A hybrid workflow connecting a network and an agent-based model for predictive pedestrian movement modelling

Artikel i vetenskaplig tidskrift, 2024

Pedestrian movement has always been a main concern for urban planning and design, but has become more important within the sustainable development agenda, as walking is crucial to reduce urban emissions and foster livable cities. Therefore, urban planners need to be able to take pedestrian movement into consideration as part of the workflow of planning and designing cities. This study outlines a comprehensive workflow tailored for urban planners. It proposes a hybrid model that integrates an agent-based model, which simulates the micro-scale movement of pedestrians in outdoor urban environments, with a network model, which predicts the aggregated pedestrian flows on a macro-scale. The hybrid model has been applied to a pedestrian precinct in the city centre of Gothenburg, Sweden and has been compared to real-world measurements. The reasonable agreement between the simulation results and the real-world data supports the reliability of the proposed workflow, underscoring the model’s capability of predicting pedestrian movement statistically on a large scale and individually on a local scale. Furthermore, the model enables the analysis of flow distributions and movement restrictions and facilitates the analysis of different design scenarios as well as specific pedestrian behavior. This functionality is valuable for urban design and planning practice, contributing to the optimization of pedestrian flow dynamics.