Dynamics analysis of pedestrian movement on slopes: Modelling, simulations and experiments

Abstract

Inclined structures play a crucial role in urban spatial planning, but inadequate crowd management often leads to significant safety risks. To better understand pedestrian dynamics on slopes and provide insights for effective crowd management, this study proposes a multi-factor floor field cellular automaton model for slope movement that integrates microscopic and mesoscopic scales. The model introduces a speed-density model that accounts for pedestrian heterogeneity, travel purposes, crowd density, and regional differences to establish the fundamental mechanism of speed variation. Additionally, the model establishes a function to evaluate pedestrian speed variations on slopes by incorporating the slope angle, the angle of movement deviation, and the distance travelled, with the function being calibrated based on empirical data. The results show that pedestrian speed variation on slopes follows a non-linear, accumulative pattern, with acceleration and deceleration effects becoming more pronounced as distance increases. The impact of slope angle on pedestrian speed variation trend is also non-linear, with 7° as the threshold. The initial speed of pedestrians, pedestrian density, and slope configuration all significantly affect the movement speed and efficiency of pedestrians on slopes. The proposed model was evaluated through real-world slope experiments and found that the simulation results closely match the experimental results. The findings illustrate that the proposed model has the potential to provide insights for analysing pedestrian dynamics on slopes movement scenarios. This study provides a model for evaluating pedestrian movement on slopes, with potential applications in optimising urban design, improving emergency evacuation strategies, and enhancing crowd management in high-density areas.