Guy Theraulaz

The Walking Behaviour of Pedestrian Social Groups and Its Impact on Crowd Dynamics

Human crowd motion is mainly driven by self-organized processes based on local interactions among pedestrians. While most studies of crowd behaviour consider only interactions among isolated individuals, it turns out that up to 70% of people in a crowd are actually moving in groups, such as friends, couples, or families walking together. These groups constitute medium-scale aggregated structures and their impact on crowd dynamics is still largely unknown. In this work, we analyze the motion of approximately 1500 pedestrian groups under natural condition, and show that social interactions among group members generate typical group walking patterns that influence crowd dynamics. At low density, group members tend to walk side by side, forming a line perpendicular to the walking direction. As the density increases, however, the linear walking formation is bent forward, turning it into a V-like pattern. These spatial patterns can be well described by a model based on social communication between group members. We show that the V-like walking pattern facilitates social interactions within the group, but reduces the flow because of its “non-aerodynamic” shape. Therefore, when crowd density increases, the group organization results from a trade-off between walking faster and facilitating social exchange. These insights demonstrate that crowd dynamics is not only determined by physical constraints induced by other pedestrians and the environment, but also significantly by communicative, social interactions among individuals.

Collective information processing and pattern formation in swarms, flocks, and crowds.

The spontaneous organization of collective activities in animal groups and societies has attracted a considerable amount of attention over the last decade. This kind of coordination often permits group-living species to achieve collective tasks that are far beyond single individuals capabilities. In particular, a key benefit lies in the integration of partial knowledge of the environment at the collective level. In this contribution, we discuss various self-organization phenomena in animal swarms and human crowds from the point of view of information exchange among individuals. In particular, we provide a general description of collective dynamics across species and introduce a classification of these dynamics not only with respect to the way information is transferred among individuals but also with regard to the knowledge processing at the collective level. Finally, we highlight the fact that the individuals ability to learn from past experiences can have a feedback effect on the collective dynamics, as experienced with the development of behavioral conventions in pedestrian crowds.

Are ants sensitive to the geometry of tunnel bifurcation

The ability to orient and navigate in space is essential for all animals whose home range is organized around a central point. Because of their small home range compared to vertebrates, central place foraging insects such as ants have for a long time provided a choice model for the study of orientation mechanisms. In many ant species, the movement of individuals on their colony home range is achieved essentially collectively, on the chemical trails laid down by their nest mates. In the initial stage of food recruitment, these trails can cross each other and thus form a network of interconnected paths in which ants have to orient. Previous simulation studies have shown that ants can find the shortest path between their nest and a food source in such a network only if there is a bias in the branch they choose when they reach an asymmetrical bifurcation. In this paper, we studied the choice of ants when facing either a symmetrical or an asymmetrical bifurcation between two tunnels. Ants were tested either on their way to a food source or when coming back to their nest, and either in the presence or in the absence of a chemical trail. Overall, our results show that the choice of an ant at a tunnel bifurcation depends more on the presence/absence of a trail pheromone than on the geometry of the bifurcation itself.

Role and variability of response thresholds in the regulation of division of labor in insect societies.

In this chapter, the regulation of division of labor in social insect colonies is studied from the perspective of response thresholds. Response thresholds refer to likelihood of reacting to task-associated stimuli. Low-threshold individuals perform tasks at a lower level of stimulus than high-threshold individuals. Task performance reduces the level of task-associated stimuli. A model based on fixed response thresholds is described, its assumptions discussed, and some of its predictions are shown to be in agreement with empirical observations. This model can be modified to make thresholds variable, but experimental results are scarce to guide the design of a model with variable thresholds. It is suggested, however, that the response threshold framework can help us understand the regulation of division of labor in social insects from a unifying perspective.

The impact of architecture on collective behaviour

Despite the obvious influence of space on interactions, constraints imposed by the built environment are seldom considered when examining collective behaviours of animals and humans. We propose an interdisciplinary path towards uncovering the impact of architecture on collective outcomes.

