The soldier crab, technically known as Mictyris guinotae, is a cute (not a technical definition here...) species of crab found in tropical regions, including Australia, South East Asia, and a few islands in the southern part of Japan. This particular type of crab is intriguing for several reasons. It moves in a straight line, unlike most crabs that have lateral movement. It forms large swarms consisting of thousands of individuals. Most importantly, unlike bees or other social animals, it exhibits straightforward social behaviors, primarily focused on eating, seeking shelter in times of danger, and reproducing during winter. This simplicity makes it an excellent subject for studying fundamental aspects of collective behavior.

In my research, I am attempting to investigate how light can influence the overall dynamics of these crab swarms, particularly whether light can be employed to "synchronize" the movements of soldier crabs. I designed a specialized device, aptly named the "crabs disco," featuring a circular track and a rotating light used to guide the crabs in a specific direction (clockwise or counterclockwise). To gain a better understanding of swarm dynamics and test various hypotheses related to their behavior, I also developed a Cellular Automata model that replicates swarm dynamics.

In the initial phase of the research, I am exploring how synchronization occurs by varying swarm density (3, 10, 30 crabs). In a second part, I am investigating whether an already synchronized swarm can be reversed by changing the direction of the light source. Results have revealed that under low densities, there is no discernible collective organization, rendering light virtually ineffective. At high densities, collective behavior naturally emerges even without external intervention. However, at medium densities, it is possible to reasonably control the swarm: crabs initially move in the same direction as the light and change their walking direction when the light's direction is reversed. This demonstrates the importance of maintaining a balance between "social" density (ability to engage in interactions) and "physical" density when studying animal swarms.

One of the most interesting aspects of soldier crabs is that their swarms are not isolated, like those of birds or fish. Instead, several swarms merge and split within a short time, creating a dynamic that is quite peculiar in the animal kingdom. The shifting nature of these swarms produces highly diverse conditions on land, with some areas densely packed with thousands of crabs while others remain sparsely occupied.

During routine observations aimed at better understanding soldier crab behavior during low tides, we noticed by chance that crabs perceive large buses as a threat and exhibit anti-predatory reactions to protect themselves. What is particularly intriguing is that this behavior changes depending on the density of the swarm. In sparse swarms, crabs tend to dig into the sand, which is their standard strategy to evade potential predators. However, in very dense swarms, the reaction is barely noticeable and generally does not result in burrowing, indicating that the crabs do not take evasive measures.

This behavior is puzzling from a biological perspective and relevant to the study of swarm robotics. In biology, it is generally expected that animals in groups react more quickly and accurately to threats than isolated individuals, consistent with the “many-eyes” hypothesis. What we observed in soldier crabs, however, is quite different. From the perspective of swarm robotics, this behavior is also significant because the ability of soldier crabs to adapt to local conditions could inspire algorithms for swarm robotic systems.

Research on this subject is still ongoing, with only a limited number of publications available. If you would like to know more, please feel free to contact me.

Pedestrian and vehicular traffic are typically segregated into areas accessible only to pedestrians and those accessible solely to cars. Pedestrians walk on the sidewalk, while cars move on the road. Unsignalized crosswalks represent one of the few points where cars and pedestrians interact. Unlike signalized crosswalks, where traffic lights coordinate the movements of both cars and pedestrians, preventing collisions, in unsignalized crosswalks, pedestrian safety relies on the successful negotiation of road crossing when individuals attempt to traverse.

Accidents can easily occur due to misunderstandings or distractions, with pedestrians typically being the victims. Therefore, it is essential to comprehend the decision-making process when people attempt to cross the road and identify the most relevant variables affecting traffic volumes for both road users.

In the course of this research, conducted in collaboration with the University of Milano-Bicocca, I utilized results from on-field observations to develop a simulation model that replicates the dynamics of pedestrians and drivers in unsignalized crosswalks.

The model has been validated using experimental data, demonstrating its capability to accurately estimate waiting times caused by the presence of the crosswalk for both pedestrians and drivers. Such a model can be applied, for instance, to determine whether installing a traffic light would reduce waiting times or if an unsignalized crosswalk is appropriate.

In a subsequent study, I also examined pedestrian safety to assess which policies are more effective in reducing the severity and number of collisions between pedestrians and vehicles. Our research indicated that while enforcing speed limits clearly helps reduce pedestrian fatalities, alternative "soft" solutions like implementing "shared spaces" can also be effective. Additionally, we emphasized the importance of conducting safety campaigns targeting drivers and raising pedestrians' awareness of potential risks.

In a collaborative research, I further investigated cognitive and environmental aspects related to unsignalized crosswalks, utilizing Virtual Reality and a self-developed driving simulator.

As part of my research on unsignalized crosswalks, we (the project was clearly a joint effort) wanted to test how the surrounding environment can influence the behavior of drivers. Small problem: at that time (and partially still now), the budget for the research was quite limited, so we had to come up with simple solutions to build a driving simulator and check how drivers’ behavior would change in different environmental settings. Together with Luca Crociani and Andrea Gorrini in Italy, we developed a very cheap driving simulator using the cheapest (or almost the cheapest) components one could find on the market. The result was the VR driving simulator you see here on the right.

