Modelling and simulation of realistic pedestrian behaviours

• Main Author: Koh, Wee Lit
• Other Authors: Zhou Suiping
• Format: Theses and Dissertations
• Language: English
• Published: 2009
• Subjects: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling; DRNTU::Engineering::Computer science and engineering::Computer applications::Social and behavioral sciences
• Online Access: https://hdl.handle.net/10356/14961
• Institution: Nanyang Technological University

Pedestrian simulation provides interesting challenges in the area of 3D visualization, computer animations, behaviourial modelling and real-time crowd simulation. With increasing computing power, many researchers are now proposing autonomous agent representation and behaviourial models that more closely reflect the behaviours of real-humans. Following this trend, an accurate representation of an autonomous agent that has human-like sensory inputs and attention systems has been developed in this research. Another important consideration in this research is to balance between the accuracy of a pedestrian representation and the computational costs of using such a representation. A pedestrian simulation is primarily concerned with the generation of realistic navigation behaviours for autonomous agents. To address this challenge, a two-tier navigation model for path-planning and reactive planning in a complex and dynamic environment has been proposed to more accurately model the navigation behaviours of a pedestrian. First, a macro-level navigation model is developed to mimic the way pedestrians plan their route to reach a particular destination in the environment. Secondly, a micro-level navigation model is developed to steer the agent away from collision with structural obstacles and other agents. In addition, the micro-level navigation model ensures that the agent stays on course according to the rough path computed by the macro-level navigation model. The proposed navigation model is able to combine the different navigation considerations of a pedestrian in the form of steering constraints on the micro-level navigation model and heuristics for the macro-level navigation model. Moreover, the navigation model is computationally efficient in that it is able to compute hundreds of agent movements in a fraction of a second.