Master’s in Semantic Mapping and Risk-Prioritised Maps Engineering
Online master's programme of 1,900 hours in semantic cartography and risk-prioritised maps engineering, structured in 12 modules covering semantic map models and ontologies, semantic segmentation, road risk analysis, crash and conflict data, risk layers, risk-aware planning and validation, map production, road infrastructure management and data governance, with an assigned technical tutor.
Master’s in Semantic Mapping and Risk-Prioritised Maps Engineering — studying from India
Indian engineering hubs in Bengaluru, Pune, Chennai and Hyderabad are increasingly involved in advanced driver assistance systems and software-defined vehicle development. Global automotive suppliers and technology firms run large engineering centres here, working on perception, sensor fusion and vehicle software platforms. Standards for automotive functional safety draw on ISO 26262, and vehicle type approval falls under the Ministry of Road Transport and Highways, with testing support from the Automotive Research Association of India. Engineers in this area focus on embedded software, autonomous driving algorithms, validation and cybersecurity for connected vehicles.
Fees for India: ₹628,000 (Indian Rupee), with instalments and employer sponsorship available.
Relevant bodies in India
Typical roles
Questions from India
Which professional bodies in India cover autonomous and ADAS engineering?
In India, vehicle and software engineering is covered by bodies such as SAE India, ARAI for vehicle standards and testing, and the Institution of Engineers (India). There is no single licence for autonomous vehicle engineers. SEIUM's qualifications are private and not accredited by a national body, so recognition is decided by employers or the relevant body. Confirm this with them before enrolling.
Which employers in India use ADAS and software-defined vehicle skills?
Demand comes from carmakers and Tier-1 suppliers developing driver assistance and connected-car systems, as well as software and semiconductor firms in Bengaluru, Pune and Chennai. Global technology companies with engineering centres in India also hire in this area. A private online qualification can support a move into these roles, but employers mainly assess project work, coding ability and domain experience.
How can I study this while working in India, and what does the workload involve?
The programme is 100% online, taught in English, and you can study from your home in India without a student visa. Schedules are set against IST, so check deadlines against your work hours. Specialist courses are about 300 hours, postgraduate diplomas about 800 and master's about 1,900. Each student gets an assigned technical tutor, and fees can be paid in instalments. Ask your employer about funding support.
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
Design semantic models and ontologies of the road environment.
Generate semantic maps using deep segmentation.
Analyse road risk using crash and conflict data.
Build risk layers integrated into HD maps.
Integrate risk into planning and validation.
Assess the ethical and data governance implications.
Develop a risk-prioritised semantic cartography project.
Who it's for
- Semantic cartography engineers.
- Road safety analysts.
- Geospatial data engineers.
- Driving planning engineers.
- Ontology specialists.
- Smart infrastructure consultants.
- Engineering or science graduates looking to enter cartography.
What you'll work with
- ASAM OpenDRIVE (road network description format)
- ASAM OpenSCENARIO (driving scenario description format)
- ISO 34503 (taxonomy for the operational design domain)
- Directive (EU) 2019/1936 (road infrastructure safety management)
- ISO 39001 (road traffic safety management systems)
- ISO 21448 (safety of the intended functionality, SOTIF)
- ISO 19157-1 (geographic data quality)
- Regulation (EU) 2016/679 (General Data Protection Regulation, GDPR)
- Lanelet2
- QGIS
- Protégé
- PyTorch
- PostGIS
12 modules · 1900 h
1.1From geometric maps to semantic maps1.2Ontologies of road entities1.3Traffic rules encoded in the map1.4Priority and right-of-way relations1.5Maps as a virtual sensor1.6Semantic maps for L2+ and L41.7Context and behaviour layers1.8Limitations of current maps1.9Trends in intelligent maps1.10Case study: semantic model of a roundabout
