Lorenza Manenti

Adaptive pedestrian behaviour for the preservation of group cohesion

PurposeA crowd of pedestrians is a complex system in which individuals exhibit conflicting behavioural mechanisms leading to self-organisation phenomena. Computer models for the simulation of crowds represent a consolidated type of application, employed on a day-to-day basis to support designers and decision makers. Most state of the art models, however, generally do not consider the explicit representation of pedestrians aggregations (groups) and their implications on the overall system dynamics. This work is aimed at discussing a research effort systematically exploring the potential implication of the presence of groups of pedestrians in different situations (e.g. changing density, spatial configurations of the environment).MethodsThe paper describes an agent-based model encompassing both traditional individual motivations (i.e. tendency to stay away from other pedestrians while moving towards the goal) and an adaptive mechanism representing the influence of group presence in the simulated population. The mechanism is designed to preserve the cohesion of specific types of groups (e.g. families and friends) even in high density and turbulent situations. The model is tested in simplified scenarios to evaluate the implications of modelling choices and the presence of groups.ResultsThe model produces results in tune with available evidences from the literature, both from the perspective of pedestrian flows and space utilisation, in scenarios not comprising groups; when groups are present, the model is able to preserve their cohesion even in challenging situations (i.e. high density, presence of a counterflow), and it produces interesting results in high density situations that call for further observations and experiments to gather empirical data.ConclusionsThe introduced adaptive model for group cohesion is effective in qualitatively reproducing group related phenomena and it stimulates further research efforts aimed at gathering empirical evidences, on one hand, and modelling efforts aimed at reproducing additional related phenomena (e.g. leader-follower movement patterns).

Data Collection for Modeling and Simulation: Case Study at the University of Milan-Bicocca

The investigation of crowd dynamics is a complex field of study that involves different types of knowledge and skills, and, also from the socio-psychological perspective, the definition of crowd is still controversial. We propose to investigate analytically this phenomenon focusing on pedestrian dynamics in medium-high density situations, and, in particular, on proxemic behavior of walking groups. In this work we will present several results collected during the observation of the incoming pedestrian flows to an admission test at the University of Milano-Bicocca. In particular, we collected empirical data about: levels of density and of service, group spatial arrangement (degree of alignment and cohesion), group size and composition (gender), walking speed and lane formation. The statistical analysis of video footages of the event showed that a large majority of the incoming flow was composed of groups and that groups size significantly affects walking speed. Collected data will be used for an investigative modeling work aimed at simulating the observed crowd and pedestrian dynamics.

An Agent-Based Pedestrian and Group Dynamics Model Applied to Experimental and Real-World Scenarios

Pedestrian simulation is a consolidated area of application in which agent-based models are often employed; successful case studies are described in the literature and commercial, off-the-shelf simulators are commonly employed by decision makers and consultancy companies. Most state-of-the-art models, however, generally do not consider the explicit representation of pedestrians aggregations (groups) and their implications on the overall system dynamics. This work is aimed at discussing the relevance and significance of this research effort with respect to the need of empirical data about the implication of the presence of groups of pedestrians in different situations (e.g., changing density, spatial configurations of the environment). The article describes an agent-based model encompassing both traditional individual motivations (i.e., tendency to stay away from other pedestrians while moving toward the goal) and a simplified mechanism considering the cohesion effects related to the presence of groups in the crowd. The model is tested in a simple scenario to evaluate the implications of some modeling choices and the presence of groups in the simulated scenario. Moreover, the model is applied in a real-world scenario characterized by the presence of organized groups as an instrument for crowd management. Results are discussed and compared to experimental observations and to data available in the literature.

MAKKSim: MAS-Based Crowd Simulations for Designer’s Decision Support

This paper presents MAKKSim, a pedestrian dynamics simulator based on a computational discrete model in which pedestrians are represented as utility-based agents. The computational model and the system architecture are discussed, focusing on the development of the tool and on its application in a real-word case study, for the comparison and the evaluation of different strategies of crowd management and of different structural changes on the geometry of the environment.

An agent-based proxemic model for pedestrian and group dynamics: motivations and first experiments