How social information can improve estimation accuracy in human groups

Significance Digital technologies deeply impact the way that people interact. Therefore, it is crucial to understand how social influence affects individual and collective decision-making. We performed experiments where subjects had to answer questions and then revise their opinion after knowing the average opinion of some previous participants. Moreover, unbeknownst to the subjects, we added a controlled number of virtual participants always giving the true answer, thus precisely controlling social information. Our experiments and data-driven model show how social influence can help a group of individuals collectively improve its performance and accuracy in estimation tasks depending on the quality and quantity of information provided. Our model also shows how giving slightly incorrect information could drive the group to a better performance. In our digital and connected societies, the development of social networks, online shopping, and reputation systems raises the questions of how individuals use social information and how it affects their decisions. We report experiments performed in France and Japan, in which subjects could update their estimates after having received information from other subjects. We measure and model the impact of this social information at individual and collective scales. We observe and justify that, when individuals have little prior knowledge about a quantity, the distribution of the logarithm of their estimates is close to a Cauchy distribution. We find that social influence helps the group improve its properly defined collective accuracy. We quantify the improvement of the group estimation when additional controlled and reliable information is provided, unbeknownst to the subjects. We show that subjects’ sensitivity to social influence permits us to define five robust behavioral traits and increases with the difference between personal and group estimates. We then use our data to build and calibrate a model of collective estimation to analyze the impact on the group performance of the quantity and quality of information received by individuals. The model quantitatively reproduces the distributions of estimates and the improvement of collective performance and accuracy observed in our experiments. Finally, our model predicts that providing a moderate amount of incorrect information to individuals can counterbalance the human cognitive bias to systematically underestimate quantities and thereby improve collective performance.

The role of colony size on tunnel branching morphogenesis in ant nests

Many ant species excavate nests that are made up of chambers and interconnecting tunnels. There is a general trend of an increase in nest complexity with increasing population size. This complexity reflects a higher ramification and anastomosis of tunnels that can be estimated by the meshedness coefficient of the tunnelling networks. It has long been observed that meshedness increases with colony size within and across species, but no explanation has been provided so far. Since colony size is a strong factor controlling collective digging, a high value of the meshedness could simply be a side effect of a larger number of workers. To test this hypothesis, we study the digging dynamics in different group size of ants Messor sancta. We build a model of collective digging that is calibrated from the experimental data. Models predictions successfully reproduce the topological properties of tunnelling networks observed in experiments, including the increase of the meshedness with group size. We then use the model to investigate situations in which collective digging progresses outward from a centre corresponding to the way tunnelling behaviour occurs in field conditions. Our model predicts that, when all other parameters are kept constant, an increase of the number of workers leads to a higher value of the meshedness and a transition from tree-like structures to highly meshed networks. Therefore we conclude that colony size is a key factor determining tunnelling network complexity in ant colonies.

Network-based model of the growth of termite nests

We present a model for the growth of the transportation network inside nests of the social insect subfamily Termitinae (Isoptera, termitidae). These nests consist of large chambers (nodes) connected by tunnels (edges). The model based on the empirical analysis of the real nest networks combined with pruning (edge removal, either random or weighted by betweenness centrality) and a memory effect (preferential growth from the latest added chambers) successfully predicts emergent nest properties (degree distribution, size of the largest connected component, average path lengths, backbone link ratios, and local graph redundancy). The two pruning alternatives can be associated with different genuses in the subfamily. A sensitivity analysis on the pruning and memory parameters indicates that Termitinae networks favor fast internal transportation over efficient defense strategies against ant predators. Our results provide an example of how complex network organization and efficient network properties can be generated from simple building rules based on local interactions and contribute to our understanding of the mechanisms that come into play for the formation of termite networks and of biological transportation networks in general.

Self-Organized Linear and Helicoidal Ramps in Insect Nests

The nests built by termites of the genus Apicotermes present a regular succession of floors interconnected by vertical passages. By scanning these nests with X-ray tomography we observed that two different configurations of vertical passages coexist: ramps and helices. Based on our current knowledge of the mechanisms of nest building behaviour in different groups of social insects we formulate hypotheses about the mechanisms that could lead to the formation of these structures. In particular, we show that a 3D model of nest building in Lasius niger ants (Khuong et al, 2016) is capable of producing layered structures with vertical helices similar to the structures built by Apicotermes by simply running it with parameters different from those empirically measured for ants. It is possible that similar self-organised building mechanisms underlie the construction of the different nest structures produced by different groups of social insects.

Interdisciplinary approaches for uncovering the impacts of architecture on collective behaviour

Built structures, such as animal nests or buildings that humans occupy, serve two overarching purposes: shelter and a space where individuals interact. The former has dominated much of the discussion in the literature. But, as the study of collective behaviour expands, it is time to elucidate the role of the built environment in shaping collective outcomes. Collective behaviour in social animals emerges from interactions, and collective cognition in humans emerges from communication and coordination. These collective actions have vast economic implications in human societies and critical fitness consequences in animal systems. Despite the obvious influence of space on interactions, because spatial proximity is necessary for an interaction to occur, spatial constraints are rarely considered in studies of collective behaviour or collective cognition. An interdisciplinary exchange between behavioural ecologists, evolutionary biologists, cognitive scientists, social scientists, architects and engineers can facilitate a productive exchange of ideas, methods and theory that could lead us to uncover unifying principles and novel research approaches and questions in studies of animal and human collective behaviour. This article, along with those in this theme issue aims to formalize and catalyse this interdisciplinary exchange. This article is part of the theme issue ‘Interdisciplinary approaches for uncovering the impacts of architecture on collective behaviour’.