Catálogo de publicaciones - libros

The spatial distribution of individuals is an important subject in many fields because it conditions the levels of interactions among individuals, and more generally the structuring as well as the organization of populations. Increase in density of individuals in a given area can be induced by environmental stimuli and/or by interactions among individuals (1–3). Thus, various definitions of aggregation have been given, ecologists privilege the importance of environmental stimuli, while others privilege existing relationships between group members.

Aggregation is one of the most widespread social phenomena and occurs at all biological levels, from bacteria to mammals including humans (4, 5). If sometimes, aggregation is associated to non-adaptive, often it is the ground on which more complex social structures are built such as synchronization or division of labour (6). However, knowledge of the mechanisms implied in the formation of aggregates remains fragmentary. The study of the proximal causes, i.e. mechanisms involved in group formation, can benefit from concepts of self-organization (5, 7). These groups find their origin and their cohesion in the inter-attraction among individuals: group members are then the source of attraction. However, in most of the situations, patterns of aggregation, resulting from individual responses to conspecifics are modulated by environmental heterogeneity (5).

Previous studies on cockroaches have already described their aggregative distribution in a natural environment where different age-classes share the resources that are present in their home range. They exhibit a strong tendency to gather during their resting period in safe shelters. Therefore, shelters are important, but also limited environmental resources for these insects.

The basic mechanisms underlying group formation is the modulation of the individual resting time as a function of the number of conspecifics on a site. In insects cuticular hydrocarbons act as a recognition signal allowing attraction between individuals (8). Cockroaches prefer their own strain odour to another strain (9). Nevertheless, when groups in tests came from two different strains, they aggregated on one site only and did not show any difference from group coming from one strain.

We used this insect as an example to show that a self-organized process leads to a diversity of optimal patterns without modification of the individual behaviours and any general knowledge of the available resources. These experimental and theoretical results point to a generic self-organized pattern-formation process independent of the level of animal sociability that should be found in other group-living organisms that present inter-attraction.

Signage systems are widely used in buildings to provide information for wayfinding, thereby assisting in navigation during normal circulation of pedestrians and, more importantly, exiting information during emergencies. An important consideration in determining the effectiveness of signs is establishing the region from which the sign is visible to occupants, the so-called Visibility Catchment Area (VCA). This paper attempts to factor into the determination of the VCA of signs, the observation angle of the observer using both experimental and theoretical analysis.

Random utility theory and discrete choice models have been widely used to explore mechanisms underlying pedestrian shopping behavior. However, these models tend to be mis-specified due to unrealistic assumption of utility maximising behavior. The bounded rationality theory may be more suitable for building models representing real shopping decision process, but existing statistical models are not able to extract information hidden in the decision process proposed by the theory. We therefore developed GEPAT, a computer program using Gene Expression Programming to solve this problem with its two most significant features. The first feature is that it has an extendable multigene-section chromosome structure which allows several inter-related target functions to be estimated simultaneously. The second feature is that it uses processors, representing mental operators, as building blocks to implement simple information processing and facilitate constructing and testing complex schemes of the problem by linking the processors properly. The overall workflow of GEPAT, its advantages, disadvantages and potentials are discussed.

The walking process is interpreted as a sequence of decisions about where to put the next step. A dynamic and individual-based spatial discretization is used to represent the physical space. A behavioral framework for pedestrian dynamics based on discrete choice models is given. Direction change behaviors and acceleration behaviors are taken into account, both in a constrained and unconstrained formulation. The unconstrained direction changes (keep direction, toward destination) and acceleration (free flow acceleration) behaviors are the same as those introduced in our previous work. In this paper we focus on the definition of the constrained counterparts. A leader follower behavior is interpreted as a constrained acceleration while collision avoidance behavior as a constrained direction change. The spatial correlation structure in the choice set deriving from a simultaneous choice of speed regimes and radial directions is taken into account specifying a cross nested logit model (CNL). Quantitative results are presented, obtained by maximum likelihood estimation on a real data set with more than 10 thousands observed positions, manually tracked from video sequences.

A frequently encountered difficulty in the field of pedestrian modelling and crowd dynamics is the scarcity of systematic empirical data. This paper attempts to narrow this gap by discussing the collection and analysis of large amounts of empirical data from around the world, which is used to first calibrate and then validate the microscopic pedestrian interaction model that lies at the heart of the commercial simulation software package ‘Legion’.

We briefly review the model which represents pedestrians as learning-adaptive agents with individual preferences and objectives. Next we describe our method of extracting microscopic (individual) and macroscopic (crowd) data from video recordings of real-life pedestrian crowds, filmed at selected locations. The former supply demographic profiles of pedestrian attributes used as inputs, and help calibrate the model parameters by probing context dependencies of the dynamics. The latter yield collective observables and patterns, used to benchmark simulation outputs.

We present examples of measurements and corresponding simulations, which demonstrate the breadth and quantitative agreement of the model with the data. Examples include sports spectators queuing as a result of operational procedures; commuters queuing at a bottleneck created by limited vertical circulation capacity; and train passengers boarding, and alighting from, densely populated carriages.

When designing complex buildings and tunnels featuring special characteristics, it is necessary to study the evacuation scenario in case of an incident in addition to the empirical figures gained from practice and expertise, in order to optimise the respective structures.

We present a method for simulating individual pedestrian motion based on empirical data. Our model keeps track of the pedestrian’s position and body configuration (pose) and uses motion capture data to produce plausible motion. While our ultimate goal is creating 3D animations of crowds, our initial efforts focus on 2D simulations. In this paper, we present a 2D model for an able-bodied male. Using our approach, we could also capture data and build models for a heterogeneous population, including children, the elderly, pedestrians in wheelchairs, and people on crutches. We demonstrate the realism of our model with a small-scale test case and a larger crowd evacuation simulation.

In order to accurately simulate pedestrian behaviour in complex situations, one is required to model both the physical environment and the strategic decision-making of individuals We present a method for integrating both of these model requirements, by distributing the computational complexity across discrete modules. These modules communicate with each other via XML messages. The approach also provides considerable flexibility for changing and evolving the model. The model is explained using an example of simulating hikers in the Swiss Alps.

Shopping centers and event halls established today are to be brought only with difficulty in harmony with the demands of the building code regulations and directives concerning the escape routes. Engineering methods like simulation-models for evacuation dynamics for the calculation of the evacuation time supply an indispensable instrument to find a compromise between a safe enough and coevally economical building. With simulation models it can be proved computational for example that in case of fire persons can leave a building quickly enough and without dubious congestions so that they are not endangered by smoke and fire gases. The difficult is that it is impossible to estimate the achieved safety level of a simulation because of the absence of a probabilistic safety concept. The question is: “How safe is safe enough”? In this article a global probabilistic safety concept is presented which in case of evacuation (for example in case of fire) starts from an extraordinary unfrequent event. The essential safety depends on the authoritative side conditions, varying by usefulness of a building, for the endangering of persons.

The WTC evacuation of 11 September 2001 provides an unrepeatable opportunity to probe into and understand the very nature of evacuation dynamics and with this improved understanding, contribute to the design of safer, more evacuation efficient, yet highly functional, high rise buildings. Following 9/11 the Fire Safety Engineering Group (FSEG) of the University of Greenwich embarked on a study of survivor experiences from the WTC Twin Towers evacuation. The experiences were collected from published accounts appearing in the print and electronic mass media and are stored in a relational data base specifically developed for this purpose. Using these accounts and other available sources of information FSEG also undertook a series of numerical simulations of the WTC North Tower. This paper represents an overview of the results from both studies.