Understanding Pedestrian Dynamics with JuPedSim: A Guide to Egress Time Evaluation
Understanding pedestrian movement, especially in emergency scenarios, is crucial for public safety. How quickly can a building be evacuated? Where are bottlenecks likely to occur? These are questions that JuPedSim, a powerful pedestrian dynamics simulator, helps us answer. In this blog post, we’ll explore the core components of a JuPedSim simulation and demonstrate how to evaluate egress time using a Python script.
The Foundation: Defining Your Environment with DXF
At the heart of any JuPedSim simulation is the definition of the environment. JuPedSim leverages DXF files (Drawing Exchange Format) for this purpose, making it easy to import geometry from CAD software.
1. Geometry Definition (DXF):
Your first DXF file will define the physical layout of your simulation space. This includes walls, obstacles, and any other fixed structures. Imagine an office building, a stadium, or a concert hall – every structural element needs to be accurately represented.
This image shows a typical geometry DXF file, outlining the walls of a building. Notice how different layers can be used to categorize elements, in this case, “WALLS.”
2. Emergency Exits (DXF):
Equally important are the emergency exits. These are also defined using DXF files, but typically as distinct entities within your geometry. JuPedSim needs to know where pedestrians can leave the simulation area.
Here, the green highlighted areas represent the defined emergency exits within the same building layout. These are critical for determining egress paths and times.
Populating Your Simulation: Defining the Agents
Once your environment is set, it’s time to introduce the “pedestrians” – or agents – into your simulation. This is typically done through an XML configuration file.
1. Agent Definition (Number, Speed, Destination):
You’ll define various properties for your agents, including:
- Number of Agents: How many individuals will be simulated?
- Average Speed: What’s their typical walking speed? JuPedSim can also account for variations and distributions.
- Destination: Where do they intend to go? In an egress scenario, their destination will be one of the defined emergency exits.
- Initial Positions: Where do they start within the simulation space?
Running the Simulation and Evaluating Egress Time with Python
With the geometry and agents defined, you can now run the JuPedSim simulation. The output of the simulation will typically be a file containing the trajectories of all agents over time. This data is then ripe for analysis.
This image depicts a snapshot of a JuPedSim simulation in progress. The colored dots represent individual agents moving through the defined geometry towards the exits. The “Time” and “Agents Remaining” counters would dynamically update in an actual animation, providing real-time insights into the evacuation process.
Conclusion
JuPedSim offers a robust platform for simulating pedestrian dynamics. By carefully defining your geometry, emergency exits, and agent properties, you can conduct realistic simulations of various scenarios. Furthermore, by leveraging Python, you can easily process the simulation output to derive critical metrics like egress time, helping engineers, urban planners, and safety officials make informed decisions to improve public safety and efficiency.
CloudHPC is a HPC provider to run engineering simulations on the cloud. CloudHPC provides from 1 to 224 vCPUs for each process in several configuration of HPC infrastructure - both multi-thread and multi-core. Current software ranges includes several CAE, CFD, FEA, FEM software among which OpenFOAM, FDS, Blender and several others.
New users benefit of a FREE trial of 300 vCPU/Hours to be used on the platform in order to test the platform, all each features and verify if it is suitable for their needs