In an urban public transport system, mass rapid transit (MRT) stations play an important role in the concentration and deconcentration of passengers. Spatial conflicts and unclear routes may lead to crowding in MRT stations and reduce their operational efficiency. For this reason, this study proposes a space service quality evaluation method based on agent-based simulation by employing spatial information from building information modeling (BIM) systems as boundary constraints. Moreover, passengers and trains are simulated as interacting agents with complex behaviors in a limited space. This method comprehensively assesses congestion, noise, and air quality to determine service quality in different spaces. Moreover, the results are visualized in different ways for decision making about space planning. Finally, this research demonstrates and verifies the functions of the proposed system with an actual MRT station. Such simulation results can be used as a reference for management personnel to adjust space/route plans to increase passenger satisfaction environment quality, and operational efficiency in the operation stage of an MRT station. The evaluation method establishes valid and reliable measures of service performance and passenger satisfaction as well as other performance outcomes.
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