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      Deviation of Pedestrian Path due to the Presence of Building Entrances

      1 , 2 , 1 , 2 , 3 , 3
      Journal of Advanced Transportation
      Hindawi Limited

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          Abstract

          Commercial areas, especially urban ones with numerous buildings, are becoming increasingly prone to congestion because of their popularity. Visual inspections show that interactions between pedestrians and building entrances affect the distribution of pedestrian trajectories, which influences the utility of pedestrian spaces and the design of urban shopping areas. Herein, we analyse the dynamics of pedestrian deviations around building entrances. We used a video recorded using an unmanned aerial vehicle to determine pedestrian trajectories in a Chinese commercial walking space. First, the candidate variables affecting deviation behaviours were determined via correlation testing. Second, two regression models were developed by considering the deviation behaviours of pedestrians walking past a building entrance. The models suggest that the starting position of a pedestrian’s deviation, the total pedestrian flow at the building entrance, the density in an area in the vicinity of the entrance, and the number of interacting pedestrians impact the total distance traversed during path deviation.

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          Social force model for pedestrian dynamics

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            The Walking Behaviour of Pedestrian Social Groups and Its Impact on Crowd Dynamics

            Human crowd motion is mainly driven by self-organized processes based on local interactions among pedestrians. While most studies of crowd behaviour consider only interactions among isolated individuals, it turns out that up to 70% of people in a crowd are actually moving in groups, such as friends, couples, or families walking together. These groups constitute medium-scale aggregated structures and their impact on crowd dynamics is still largely unknown. In this work, we analyze the motion of approximately 1500 pedestrian groups under natural condition, and show that social interactions among group members generate typical group walking patterns that influence crowd dynamics. At low density, group members tend to walk side by side, forming a line perpendicular to the walking direction. As the density increases, however, the linear walking formation is bent forward, turning it into a V-like pattern. These spatial patterns can be well described by a model based on social communication between group members. We show that the V-like walking pattern facilitates social interactions within the group, but reduces the flow because of its “non-aerodynamic” shape. Therefore, when crowd density increases, the group organization results from a trade-off between walking faster and facilitating social exchange. These insights demonstrate that crowd dynamics is not only determined by physical constraints induced by other pedestrians and the environment, but also significantly by communicative, social interactions among individuals.
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              Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions

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                Author and article information

                Contributors
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                Journal
                Journal of Advanced Transportation
                Journal of Advanced Transportation
                Hindawi Limited
                2042-3195
                0197-6729
                June 29 2021
                June 29 2021
                : 2021
                : 1-12
                Affiliations
                [1 ]School of Architecture, Harbin Institute of Technology, Harbin 150006, China
                [2 ]Key Laboratory of Cold Region Urban and Rural Human Settlement Environment Science and Technology, Ministry of Industry and Information Technology, Harbin 150006, China
                [3 ]Department of Transport & Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology, CN Delft 2628, Netherlands
                Article
                10.1155/2021/5594738
                5dea2b54-b2f8-4015-b84f-9065e1ae3838
                © 2021

                https://creativecommons.org/licenses/by/4.0/

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