Efficient parallel implementation of crowd simulation using a hybrid CPU plus GPU high performance computing system

Article Computer Science, Interdisciplinary Applications

Data-driven Crowd Modeling Techniques: A Survey

Jinghui Zhong et al.

Summary: This article provides a comprehensive survey of popular and effective data-driven crowd modeling techniques, including commonly used datasets, discussions on different methods, validation techniques, and six promising research topics.

ACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION (2022)

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Article Engineering, Civil

Emotion-Based Crowd Simulation Model Based on Physical Strength Consumption for Emergency Scenarios

Mingliang Xu et al.

Summary: This paper introduces an emotion-based crowd simulation model that integrates physical strength consumption and panic levels of individuals. The model uses a physics-based numerical method to compute human physical strength consumption and an enhanced emotional contagion model to estimate panic levels. It is the first method to integrate physical strength consumption into an emotion-based crowd simulation model.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2021)

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Article Computer Science, Software Engineering

A history of crowd simulation: the past, evolution, and new perspectives

Soraia Raupp Musse et al.

Summary: This paper discusses the past, evolution, and new perspectives in crowd simulation, revisiting the main aspects of the area and presenting historical periods and evolution. Additionally, it also discusses the present state and potential future trends.

VISUAL COMPUTER (2021)

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Article Computer Science, Software Engineering

Algorithms for Microscopic Crowd Simulation: Advancements in the 2010s

W. van Toll et al.

Summary: Real-time simulation of human crowds has various applications and research on how to simulate crowd movement in environments is actively growing. The focus is on microscopic crowd simulation methods, particularly in the areas of local navigation and collision avoidance. Researchers predict significant growth in data-driven and learning-based agent navigation methods in the future.

COMPUTER GRAPHICS FORUM (2021)

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Review Computer Science, Software Engineering