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

Pedestrian movement has always been one of the main concerns for urban planning and design, but it has become more important within the sustainable development agenda, as walking is crucial to reducing urban emissions and fostering liveable cities. Therefore, urban planners need 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 is applied to a pedestrian precinct in the city centre of Gothenburg, Sweden, and is 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 ability to statistically predict pedestrian movement 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 and specific pedestrian behaviour. This functionality is valuable for urban design and planning practice, contributing to the optimisation of pedestrian flow dynamics.