2.1OWL and RDF languages2.2Driving scenario ontologies2.3ASAM OpenXOntology model2.4Road knowledge graphs2.5Reasoning about traffic rules2.6SPARQL queries on the map2.7Integration with Lanelet22.8Validation of semantic consistency2.9Interoperability between models2.10Lab: intersection ontology in Protégé
3.1Point-cloud segmentation3.2Segmentation of aerial imagery3.3Fusion of multi-view segmentations3.4Bird's-eye-view semantic maps3.5Online semantic mapping with HDMapNet3.6Vectorisation with MapTR3.7Road type classification3.8Detection of roadworks zones3.9Semantic quality metrics3.10Practical: generating a semantic BEV map
4.1Crash risk analysis methods4.2Risk indices by road section4.3The iRAP programme and star ratings4.4Black spots and high-concentration sections4.5Crash prediction models4.6Geometric risk factors4.7Traffic conflict data4.8Surrogate safety indicators4.9EuroRAP infrastructure assessment4.10Workshop: risk index of a road
5.1Crash databases5.2Georeferencing of crashes5.3Harsh-braking data from fleets5.4Near-miss detection5.5Time to collision and PET5.6Spatial analysis with kernel density estimation5.7Temporal and seasonal analysis5.8Biases in crash data5.9Privacy in conflict data5.10Lab: conflict heat map
6.1The concept of a map with a risk layer6.2Assigning risk to map elements6.3Risk-based prioritisation of production6.4Risk-based prioritisation of updates6.5Dynamic risk from weather and traffic6.6Risk from vulnerable road users6.7Risk associated with roadworks6.8Representation of risk in formats6.9Use of risk in planning6.10Practical: risk layer in OpenDRIVE
7.1Risk maps in route planning7.2Risk-based speed adjustment7.3Conservative behaviour in critical zones7.4Map-based ODD restrictions7.5Activation and deactivation of functions7.6Risk-based driver warnings7.7Integration with eHorizon7.8Assessment of the safety benefit7.9Validation in simulation7.10Workshop: risk-aware planner
8.1Extracting scenarios from the map8.2Prioritisation of test scenarios8.3Risk-based ODD coverage8.4Generation of critical scenarios8.5Using OpenSCENARIO with maps8.6Selection of validation routes8.7Exposure metrics8.8Safety argumentation8.9Integration with SOTIF8.10Case study: risk-based validation plan
9.1Data sources for semantic layers9.2Automatic attribute production9.3Crowdsourcing of risk events9.4Detection of semantic changes9.5Prioritised update cycles9.6Semantic quality control9.7Versioning of risk layers9.8Distribution to the vehicle9.9Maintenance costs9.10Lab: semantic update pipeline
10.1Risk maps for road authorities10.2Planning of safety investments10.3Road safety audits10.4Road Infrastructure Safety Management Directive10.5Preparing roads for automation10.6Machine-readable signage10.7Digital twins of roads10.8Collaboration between OEMs and road authorities10.9Open infrastructure data10.10Practical: prioritisation of road investments
11.1Biases in risk maps11.2Territorial fairness in prioritisation11.3Transparency of risk algorithms11.4Personal data protection11.5Liability for erroneous information11.6Use of data by insurers11.7Governance of shared data11.8Data quality standards11.9Communicating risk to the user11.10Case study: ethical assessment of a risk map
12.1Definition of the study area12.2Design of the semantic model12.3Generation of semantic layers12.4Road risk analysis12.5Construction of the risk layer12.6Integration into planning12.7Validation of the approach12.8Conclusions and future work12.9Master's Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
The programme is 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 the intake, so you can combine it with your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Lanelet2, QGIS, Protégé, PyTorch and PostGIS, in free, academic or evaluation versions. Testing is studied through real procedures for spatial analysis of crash data, generation of semantic maps with deep learning and validation of risk-aware planning. Assessment is continuous by module, plus the final Master's Thesis.
Standards covered: ASAM OpenDRIVE, ASAM OpenSCENARIO, ISO 34503, Directive (EU) 2019/1936 (road infrastructure safety management), ISO 39001, ISO 21448, ISO 19157-1, Regulation (EU) 2016/679 (GDPR).
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
- 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.
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 work with Lanelet2, QGIS, Protégé, PyTorch and PostGIS, 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 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 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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