Microscopic road traffic simulator is a powerful tool to analyze and evaluate various transportation systems due to its efficiency and risk-free operation. It is, therefore, widely used in traffic engineering field along with the gradual implementation of novel intelligent transportation systems. A reliable microscopic traffic simulator is able to accurately represent the real-world traffic situation when it is effectively calibrated with the combination of field data and proper simulation settings. Based on the existing theoretical calibration framework for the microscopic traffic simulator, this paper proposes an online calibration procedure using genetic algorithm as well as a specific implementation method to provide real-time performance measures that adequately mimic the field traffic situation. The proposed method was tested based on loop detector data demonstrating that real-time traffic modeling can be run in parallel with the real-world traffic process.

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Scientific computation is emerging as the central pillar of science. However, loosed research practices and the own nature of the work is leading to a credibility crisis. Reproducible computational research is gaining attraction in the last decades not only because it benefits the validation and attestation of findings, making a more trustworthy publication, but also lowering the barrier of entry, making it more understandable for the target audience and, therefore, increasing its impact. In this article, an online platform where it is possible to store, share and execute linked code and data, from signal processing, applied to electric power quality, is presented. In such manner, this article presents an alternative for researchers in the field to conduct and share their work satisfying the requirements of reproducible research.