摘要
This paper describes a novel model known as the shadow obstacle model to generate a realistic comer-tuming behavior in crowd simulation. The motivation for this model comes from the observation that people tend to choose a safer route rather than a shorter one when turning a comer. To calculate a safer route, an optimization method is proposed to generate the corner-turning rule that maximizes the viewing range for the agents. By combining psychological and physical forces together, a full crowd simulation framework is established to provide a more realistic crowd simulation. We demonstrate that our model produces a more realistic comer-turning behavior by comparison with real data obtained from the experiments. Finally, we per- form parameter analysis to show the believability of our model through a series of experiments.
This paper describes a novel model known as the shadow obstacle model to generate a realistic corner-turning behavior in crowd simulation. The motivation for this model comes from the observation that people tend to choose a safer route rather than a shorter one when turning a corner. To calculate a safer route, an optimization method is proposed to generate the corner-turning rule that maximizes the viewing range for the agents. By combining psychological and physical forces together, a full crowd simulation framework is established to provide a more realistic crowd simulation. We demonstrate that our model produces a more realistic corner-turning behavior by comparison with real data obtained from the experiments. Finally, we perform parameter analysis to show the believability of our model through a series of experiments.
基金
Project supported by the National Natural Science Foundation of China(Nos.61170318 and 61300133)
the Open Research Funding Program of Key Laboratory of Geographic Information Science,China(No.KLGIS2015A05)
the Fundamental Research Funds for the Central Universities,China(No.222201514331)
the Opening Project of Shanghai Key Laboratory of New Drug Design,China(No.14DZ2272500)
