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deeprl_signal_control

multi-agent deep reinforcement learning for large-scale traffic signal control.

dotfiles

lustlte

LuST + VeinsLTE

lustscenario

Luxembourg SUMO Traffic (LuST) Scenario

mostscenario

Monaco SUMO Traffic (MoST) Scenario

persuasive

“Persuasive”: Crowdsensing-enabled Dynamic Traffic Congestion Mitigation Strategies for Large-Scale Social Events

persuasive-devel

Persuasive project development environment

pypml

Python Parking Monitoring Library for SUMO

random-grid-sumo

SUMO Scenario - Random Grid environment with parking areas and public transports (metro and bus). 24h mobility based on SAGA activity-based mobility generator.

ray

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

results

rllibsumodocker

Docker environment for RLLIB+SUMO Utils python library.

rllibsumoutils

Python3 library able to connect the RLLIB framework with the SUMO simulator.

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

sumo

SUMO is an open source, highly portable, microscopic and continuous road traffic simulation package designed to handle large road networks. It allows for intermodal simulation including pedestrians and comes with a large set of tools for scenario creation.

sumoactivitygen

An Activity-based Multi-modal Mobility Scenario Generator for SUMO. This project is available in the Eclipse SUMO contributed tools section (https://github.com/eclipse/sumo/tree/master/tools/contributed) under the name SAGA (SUMO Activity GenerAtion).

tralama

The TraLAMA plugin for JOSM allows the user to export the displayed OpenStreetMap data to the traffic simulation platform SUMO, run a traffic simulation and view the results in JOSM as additional layers.

tustscenario