After building the simulator, the next question that came up was whether such a simple simulator could be enough to study driver behavior. Our tests showed that, at least for very simple scenarios and if only simple measures are sought, such an approach could be sufficient. We were able to detect some typical differences in driving behavior between young and elderly participants by both measuring their driving speed and their attitude toward risk-taking. The only (big) problem was that due to the use of cheap components, the driving experience was quite poor, with most people becoming sick during the tests.

A few years later, new people joined the project (Akihito Nagahama and Geng Cui), and we enjoyed better funding. That was the time to redevelop the driving simulator using better equipment: a better VR headset, a better wheel with force feedback, and a PC capable of handling 3D graphics smoothly. The result was a much better driving simulator, which allowed us to test longer scenarios and achieve the initial goal of checking how the surrounding environment affects driving behavior.

The result? The “broken window theory” was found to apply to traffic safety as well. Driving in a flawless, “perfect” environment made people more risk-aware, and drivers would start slowing down well before approaching the crosswalk. But when people were driving in a dirty and noisy environment, their approach became more aggressive, with higher speeds and stopping (too) close to the crosswalk.

I am clearly not an anthropologist, nor do I pretend to be one, out of respect for those researchers who do serious work in this field. However, having spent almost half of my life abroad or in linguistic regions different from where I was raised, I am indeed interested in cultures. Isn’t it intriguing how people can shape the environment to fit their culture, and how, conversely, the environment shapes culture? Or how culture can simply emerge from the interactions between people, depending on the characteristics of those who lived in a region many generations ago?

Of course, I am not the person to answer these questions, and I wouldn’t even attempt to. Still, I find them fascinating. So, whenever I had the chance to study cultures within the framework of my research on crowds and related subjects, I engaged with enthusiasm. I was fortunate to meet people with similar interests and to get involved in various projects that considered aspects of cross-cultural comparison.

In one project (right image), with colleagues from Australia, China, Germany, Japan (myself), and Palestine, we studied whether cultural background could influence the fundamental movement patterns of people. The results were quite clear: there were no significant differences among the countries surveyed. Of course, cultural differences do exist when people move in groups, but these are only noticeable when social interactions occur, not in simple scenarios like walking in a line.

In a separate project, proudly an all-female team except for me—we studied how people from different countries perceive crowd accidents and their representations. We covered Germany, Japan, South Korea, and the UK, and found that the results varied only slightly across countries.

In another study, conducted with colleagues from urban studies, we investigated changes in mood during COVID-19 in different countries. Here, some differences did emerge, suggesting that when emotions are considered within a social context, the environment (i.e., culture) does play a role to some extent.

In this research, conducted in collaboration with various partners, I am endeavoring to comprehend how population density can influence people's lives and what kind of connections exist between the "crude" measure of people per square kilometer and the actual perceptions of individuals.

On one side, I have been collaborating with Alice Pacher (an expert in sexuality) and Andrea Gorrini (an environmental psychologist) to explore whether population density, or more broadly, the living environment, can impact human sexuality and in what ways. We found that housing environment has minimal influence on our sexual lives, regardless of the cultural context. However, working environment played a significant role in Western countries, such as Germany and Italy. Specifically, individuals who found their work meaningful were more likely to have an active sexual life. In Japan, social life took on greater importance, with the so-called "third place" playing a notable role in sexuality.

On the other hand, I am collaborating with architects and urban planners, namely Karri Flinkman and Hideki Kozumi, to investigate whether population density, expressed as people per square kilometer, can effectively measure perceptual aspects related to everyday life. We are also exploring how individuals from diverse cultures perceive different environments, such as the countryside and metropolis, for example.

Prior to embarking on my research concerning pedestrian crowds, I was engaged in various research projects across different disciplines, primarily focusing on fluid dynamics.

As an undergraduate student, I delved into the generation of turbulence within a jet stream by conducting laboratory experiments. I investigated high-speed jet streams using Particle Image Velocimetry (PIV) to explore the feasibility of employing this technique to study turbulence.

As a graduate student in nuclear engineering, I designed a device for gas mixing that facilitated the measurement of radioactive Xenon (Xe) using gas mass microscopy. This device allowed for the controlled dilution of radioactive gas with a precisely known dilution ratio, subsequently enabling its analysis with highly sensitive specialized equipment.

During my tenure as an R&D engineer in the field of polymer science, I developed a computational method for determining the thermal conductivity of fiber-reinforced polymers through simulation. We submitted a patent related to this innovative method. Throughout my engineering experience, I had the opportunity to utilize various commercial software applications in fluid dynamics, including the simulation of phenomena like falling ice using Flow3D (view a movie here).

Throughout my educational and research endeavors, I also had the privilege of working with several codes related to fluid dynamics, spanning various disciplines, including reactive polymers and tsunami propagation (view a movie here).

While employed at a small company in Switzerland (MAIN Gmbh), I additionally created software to simulate the dynamics of a twin-roll casting plant and estimate Return on Investment (ROI) based on various factors, including electricity and gas costs and invested capital (see screenshot).