Research Data Leeds Repository

Citation

Bocian, Mateusz, Soczawa-Stronczyk, Artur A. and Curtis, Samuel D. (2026) Data from: A data-driven model of pedestrian stepping behaviour including randomness and interpersonal interactions. University of Leeds. [Dataset] https://doi.org/10.5518/1858

Dataset description

Human walking gait exhibits complex and subtle dynamics. In individuals, footstep frequency is both speed-dependent and subject to random variability. In pairs, especially when given a shared task or when holding hands, pedestrians tend to synchronise their steps. In crowds, this tendency appears weaker due to the presence of multiple simultaneous sensory cues for gait coordination. A time-domain, data-driven model capable of reproducing such behaviours and suitable for implementation in crowd simulations is proposed in this study. In this model, the time intervals between footsteps are generated by a stochastic process that takes as inputs walking speed and the presence of visible neighbouring pedestrians. The proposed model enriches agent-based crowd simulations, enabling more realistic representations of human movement in urban planning, evacuation analysis, and infrastructure design.

Keywords:	crowd dynamics, gait synchronisation, stepping behaviour
Subjects:	H000 - Engineering > H200 - Civil engineering
Divisions:	Faculty of Engineering and Physical Sciences > School of Civil Engineering
License:	Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited:	11 May 2026 20:09
URI:	https://archive.researchdata.leeds.ac.uk/id/eprint/1546
Additional details Additional details Creators or authors: Creators ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type Bocian, Mateusz https://orcid.org/0000-0002-3539-5474 University of Leeds https://ror.org/024mrxd33 ror Soczawa-Stronczyk, Artur A. https://orcid.org/0000-0002-3393-8404 University of Leeds https://ror.org/024mrxd33 ror Curtis, Samuel D. https://orcid.org/0009-0000-7513-4132 University of Leeds https://ror.org/024mrxd33 ror Type of data: Dataset Research funders: University of Leeds Publication date: 2026 Resource language: English Metadata language: English Publisher: University of Leeds Contact email: vdft5519@leeds.ac.uk Last Modified: 12 May 2026 12:22

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