Abstract
In recent years, modelling crowd and evacuation dynamics has become very important, with increasing huge numbers of people gathering around the world for many reasons and events. The fact that our global population grows dramatically every year and the current public transport systems are able to transport large amounts of people heightens the risk of crowd panic or crush. Pedestrian models are based on macroscopic or microscopic behaviour. In this paper, we are interested in developing models that can be used for evacuation control strategies. This model will be based on microscopic pedestrian simulation models, and its evolution and design requires a lot of information and data. The people stream will be simulated, based on mathematical models derived from empirical data about pedestrian flows. This model is developed from image data bases, so called empirical data, taken from a video camera or data obtained using human detectors. We consider the individuals as autonomous particles interacting through social and physical forces, which is an approach that has been used to simulate crowd behaviour. The target of this work is to describe a comprehensive approach to model a huge number of pedestrians and to simulate high density crowd behaviour in overcrowding places, e.g. sport, concert and pilgrimage places, and to assist engineering in the resolution of complicated problems through integrating a number of models from different research domains.
Highlights
In recent years, several models for the movement of crowds have been proposed
With the huge development in the transportation technology in recent years the number of pilgrims arriving to Mecca grow systematically
The third scenario showed the optimum steady state when about 125 pilgrim enter per minute and exit the floor, with no jams. This results in an overall capacity of about 9000 finished Tawaf/hour and an average time of approximately 25 min to complete the Tawaf
Summary
Several models for the movement of crowds have been proposed. One can distinguish between. In this model, individuals are treated as self-driven particles that interact through social and physical rules. The current velocity and direction of a single individual in the crowd is a result of the circumstances and social interactions. These social forces can be influenced by the environment, other people and internal states. In this approach, the pedestrians are treated as “particles” moving according to Newton’s law: dv dr. We will discuss the main forces that can be identified acting on a pedestrian
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