Fachgebiet für Verkehrssicherheit und Zuverlässigkeit

Research

    
The research of the chair for traffic safety and reliability focuses on system and model-based reliability analysis, multi-agent systems, interaction particle systems, highway and mixed urban traffic, intelligent transportation systems, advanced driver-assistance systems, and pedestrian and evacuation dynamics.

We develop and analyze mathematical models and numerical simulation tools based on differential systems, stochastic processes, or data-driven algorithms. We calibrate and train models and algorithms using experimental and field data. The objective is to identify, understand, predict, and control complex systems, including collective dynamics. The computations are carried out using open-source packages and multi-agent simulation platforms.

   
Approach:         Modelling  →  Analysis  →  Simulation  →  Optimisation

Duality:             Linear modelling  –  Non-linear modelling
                          Physics and knowledge-based  –  Data-driven / Deep learning
                          Microscopic approaches  –  Mesoscopic / Macroscopic approaches

Pedestrian trajectories

   
Road vehicle naturalistic trajectories

   
Predictive maintenance

  • NetLogo – Simulation of multi-agent systems (open-source)

  • JuPedSim – Simulation and analysis of pedestrian models (open-access)

  • GAMA Platform – Agent-based modelling and simulation (open-source)

  • Eclipse SUMO – Simulation of Urban MObility (open-access)

  • CARLA Simulator – Autonomous driving simulator (open-source)

  • MATSim – Large-scale agent-based transport simulations (open-source)

Traffic flow and pedestrian dynamics

   
Complex systems and multi-agent systems

  
Intelligent transportation systems and automated vehicles

   
Reliability engineering

   
Artificial intelligence and machine learning

    

wikicfp.com (conferences and calls for paper search engine)

Collective Dynamics is a diamond open-access multidisciplinary journal publishing research in the field of pedestrian dynamics, vehicular traffic, and other systems of self-driven particles or interacting agents.

The journal covers, but is not limited to, the following areas:

Further information are available here.

  • R – Statistical computing and graphics

  • PyTorch – Machine learning Python framework

  • SysMLModeling language for systems engineering

  • ChatGDPGenerative pre-trained transformer

  • OpenPIV – Particle image velocimetry

  • OpenCV – Pedestrian detection

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