About the CoMSES Model Library more info
CoMSES Net maintains cyberinfrastructure to foster FAIR data principles for access to and (re)use of computational models. Model authors can publish their model code in the Computational Model Library with documentation, metadata, and data dependencies and support these FAIR data principles as well as best practices for software citation. Model authors can also request that their model code be peer reviewed to receive a DOI. All users of models published in the library must cite model authors when they use and benefit from their code.
Please check out our model archive tutorial or contact us if you have any questions or concerns about archiving your model.
CoMSES Net also maintains a curated database of over 7500 publications of agent-based and individual based models with additional metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
3D Urban Traffic Simulator (ABM) in Unity
Sedar Olmez Obi Thompson Sargoni Alison Heppenstall Daniel Birks Annabel Whipp Ed Manley | Published Fri Jan 22 10:49:44 2021 | Last modified Mon Mar 22 15:38:03 2021The Urban Traffic Simulator is an agent-based model developed in the Unity platform. The model allows the user to simulate several autonomous vehicles (AVs) and tune granular parameters such as vehicle downforce, adherence to speed limits, top speed in mph and mass. The model allows researchers to tune these parameters, run the simulator for a given period and export data from the model for analysis (an example is provided in Jupyter Notebook).
The data the model is currently able to output are the following:
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Agent-based Line-of-Sight Simulation for safer Crossings (Short Paper - Netlogo Model)
Vincent Franke | Published Thu Aug 5 07:57:48 2021This software simulates cars and bicycles as traffic participants while crossing different crossroad designs such as roundabouts, protected crossroads and standard crossroads. It is written in Netlogo 6.2 and aims to identify safety characteristics of these layouts using agent-based modeling. Participants track the line of sight to each other and print them as an output alongside with the adjacent destination, used layout, count of collisions/cars/bicycles and time.
Detailed information can be found within the info tab of the program itself.
This model presents an autonomous, two-lane driving environment with a single lane-closure that can be toggled. The four driving scenarios - two baseline cases (based on the real-world) and two experimental setups - are as follows:
- Baseline-1 is where cars are not informed of the lane closure.
- Baseline-2 is where a Red Zone is marked wherein cars are informed of the lane closure ahead.
- Strategy-1 is where cars use a co-operative driving strategy - FAS. <sup>[1]</sup>
- Strategy-2 is a variant of Strategy-1 and uses comfortable deceleration values instead of the vehicle’s limit.
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Evacuation of the city of Rouen using the GAMA advanced driving skill
Patrick Taillandier Guillaume Czura Pierrick Tranouez Eric Daudé | Published Thu Apr 25 09:03:01 2019Model that illustrates the use of the GAMA advanced driving skill through a case study concerning the evacuation of the city of Rouen (France).
Eixample-MAS Traffic Simulation
Àlex Pardo Fernandez David Sánchez Pinsach | Published Tue Jan 22 09:33:39 2013 | Last modified Sat Apr 27 20:18:30 2013This MAS simulates the traffic of Barcelona Eixample. Uses a centralized AI system in order to control the traffic lights. Car agents are reactive and have no awareness of the intelligence of the system. They (try to) avoid collisions.