This agent based traffic model is built using the MESA package in python. We simulate the movement of cars on a road network using a grid model. Cars drive random optimal paths, stopping when they are too close to other cars or when they encounter a red traffic light. Traffic lights were placed at each intersection. Additionally, when a car experiences a high level of congestion (calculated as the ratio of its cumulative speed and maximum speed) it enters a hasty state, causing the agent to drive over the speed limit. The model output measured is the average congestion experienced by agents.
All simulation files are under the abm_project folder.
There are four parameters in our model that can be adjusted:
- maximum number of cars
- traffic light duration
- maximum speed
- haste tolerance level
Executing run.py will open the simulation as a browser window, where the model parameters can be tweaked using sliders.
The sensitivity_analysis.ipynb is a Jupyter Notebook that does sensitivity analysis on the model with OFAT and Sobol decomposition.
The simulation shows the average congestion level and the haste level, the more cars being put into the simulation, the likely it will get a high congestion. This may cause a gridlock, where the cars are not able to move anymore.
"Mesa: Agent-based modeling in Python 3+ — Mesa .1 documentation", Mesa.readthedocs.io, 2021. [Online]. Available: https://mesa.readthedocs.io/en/stable/index.html. [Accessed: 03- Feb- 2021].
Copyright by 2020 Core Mesa Team,
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