Hai Yang, Ethan Wong, Haggai Davis III, Joseph Y.J. Chow
{"title":"A co-simulation system that integrates MATSim with a set of external fleet simulations","authors":"Hai Yang, Ethan Wong, Haggai Davis III, Joseph Y.J. Chow","doi":"10.1016/j.simpat.2024.102957","DOIUrl":null,"url":null,"abstract":"<div><p>Simulation plays a crucial role in transportation studies. However, most simulation tools are individually developed to tackle specific transportation problems, making it challenging to incorporate multiple simulation tools into a unified setting and generate collaborative output. In this study, we develop a co-simulation system that integrates MATSim with an external fleet-based simulator to extend MATSim's functionalities. The overall structure enables the integration of MATSim simulation and multiple external simulations, which results in a cohesive simulation output. Though only one external simulator engages in the current development, the framework can be easily adapted to involve more fleet-based simulators that meet the system requirements. As a result, more complex transportation systems can be simulated using the framework without the need to develop these dedicated MATSim extensions, e.g. any new fleet algorithm from emergent R&D. The developed co-simulation system is named the Fleet Demand (FD) Simulator. We demonstrate the functionality of the FD Simulator by showcasing a simulation scenario involving MATSim and a ride-pooling simulator, which integrates novel ride-pooling services into the MATSim environment. First, we show the co-simulation system's capability to generate reliable results consistent with those produced by using the \"DRT\" extension-enabled MATSim. Less than 10 % discrepancies between the two results are observed. We then use the FD Simulator to evaluate ride-pooling services under various scenarios, where we assign different service parameters to two service fleets. Operations of the two fleets are simulated in two separate external simulation environments, showcasing the FD simulator's ability of engaging multiple simultaneous simulations. The affected service parameters are not adjustable in the \"DRT\" extension, showing the advantage of the co-simulation system. By running these scenarios using the FD Simulator, travel decisions made by agents in MATSim are observed when facing heterogeneous ride-pooling services. The results highlight the relevance of the co-simulation system in evaluating complex transportation systems.</p></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"134 ","pages":"Article 102957"},"PeriodicalIF":3.5000,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Simulation Modelling Practice and Theory","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1569190X24000716","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Simulation plays a crucial role in transportation studies. However, most simulation tools are individually developed to tackle specific transportation problems, making it challenging to incorporate multiple simulation tools into a unified setting and generate collaborative output. In this study, we develop a co-simulation system that integrates MATSim with an external fleet-based simulator to extend MATSim's functionalities. The overall structure enables the integration of MATSim simulation and multiple external simulations, which results in a cohesive simulation output. Though only one external simulator engages in the current development, the framework can be easily adapted to involve more fleet-based simulators that meet the system requirements. As a result, more complex transportation systems can be simulated using the framework without the need to develop these dedicated MATSim extensions, e.g. any new fleet algorithm from emergent R&D. The developed co-simulation system is named the Fleet Demand (FD) Simulator. We demonstrate the functionality of the FD Simulator by showcasing a simulation scenario involving MATSim and a ride-pooling simulator, which integrates novel ride-pooling services into the MATSim environment. First, we show the co-simulation system's capability to generate reliable results consistent with those produced by using the "DRT" extension-enabled MATSim. Less than 10 % discrepancies between the two results are observed. We then use the FD Simulator to evaluate ride-pooling services under various scenarios, where we assign different service parameters to two service fleets. Operations of the two fleets are simulated in two separate external simulation environments, showcasing the FD simulator's ability of engaging multiple simultaneous simulations. The affected service parameters are not adjustable in the "DRT" extension, showing the advantage of the co-simulation system. By running these scenarios using the FD Simulator, travel decisions made by agents in MATSim are observed when facing heterogeneous ride-pooling services. The results highlight the relevance of the co-simulation system in evaluating complex transportation systems.
期刊介绍:
The journal Simulation Modelling Practice and Theory provides a forum for original, high-quality papers dealing with any aspect of systems simulation and modelling.
The journal aims at being a reference and a powerful tool to all those professionally active and/or interested in the methods and applications of simulation. Submitted papers will be peer reviewed and must significantly contribute to modelling and simulation in general or use modelling and simulation in application areas.
Paper submission is solicited on:
• theoretical aspects of modelling and simulation including formal modelling, model-checking, random number generators, sensitivity analysis, variance reduction techniques, experimental design, meta-modelling, methods and algorithms for validation and verification, selection and comparison procedures etc.;
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• simulation languages and environments including those, specific to distributed computing, grid computing, high performance computers or computer networks, etc.;
• distributed and real-time simulation, simulation interoperability;
• tools for high performance computing simulation, including dedicated architectures and parallel computing.