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Mercury: An open-source simulator for the evaluation of air transport mobility

Luis Delgado et al.

European Journal of Transport and Infrastructure Research2026https://doi.org/10.59490/ejtir.2026.26.1.7529article
ABDC B
Weight
0.50

Abstract

The Mercury simulator, a performance assessment platform, is a stochastic, agent-based model developed over several years during research projects. It features a detailed description of the air transportation system at the European level, including passengers and aircraft, and various important actors such as the Network Manager, airports, etc. This article presents the possibilities offered by the simulator’s current, now open-source version. We describe the core Mercury functionalities and highlight its modularity and the possibility of its usage with other tools. We present a new interface, which supports user-friendly interaction with the simulator, exploring data input/output and parameter settings. We emphasise possible uses as a solution performance assessment tool, which is usable early in the innovation pipeline to better estimate the impact of changes and new systems in the air transportation system. We hope that opening the simulator may encourage other developers to open their models, allowing faster prototyping of new operational concepts early in the innovation pipeline and an in fine support standardisation and higher performance of simulation-based performance assessment tools.

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https://doi.org/https://doi.org/10.59490/ejtir.2026.26.1.7529

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@article{luis2026,
  title        = {{Mercury: An open-source simulator for the evaluation of air transport mobility}},
  author       = {Luis Delgado et al.},
  journal      = {European Journal of Transport and Infrastructure Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.59490/ejtir.2026.26.1.7529},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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