"Libsignal: an open library for traffic signal control" by Hao Mei, Xiaoliang Lei et al.
 

Libsignal: an open library for traffic signal control

Document Type

Article

Publication Date

8-1-2024

Abstract

This paper introduces a library for cross-simulator comparison of reinforcement learning models in traffic signal control tasks. This library is developed to implement recent state-of-the-art reinforcement learning models with extensible interfaces and unified cross-simulator evaluation metrics. It supports commonly-used simulators in traffic signal control tasks, including Simulation of Urban MObility(SUMO) and CityFlow, and multiple benchmark datasets for fair comparisons. We conducted experiments to validate our implementation of the models and to calibrate the simulators so that the experiments from one simulator could be referential to the other. Based on the validated models and calibrated environments, this paper compares and reports the performance of current state-of-the-art RL algorithms across different datasets and simulators. This is the first time that these methods have been compared fairly under the same datasets with different simulators.

Identifier

85177767796 (Scopus)

Publication Title

Machine Learning

External Full Text Location

https://doi.org/10.1007/s10994-023-06412-y

e-ISSN

15730565

ISSN

08856125

First Page

5235

Last Page

5271

Issue

8

Volume

113

Grant

2153311

Fund Ref

National Science Foundation

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