The simulation of pedestrian dynamics is a consolidated area of application for agent-based models: successful case studies can be found in the literature and off-the-shelf simulators are commonly employed by end-users, decision makers and consultancy companies. These models, however, generally neglect or treat in a simplistic way aspects like (i) the impact of cultural heterogeneity among individuals and (ii) the effects of the presence of groups and particular relationships among pedestrians. This work is aimed, on one hand, at introducing some fundamental anthropological considerations on which most pedestrian models are based, and in particular Edward T. Halls work on proxemics. On the other hand, the paper describes an agent-based model encapsulating in the pedestrians behavioural model effects representing both proxemics and a simplified account of influences related to the presence of groups in the crowd. The model is tested in a simple scenario to evaluate the implications of some modeling choices and the presence of groups in the simulated scenario. Results are discussed and compared to experimental observations and to data available in the literature.Models for the simulation of pedestrian dynamics and crowds of pedestrians have already been successfully applied to several scenarios and case studies, off-the-shelf simulators can be found on the market and they are commonly employed by end-user and consultancy companies. However, these models are the result of a first generation of research efforts considering individuals, their interactions with the environment and among themselves, but generally neglecting aspects like (a) the impact of cultural heterogeneity among individuals and (b) the effects of the presence of groups and particular relationships among pedestrians. This work is aimed, on one hand, at clarifying some fundamental anthropological considerations on which most pedestrian models are based, and in particular Edward T. Hall’s work on proxemics. On the other hand, the paper will briefly describe the first steps towards the definition of an agentbased model encapsulating in the pedestrian’s behavioural model effects capturing both proxemics and influences due to potential presence of groups in the crowd.

A Knowledge-based Approach to Crowd Classification

This paper illustrates a formal tool for knowledge representation and management in the crowding area, in order to improve on the sharing of knowledge, data and information produced by different models and simulation tools. The presented approach exploits knowledge-based methods for acquisition and representation phases.

An Innovative Scenario for Pedestrian Data Collection: The Observation of an Admission Test at the University of Milano-Bicocca

The investigation of crowd dynamics is a complex field of study that involves different types of knowledge and skills. Due to the difficulty in reaching an exhaustive definition of the notion of crowd, we propose to analytically investigate this phenomenon focusing on pedestrian dynamics in medium-high density situations, and, in particular, on proxemic behavior of walking groups. In this work we will present several results collected during the observation of the incoming pedestrian flows to an admission test at the University of Milano-Bicocca. In particular, we collected empirical data about: level of density and service, spatial arrangement, composition (size, gender) and walking speed of groups. The analysis of video footages of the event showed that unexpectedly a large majority of the incoming flow was composed of groups, and that group size significantly affects walking speed.

Metadata support to retrieve and revise solutions in case-based reasoning

Case Based Reasoning (CBR) is a knowledge management approach that consists of the development of decision-support systems where problems are solved by analogy with similar problems solved in the past. In this way, the system supports users in finding solutions without starting from scratch. CBR has become a very important research topic in artificial intelligence, with the definition of methodologies and architectural patterns for supporting developers in the design and implementation of case-based systems. This paper presents one of these frameworks, namely CRePERIE, an on-going research project based on the integration between CBR paradigm and metadata approach to obtain domain-independent case structure and retrieval algorithm definition. The paper focuses on how the developed retrieval strategy can be profitably exploited for the CBR revision step too, according to a substitutional approach.

Generation of Pedestrian Groups Distributions with Probabilistic Cellular Automata

The aim of this work is to present a model based on a Stochastic Cellular Automata to generate granulometric distribution of pedestrian groups in structured spaces. The main goal of this model is to set initial configurations for pedestrian simulations starting from plausible scenarios that consider the presence of groups within a crowd.

An Agent-Based Proxemic Model for Pedestrian and Group Dynamics: Motivations and First Experiments

The simulation of pedestrian dynamics is a consolidated area of application for agent-based models: successful case studies can be found in the literature and off-the-shelf simulators are commonly employed by end-users, decision makers and consultancy companies. These models, however, generally neglect or treat in a simplistic way aspects like (i) the impact of cultural heterogeneity among individuals and (ii) the effects of the presence of groups and particular relationships among pedestrians. This work is aimed, on one hand, at introducing some fundamental anthropological considerations on which most pedestrian models are based, and in particular Edward T. Halls work on proxemics. On the other hand, the paper describes an agent-based model encapsulating in the pedestrians behavioural model effects representing both proxemics and a simplified account of influences related to the presence of groups in the crowd. The model is tested in a simple scenario to evaluate the implications of some modeling choices and the presence of groups in the simulated scenario. Results are discussed and compared to experimental observations and to data available in the literature.Models for the simulation of pedestrian dynamics and crowds of pedestrians have already been successfully applied to several scenarios and case studies, off-the-shelf simulators can be found on the market and they are commonly employed by end-user and consultancy companies. However, these models are the result of a first generation of research efforts considering individuals, their interactions with the environment and among themselves, but generally neglecting aspects like (a) the impact of cultural heterogeneity among individuals and (b) the effects of the presence of groups and particular relationships among pedestrians. This work is aimed, on one hand, at clarifying some fundamental anthropological considerations on which most pedestrian models are based, and in particular Edward T. Hall’s work on proxemics. On the other hand, the paper will briefly describe the first steps towards the definition of an agentbased model encapsulating in the pedestrian’s behavioural model effects capturing both proxemics and influences due to potential presence of groups in the crowd.