Empirical characterisation of agents’ spatial behaviour in pedestrian movement simulation

Summary

Route choice behaviour is an important factor in determining pedestrian movement flows across the urban space. Agent-based modelling, a simulation paradigm that allows modelling individual behaviour mechanisms to observe the emergence of macro-level patterns, has not employed empirical data regarding route choice behaviour in cities or accommodated heterogeneity. The aim of this paper is to present an empirically based Agent-Based Model (ABM) that accounts for behavioural heterogeneity in pedestrian route choice strategies, for simulating the movement of pedestrians in cities. We designed a questionnaire to observe to what degree people resort to salient urban elements (i.e. local and global landmarks, regions, and barriers) and road costs (i.e. road distance, cumulative angular change) and empirically characterise the agent behaviour in our ABM. We hypothesised that a heterogeneous ABM configuration based on the construction of agent typologies from empirical data would portray a more plausible picture of pedestrian movement flows than a homogeneous configuration based on the same data, or a random configuration. The city of Münster (DE) was used as a case study. From a sample of 301 subjects, we obtained six clusters that differed in the usage of global elements (distant landmarks, barriers, and regions) and meaningful local elements along the route, when they choose their route. The random configuration directed agents nearby natural elements and across the streets of the historical centre. The empirically based model configurations resulted in lower pedestrian volumes along roads designed for cars (25% decrease) but higher concentrations along the city's Promenade and the lake (40% increase); based on our knowledge, we deem those results more plausible. Little differences were identified between the heterogeneous and homogeneous configurations. While these findings indicate that the inclusion of heterogeneity does not make a difference in terms of global patterns, we demonstrated that simulation models of pedestrian movement in cities should be at least based on average, sample-level, empirical data to inform urban planners about areas subject to high volumes of pedestrians.