Dynamic stride length adaptation according to utility and personal space. (April 2015)

• Record Type: Journal Article
• Authors: von Sivers, Isabella; Köster, Gerta
• Is Part Of: Transportation research. Volume 74(2015)
• Page Start: 104
• Page End: 117
• Publication Date: 2015-04
• Subjects: Pedestrian movement -- Crowd dynamics -- Optimal Steps Model -- Stride length adaptation -- Personal space -- Optimisation; Transportation -- Research -- Periodicals; Transportation -- Mathematical models -- Periodicals
• DOI: 10.1016/j.trb.2015.01.009
• Languages: English
• ISSNs: 0191-2615

Abstract

Highlights: Microscopic pedestrian motion model with adjustment of pedestrians' stride length. Stride adaptation according to established psychological personal space model. Calibration of the psychological parameters allows fitting to fundamental diagrams. Independent observables such as density at a bottleneck are correctly predicted. Abstract: Pedestrians adjust both speed and stride length when they navigate difficult situations such as tight corners or dense crowds. They try to avoid collisions and to preserve their personal space. State-of-the-art pedestrian motion models automatically reduce speed in dense crowds simply because there is no space where the pedestrians could go. The stride length and its correct adaptation, however, are rarely considered. This leads to artefacts that impact macroscopic observation parameters such as densities in front of bottlenecks and, through this, flow. Hence modelling stride adaptation is important to increase the predictive power of pedestrian models. To achieve this we reformulate the problem as an optimisation problem on a disk around the pedestrian. Each pedestrian seeks the position that is most attractive in a sense of balanced goals between the search for targets, the need for individual space and the need to keep a distance from obstacles. The need for space is modelled according to findings from psychology defining zones around a person that, when invaded, cause unease. The result is a fully automatic adjustment that allows calibration through meaningful social parameters and that gives visually natural results with an excellent fit to measured experimental data.