Abstract
Pedestrian crowds often have been modeled as many-particle system including microscopic multi-agent simulators. One of the key challenges is to unearth governing principles that can model pedestrian movement, and use them to reproduce paths and behaviors that are frequently observed in human crowds. To that effect, we present a novel crowd simulation algorithm that generates pedestrian trajectories that exhibit the speed-density relationships expressed by the Fundamental Diagram. Our approach is based on biomechanical principles and psychological factors. The overall formulation results in better utilization of free space by the pedestrians and can be easily combined with well-known multi-agent simulation techniques with little computational overhead. We are able to generate human-like dense crowd behaviors in large indoor and outdoor environments and validate the results with captured real-world crowd trajectories.
Highlights
The problem of simulating the movement and behaviors of human-like crowds is important in many applications, including architecture and urban design, pedestrian dynamics, computer animation, games, virtual reality, etc
We address the problem of modeling crowd behaviors governed by these densities: which we term as density-dependent behaviors
Main Results We present a novel approach for crowd trajectory computation in dense scenarios that can generate realistic density-dependent behaviors and result in good space utilization
Summary
The problem of simulating the movement and behaviors of human-like crowds is important in many applications, including architecture and urban design, pedestrian dynamics, computer animation, games, virtual reality, etc. A key observation in understanding how individual trajectories are formulated arises from studies in pedestrian dynamics and traffic management that highlight the relationship between crowd density and pedestrian movement; as density increases, speed decreases [1,2,3,4,5,6,7]. This phenomenon is called the Fundamental Diagram [8].
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