Division for Traffic Safety and Reliability

Research

    
The research of the chair for traffic safety and reliability focuses on model-based safety analysis and simulation of highway and urban traffic systems, intelligent transportation systems, advanced driver-assistance and driving automation systems, pedestrian and evacuation dynamics, and swarm behaviors.

Pedestrian and vehicle flows are both dynamical systems of self-driven agents interacting locally with partial knowledge of the environment. They are complex as the system performances can not be directly deduced from the individual behaviors of the agents. The system behaviors describe non-linear phenomena and phase transitions to self-organized collective dynamics, e.g., lane formation or stop-and-go waves upon other coordinated phenomenas and paradoxes.

We develop and analyze mathematical models and numerical simulation tools for pedestrian and vehicular dynamics 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 traffic states, including collective dynamics, and to device safe and intelligent traffic management and control systems. The computations are carried out using open-source packages such as R and Python, or multi-agent simulation platforms like NetLogo, JuPedSim, SUMO, CARLA, or GAMA.

   
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

  • R – Statistical computing and graphics (open-source)

  • PyTorch – Machine learning Python framework (open-source)

  • 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)

  • PeTrack – Automatic pedestrian video tracking (open-access)

  • SysMLModeling language for systems engineering (open-source)

Traffic flow and pedestrian dynamics

   
Complex systems and multi-agent systems

  
Intelligent transportation systems and automated vehicles

   
Reliability engineering, statistical physics, and applied mathematics

   
Artificial intelligence and machine learning

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.

    

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