Postgraduate Diploma in VRU Detection and Risk-Based Urban Safety
Online 800-hour Postgraduate Diploma in VRU Detection and Risk-Based Urban Safety. 8 modules covering Regulation (EU) 2019/2144 (GSR), UN Regulation No. 152 and PyTorch. Dedicated tutor and enrolment open.
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
Analyse the accident statistics and risk factors affecting vulnerable road users.
Implement robust pedestrian and cyclist detectors.
Predict the intention and trajectory of vulnerable road users.
Calculate real-time risk metrics.
Specify VRU protection functions in line with regulations.
Apply infrastructure measures for urban safety.
Evaluate protection systems through testing and simulation.
Who it's for
- Perception engineer looking to specialise in VRU Detection and Risk-Based Urban Safety.
- Active safety engineer looking to specialise in VRU Detection and Risk-Based Urban Safety.
- Road safety engineer looking to specialise in VRU Detection and Risk-Based Urban Safety.
- Accident analyst looking to specialise in VRU Detection and Risk-Based Urban Safety.
- Researcher in behaviour prediction looking to specialise in VRU Detection and Risk-Based Urban Safety.
- Municipal mobility technician looking to specialise in VRU Detection and Risk-Based Urban Safety.
- Graduates in engineering or sciences seeking to enter the automotive sector.
What you'll work with
- Reglamento (UE) 2019/2144 (GSR)
- Reglamento ONU n.º 152
- Reglamento ONU n.º 151
- Reglamento ONU n.º 159
- Reglamento ONU n.º 138
- ISO 39001:2012
- ETSI TS 103 300-3
- ISO 21448:2022 (SOTIF)
8 modules · 800 h
1.1Statistics for pedestrians, cyclists and motorcyclists1.2Users of personal mobility vehicles (VMP) and new forms of mobility1.3Typical pedestrian collision configurations1.4Urban risk factors1.5Pedestrian injury biomechanics1.6Accident databases such as GIDAS1.7Vision Zero approach and safe system1.8DGT regulations on VMP1.9Older people and children as at-risk groups1.10Case study: accident rates in a city
2.1Single-stage and two-stage detectors2.2Partially occluded persons2.3Pose and orientation estimation2.4Cyclists and e-scooter riders2.5Small objects at long range2.6Night-time detection2.7EuroCity Persons and CityPersons datasets2.8Log-average miss rate metric2.9Detection of wheelchairs and pushchairs2.10Laboratory: pedestrian detector with YOLO
3.1Intention cues: gaze, posture and direction3.2Social force models3.3Trajectory prediction with LSTM3.4Transformer-based models3.5Multimodal and probabilistic prediction3.6Pedestrian–vehicle interaction3.7PIE and JAAD datasets3.8ADE and FDE metrics3.9Behaviour at uncontrolled crossings3.10Practical: predicting pedestrian crossing
4.1Time to collision and surrogate safety measures4.2Risk fields and potentials4.3Collision probability with uncertainty4.4Expected impact severity4.5Risk by urban context4.6Object prioritisation by risk4.7Warning and intervention thresholds4.8False positive management4.9Impact speed and probability of injury4.10Laboratory: risk calculation with real data
5.1AEB for pedestrians and cyclists5.2Turn assist for heavy vehicles5.3Blind spot detection5.4Door opening warning5.5Active bonnet systems5.6AVAS acoustic warnings5.7Driver interface and acceptance5.8UN Regulations No. 151 and No. 1595.9Direct vision in lorry cabs5.10Case study: specification of a turn assist system
6.1Safe intersection design6.2Infrastructure sensors and smart crossings6.3V2X messages for VRUs6.4Video-based conflict analysis6.5Traffic calming and speed limits6.6Accident black spots6.7Collaboration with town councils6.8Urban safety indicators6.9Segregated cycle lanes and their design6.10Practical: conflict analysis at an intersection
7.1Euro NCAP protocols for VRUs7.2Pedestrian and cyclist dummies7.3CPNA and CBLA test scenarios7.4Simulation of urban scenarios7.5Evaluation in real driving7.6EU General Safety Regulation7.7Estimated benefit in casualties avoided7.8Fairness in the detection of user groups7.9Retrospective analysis of real accidents7.10Workshop: AEB pedestrian test plan
8.1Definition of the target urban environment8.2Baseline accident analysis8.3Vulnerable user detector8.4Intention prediction model8.5Risk metric and prioritisation8.6Proposed protection function8.7Evaluation in scenarios8.8Complementary infrastructure measures8.9Report and presentation8.10Final review with the tutor
How you'll learn
Training 100 % online 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, which makes it possible to combine the programme with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is PyTorch, Ultralytics YOLO, CARLA, IPG CarMaker, PTV Vissim, in free, academic or evaluation versions. Testing is studied through real procedures for pedestrian detection in urban environments, conflict analysis at a real intersection, and evaluation of AEB for pedestrians in Euro NCAP scenarios. Assessment is continuous per module plus the final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Analyse the accident statistics and risk factors affecting vulnerable road users.
Implement robust pedestrian and cyclist detectors.
Predict the intention and trajectory of vulnerable road users.
Calculate real-time risk metrics.
Specify VRU protection functions in line with regulations.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. A university degree is not 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 comprises 800 hours in total, spread over 6 to 8 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.
The programme works with PyTorch, Ultralytics YOLO, CARLA, IPG CarMaker, PTV Vissim. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
A SEIUM Institute diploma upon passing the continuous assessment and the integrating project. This is in-house training, not an official qualification from the Ministry.
Yes. Modules passed in a course or diploma in the same area are recognised in the advanced programme. Check the recognition policy when you enrol.
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