Introduction

Introduction#

Project Overview#

TransitLab SimMETRO is a sophisticated simulation tool developed upon decades of research (Koutsopoulos and Wang [KW07] and Zhou [Zho22]) and development to address the operational challenges faced by heavy rail systems in major metropolitan areas, particularly during peak periods when demand is highest. This tool provide microscopic simulation model for heavy rail systems, enabling detailed analysis of train behaviors, signaling systems (fixed-block and moving block), and interactions between trains and passengers. By employing TransitLab SimMETRO, reseachers can evaluate various operating strategies such as skip-stop, station consolidation, and dwell control to mitigate capacity bottlenecks.

The simulation framework is built using Python in a unix environment, ensuring robust performance and flexibility. The model’s accuracy and reliability can be further enhanced through a calibration process using data from Operational Control Systems [WK11]. Numerous visualization tools allow users to analyze simulation outputs.

Numerous case studies (see Zhou et al. [ZKS20] and Zhou and Koutsopoulos [ZK22]) demonstrate how MIT TransitLab SimMETRO has helped agencies address congestion, improve service reliability, and support long-term planning decisions.

Features#

  1. Detailed modeling of signal systems, including both fixed-block and moving-block, with precise train movement simulations at the individual vehicle level.

  2. Accurate dwell time modeling at stations to reflect real-world scenarios.

  3. Realistic passenger boarding and alighting behaviors.

  4. Implementation of headway-based dispatching to model stochasticities in rail operations.

  5. Comprehensive simulation outputs for thorough analysis.

  6. Multiple visualization tools available for detailed examination of simulation data.

  7. Customizable train movement models to suit various rail systems.

License#

The project License is yet to be determined. Please contact the development team for more information.

[KW07]

Haris N. Koutsopoulos and Zhigao Wang. Simulation of Urban Rail Operations. Transportation Research Record, 2006:84–91, 2007. URL: https://api.semanticscholar.org/CorpusID:110620690.

[WK11]

Zhigao Wang and Haris N. Koutsopoulos. Calibration of urban rail simulation models: a methodology using SPSA algorithm. In Proceedings of the Winter Simulation Conference, Wsc '11, 3704–3714. Winter Simulation Conference, 2011.

[Zho22]

Jiali Zhou. Urban rail simulation and applications in service planning and operations. PhD thesis, Northeastern University, 2022.

[ZK22]

Jiali Zhou and Haris N. Koutsopoulos. Schedule-based Analysis of Transmission Risk in Public Transportation Systems. ArXiv, 2022. URL: https://api.semanticscholar.org/CorpusID:246904579.

[ZKS20]

Jiali Zhou, Haris N. Koutsopoulos, and Saeid Saidi. Evaluation of Subway Bottleneck Mitigation Strategies using Microscopic, Agent-Based Simulation. Transportation Research Record, 2674:649–661, 2020. URL: https://api.semanticscholar.org/CorpusID:218922083.

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