Analyzing pedestrian individual and interaction collision avoidance dynamics in traditional scenarios

Abstract Revealing the behavioral mechanism of crowd dynamics is crucial for explaining the self-organized phenomena and making a quick emergent response for crowd management. Various approaches have been proposed to analyze self-organized phenomena of crowd dynamics, but the essential mechanisms of complicated and heterogeneous collision avoidance behaviors are still not clear. To deeply investigate the microscopic behaviors, the geometrical characteristics of Voronoi diagrams and velocity obstacles are explored and a unified spatial tessellation and velocity obstacle approach is proposed. The personal space is divided into four regions, and a velocity graph that is a subgraph of Delaunay triangulation will be established to describe the relationship between pedestrians. In a velocity graph, a link represents that a pedestrian’s speed is towards a Voronoi edge of its neighbor. According to the experimental pedestrian trajectory data, the collision avoidance probability is relevant to some parameters, such as spatial conflict time, and minimal velocity difference. Results show that the probability is related to the distance to velocity obstacle boundary and relaxation time by Sigmoid function. Besides, the behavior dynamics in each region is analyzed, and it is determined by the deviation angles between Voronoi nodes and neighbor locations. This approach can be potentially applied to pedestrian behavioral analysis and crowd management.