cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: "Yousefi"
    given-names: "Mojtaba"
    orcid: "https://orcid.org/0000-0002-2671-1295"
  - family-names: "Koutsopoulos"
    given-names: "Haris N."
    orcid: "https://orcid.org/0000-0003-3830-9794"
title: "TransitLab SimMETRO: A Modern Rail Transit Simulation Platform"
version: 0.2.0
doi: 10.5281/zenodo.13111726
date-released: 2024-06-01
url: "https://myousefi.github.io/transit-lab-SimMETRO-docs/"
repository-code: "https://github.com/myousefi/transit-lab-SimMETRO-docs"
keywords:
  - research
  - software
  - transit
  - urban heavy rail
  - MIT Transit Lab
  - performance evaluation
  - signal system
  - microspopic simulation
  - object-oriented design
  - modular
  - fixed-block
  - moving-block
  - design pattern
abstract: >
  TransitLab SimMETRO is an urban heavy-rail operations simulation model developed at the MIT Transit Lab, built upon decades of research. This repository contains a comprehensive documentation. While the full package may not be open-sourced soon, the documentation provides valuable insights into the capabilities of the simulation model.
references:
  - type: article
    authors:
      - family-names: "Koutsopoulos"
        given-names: "Haris N."
      - family-names: "Wang"
        given-names: "Zhigao"
    title: "Simulation of Urban Rail Operations"
    year: 2007
    journal: "Transportation Research Record"
    volume: 2006
    pages: "84-91"
    url: "https://api.semanticscholar.org/CorpusID:110620690"

  - type: inproceedings
    authors:
      - family-names: "Wang"
        given-names: "Zhigao"
      - family-names: "Koutsopoulos"
        given-names: "Haris N."
    title: "Calibration of urban rail simulation models: a methodology using SPSA algorithm"
    year: 2011
    booktitle: "Proceedings of the Winter Simulation Conference"
    location: "Phoenix, Arizona"
    publisher: "Winter Simulation Conference"
    series: "Wsc '11"
    pages: "3704–3714"
    abstract: "Rail simulation model calibration is a process of adjusting model parameters while comparing model output with observations from the real rail system. There is a lack of systematic methodology for calibrating urban rail simulation models. Based on a simulator developed for urban rail operations and control, the paper demonstrates a methodology of calibrating model parameters, and specifically, fine-tuning some of the simulation inputs. The calibration process is modeled as a multi-variate optimization problem and solved by the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm. A case study of the Massachusetts Bay Transportation Authority (MBTA) Red Line shows that the methodology improves the simulation model dramatically in terms of replicating the track block runtimes. At the same time, it upgrades the station specific dwell time parameters and enhances a-priori boarding rates at stations fairly effectively."
    numpages: 11

  - type: article
    authors:
      - family-names: "Zhou"
        given-names: "Jiali"
      - family-names: "Koutsopoulos"
        given-names: "Haris N."
      - family-names: "Saidi"
        given-names: "Saeid"
    title: "Evaluation of Subway Bottleneck Mitigation Strategies using Microscopic, Agent-Based Simulation"
    year: 2020
    journal: "Transportation Research Record"
    volume: 2674
    pages: "649-661"
    url: "https://api.semanticscholar.org/CorpusID:218922083"

  - type: phdthesis
    authors:
      - family-names: "Zhou"
        given-names: "Jiali"
    title: "Urban rail simulation and applications in service planning and operations"
    year: 2022
    school: "Northeastern University"
    publisher: "Northeastern University Library"

  - type: article
    authors:
      - family-names: "Zhou"
        given-names: "Jiali"
      - family-names: "Koutsopoulos"
        given-names: "Haris N."
    title: "Schedule-based Analysis of Transmission Risk in Public Transportation Systems"
    year: 2022
    journal: "ArXiv"
    volume: "abs/2202.08505"
    url: "https://api.semanticscholar.org/CorpusID:246904579"