taught in English, with an assigned technical tutor and a final project. No student visa is needed to study from home. Time zone is usually not a barrier since you study asynchronously, but confirm the schedule with the institute. Plan around your working hours, and ask about instalment payments and employer sponsorship.
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 the structure and ontologies of semantic maps.
Extract semantic information from sensors.
Analyse the spatial distribution of road crashes and their contributing factors.
Prioritise map elements and areas according to their risk.
Use the semantic map in vehicle functions.
Ensure the quality and interoperability of semantic data.
Apply the regulatory framework for road infrastructure safety.
Who it's for
- Semantic cartography engineer looking to specialise in Semantic Cartography and Risk-Prioritised Maps.
- Road safety analyst looking to specialise in Semantic Cartography and Risk-Prioritised Maps.
- GIS analyst looking to specialise in Semantic Cartography and Risk-Prioritised Maps.
- Perception engineer looking to specialise in Semantic Cartography and Risk-Prioritised Maps.
- Road infrastructure technician looking to specialise in Semantic Cartography and Risk-Prioritised Maps.
- Safe mobility consultant looking to specialise in Semantic Cartography and Risk-Prioritised Maps.
- Engineering or science graduates seeking to enter the automotive sector.
What you'll work with
- Directiva (UE) 2019/1936
- Directiva 2008/96/CE
- ISO 39001:2012
- ASAM OpenDRIVE 1.8
- ISO 21448:2022 (SOTIF)
- Real Decreto 345/2011
- ISO 19157-1:2023
- ASAM OpenXOntology 1.0
8 modules · 800 h
1.1Semantic versus geometric layers1.2Ontologies of the road environment1.3Lanes, zones and rules1.4Dynamic and temporal semantics1.5Lanelet2 and semantic OpenDRIVE1.6ASAM OpenXOntology1.7Uses in planning and prediction1.8Granularity and level of detail1.9Priority relationships and right of way1.10Case study: semantic modelling of a roundabout
2.1Semantic image segmentation2.2Point cloud segmentation2.3Bird's-eye-view projection2.4Aggregation of multiple drives2.5Vector maps with HDMapNet2.6Online vector maps with MapTR2.7Fusion of semantic observations2.8Labelling and verification2.9Classification of urban land use2.10Laboratory: BEV semantic map with nuScenes
3.1Geo-referenced crashes3.2Kernel density estimation3.3Spatial autocorrelation and Moran's index3.4Crash prediction models3.5Infrastructure risk factors3.6Exposure and traffic volumes3.7iRAP star rating assessment3.8Risk indicators by road section3.9Negative binomial regression in crash data3.10Practical: crash density map in QGIS
4.1Criticality of safety-relevant elements4.2Risk matrix by layer4.3Risk-prioritised updating4.4Inspection frequency according to criticality4.5Allocation of capture resources4.6Differentiated quality by zone4.7School and sensitive environments4.8Residual risk and acceptance4.9Cost-effectiveness of prioritisation4.10Workshop: prioritised map maintenance plan
5.1Speed adjustment according to context5.2Focused attention in risk zones5.3Priority in perception and prediction5.4Conditional activation of functions5.5ODD management with map information5.6Contextual driver alerts5.7Consistency between map and perception5.8Degradation when the map is outdated5.9Intelligent speed adaptation5.10Practical: map-based speed limiter
6.1Semantic data schemas6.2Spatial databases6.3Semantic quality control6.4Attribute traceability6.5Integration with open data6.6Interoperability between providers6.7Privacy in crash data6.8Public data licences6.9Updating risk attributes6.10Case study: integrating open crash data
7.1Infrastructure safety management7.2Directive on road infrastructure safety7.3Road safety impact assessment7.4Safety audits and inspections7.5ISO 39001 management systems7.6Vision Zero and municipal plans7.7Use of the map by public administrations7.8Risk communication7.9Network classification by safety level7.10Workshop: network assessment under Directive 2019/1936
8.1Definition of the study area8.2Collection of semantic data8.3Building the semantic map8.4Spatial crash analysis8.5Prioritisation matrix8.6Integration into vehicle functions8.7Prioritised update plan8.8Benefit assessment8.9Report and presentation8.10Final review with the tutor
How you'll learn
100 % online training on the SEIUM campus, with downloadable material, recorded classes and a dedicated technical tutor. No fixed timetable: students progress at their own pace within the intake, making it easy to combine with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is QGIS, PostGIS, Lanelet2, PyTorch, Python (PySAL), in free, academic or evaluation versions. Practicals cover real procedures for building a BEV semantic map, spatial analysis of urban crashes, and risk-based prioritisation of map maintenance. Assessment is continuous per module plus the final integrative project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Understand the structure and ontologies of semantic maps.
Extract semantic information from sensors.
Analyse the spatial distribution of road crashes and their factors.
Prioritise map elements and areas according to their risk.
Use the semantic map in vehicle functions.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university 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.
Frequently asked questions
The programme consists of 800 hours in total, spread over 6 to 8 months. That is an average of 10 to 15 hours per week, compatible with full-time work.
The programme uses QGIS, PostGIS, Lanelet2, PyTorch, Python (PySAL). Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
A SEIUM own diploma upon passing the continuous assessment and the integrative project. This is in-house training, not an official qualification from the Ministry.
Yes. Modules passed in a course or postgraduate diploma in the same area can be credited towards the higher programme. Check the credit transfer policy when you enrol.
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