PHuNAC Model: Simulation of Human Nature and Personalities of Autonomous Crowds

PHuNAC Model: Simulation of Human Nature and Personalities of Autonomous Crowds

Olfa Beltaief (ISG of Tunis, Tunisia), Sameh El Hadouaj (Emirates College of Technology, UAE) and Khaled Ghedira (ISG of Tunis, Tunisia)
DOI: 10.4018/978-1-4666-9572-6.ch006
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Abstract

The swarm behavior of pedestrians in a crowd, generally, causes a global pattern to emerge. A pedestrian crowd simulation system must have this emergence in order to prove its effectiveness. For this reason, the aim of this work is to demonstrate the effectiveness of the PHuNAC model (Personalities' Human's Nature of Autonomous Crowds) and also prove that the swarm behavior of pedestrians' agents in this model allows the emergence of these global patterns. In order to validate the approach of this work, the authors compared the simulation system with real data. The conducted experiments show that the model is consistent with the various emergent behaviors and thus it provides realistic simulated pedestrian's behavior.
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Introduction

The pedestrian crowd can be defined as a group of individuals who share the same location. The pedestrian crowd is a phenomenon which can be observed in several situations such as in the street, in the commercial areas, football events, etc. For this purpose, it becomes an inseparable event of the daily life.

Concretely, in this everyday phenomenon we observe a collective behavior. This collective behavior presents an extremely surprising organizational ability. In fact, none of pedestrians who compose these crowds is really aware of this apparent divergence. This phenomenon is called “swarm behavior”. The swarm behavior phenomenon has taken a big theoretical and practical interest in scientific research. The simulation of this phenomenon helps us to reproduce the pedestrian behavior. Indeed, the swarm behavior of pedestrians in a crowd, generally, causes a global pattern to emerge. A pedestrian crowd simulation system must have this emergence in order to prove its effectiveness

Hence, many scientists and researchers are interested to find solutions that seriously improve pedestrian's swarm behavior. It could be really interesting to be able to simulate the swarm behavior in a real way in such environments in order to predict the situation and consequently take the necessary precautions. This solution also helps to manage these important events and to avoid dangerous situations. Indeed, a manager can estimate the behavior of the crowd through the simulation and take thereafter the necessary precautions. However, the manager may have misleading information if the simulation of the system which does not reflect reality. For this reason, simulation models of pedestrian crowds are useful only if they reproduce realistic simulation. Several pedestrian crowd simulation models were proposed. These models could be classified into two families: macroscopic models and microscopic models. The macroscopic approaches simulate the behavior of the crowd as a whole. In this case, the system is generally described in terms of the density of individuals or the travel speeds average in different areas of the space. On the other hand, the microscopic approaches are interested in the behavior, actions and decisions of each pedestrian and their interactions with others (Challenger R., Clegg .C & Robinson M., 2009). The microscopic models allow obtaining more details on simulated crowds. For this reason, in our work, we adopt a microscopic approach and more specifically an Agent-Based model. In fact, multi-agent systems represent the most suitable tool for realistic simulation (Eric Bonabeau, 2002). However, if psychological factors are not reflected when implementing the pedestrian agent behavior, the resulting simulation would not be realistic. A growing emphasis is set on researching the effects of human personalities. Concretely, a great number of Agent -Based crowd simulation models do not cover all the psychological factors which are necessary for a pedestrian located in a crowd (see Moussaïd M., Perozo N., Garnier S., Helbing D. & Theraulaz G., 2010; Natalie Fridman & Gal A. Kaminka, 2007). Moreover, many of these models simulate only homogenous personalities of pedestrians, where actually, there are different personalities. Experimentations’ results of these models show that they lack realism. For this purpose, the goal of this work is to reproduce realistic pedestrian crowd simulated situations by simulating a realistic pedestrian behavior and personality. This work includes, firstly, the HuNAC (Human's Nature of Autonomous Crowds) model which integrates the necessary psychological factors for a pedestrian located in a crowd (O.Beltaief, S.Hadouaj & K.Ghedira, 2011). As a second step, this work includes also the PHuNAC (Personnalities’ Human's Nature of Autonomous Crowds) version which integrates heterogeneous crowd (O.Beltaief, S.Hadouaj & K.Ghedira, 2014a, 2014b).

Key Terms in this Chapter

Fundamental Diagrams: Each field has its own fundamentals diagrams. These diagrams represent the principal characteristics of this field. In the crowd pedestrian field, the velocity and the flow rates are the most important characteristics.

Swarm Behavior: The swarm behavior is the collective behavior of a large number of animals or individuals which aggregate together.

Emergence Behavior: The emergence behavior is the result of the collective behavior of a large number of animals or individuals that does not depend on its individual parts, but on their relationships to one another. There is not a prior agreement between individuals to organize the group's activities.

Qubit: The qubit consists of a superposition of two basis states like the case of the bit 0 and 1. Except that the classical bits are always either in state 0 or in state 1 whiles a qubit is the superposition of these two states.

Human Nature: The human nature is the set of the constraints and norms that define the patterns of thoughts, feelings, and behaviors guided by the evolved psychological mechanisms encompass.

Clogging and Arching Behavior: In emergency case and when there is dense crowds push forward towards a narrow exit, clogging and arching are observed. The exit becomes clogged and the crowd forms an arch-shape, radiating outwards from the exit.

Lane Formation Behavior: When pedestrians move in opposite directions, they self-organize to form a lane for each direction. These two lanes of pedestrians appear so perfectly organized. In the reality, there is not a prior agreement between individuals to organize the group's activities and improve the ride comfort of all. This organization helps to reduce pedestrian collisions and increase speed.

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