Luca Crociani

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).

Multidestination Pedestrian Flows in Equilibrium: A Cellular Automaton-Based Approach

This article presents a new simulation approach for multidestination pedestrian crowds in complex environments. The work covers two major topics. In the first part, a novel cellular automaton CA model is proposed. The model describes the pedestrian movement by a set of simple rules and produces fundamental diagrams similar to those derived from laboratory experiments. The second topic of this work describes how the CA can be integrated into an iterative learning cycle where the individual pedestrian can adapt travel plans based on experiences from previous iterations. Depending on the setup, the overall travel behavior moves either toward a Nash equilibrium or the system optimum. The functional interaction of the CA with the iterative learning approach is demonstrated on a set of transport paradoxes. Furthermore, time series of speed and density observed in a small-scale experiment show a general agreement between the CA simulation and laboratory experiments. The scalability of the proposed approach is demonstrated on a large-scale scenario.

Multi-scale Simulation for Crowd Management: A Case Study in an Urban Scenario

Safety, security, and comfort of pedestrian crowds during large gatherings are heavily influenced by the layout of the underlying environment. This work presents a systematic agent-based simulation approach to appraise and optimize the layout of a pedestrian environment in order to maximize safety, security, and comfort. The performance of the approach is demonstrated based on annual “Salone del mobile” (Design Week) exhibition in Milan, Italy. Given the large size of the scenario, and the proportionally high number of simultaneously present pedestrians, the computational costs of a pure microscopic simulation approach would make this hardly applicable, whereas a multi-scale approach, combining simulation models of different granularity, provides a reasonable trade off between a detailed management of individual pedestrians and possibility to effectively carry out what-if analyses with different environmental configurations. The paper will introduce the scenario, the base model and the alternatives discussing the achieved results.

Heterogeneous Pedestrian Walking Speed in Discrete Simulation Models

Discrete pedestrian simulation models are viable alternatives to particle based models, employing a continuous spatial representation and they are able to reproduce realistic pedestrian dynamics from the point of view of a number of observable properties. The effects of discretisation, however, also imply difficulties in modelling some phenomena that can be observed in reality. This paper presents a discrete model extending the floor field approach allowing heterogeneity in the walking speed of the simulated population of pedestrians. Whereas some discrete models allow pedestrians to move more than a single cell per time step, in the present work we maintain a maximum speed of one cell per step but we model lower speeds by having pedestrians yielding their movement in some turns. Different classes of pedestrians are associated to different desired walking speeds and we define a stochastic mechanism ensuring that they maintain an average speed close to this threshold.

When reactive agents are not enough: Tactical level decisions in pedestrian simulation

Pedestrian and crowd simulation is generally focused on operational level decisions, providing the choice of exact steps of pedestrians in a representation of the environment, with the aim of replicating observed patterns of space utilization, trajectories and timings. When relatively large environments are considered, though, tactical level decisions become equally important: in general, multiple paths can be followed to reach a target from an entrance or starting point, and path length might not be the only reasonable criterion. This paper presents a hybrid agent architecture for modeling different types of decisions in a pedestrian simulation system, encompassing a floor-field based operational level (based on a “least effort” principle) and an adaptive tactical level component, provided with a graph-like representation of the envornment, considering both perceived congestion and characteristics of potential paths in the related decision. The model is experimented and evaluated both qualitatively and quantitatively in benchmark scenarios to show its adequacy and expressiveness.

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 Model of Pedestrian Dynamics Considering Groups: A Real World Case Study

Groups have a significant influence of pedestrian dynamics: members of groups, in fact, carry out of a form of interaction (by means of verbal or non-verbal communication) that allows them to preserve cohesion even in particular conditions, such as counter flows, presence of obstacles or narrow passages. The paper describes an agent-based model for the simulation of crowds of pedestrians whose main innovative element is the representation and management of groups in the simulated population. The paper briefly describes the model and then it presents its application to a real world scenario in which an analysis of the impact of groups on the overall observed system dynamics was performed.

An Integrated Model for the Simulation of Pedestrian Crossings

The present paper represents an approach to the modeling of pedestrians and vehicles interaction in the area of a zebra crossing, either signalised or not, employing two existing models devoted to the simulation of the specific pedestrian and vehicular sub-systems and integrating them in a comprehensive agent environment. The latter acts as a bridge allowing mutual perception of the different heterogeneous agents that cooperate to avoid accidents: vehicles give way to perceived pedestrians whenever they can safely brake to let them pass, pedestrians yield whenever they perceive cars that would not be able to stop before the zebra crossing. The paper presents the model and shows results in simple crossing scenarios.

Route choice in pedestrian simulation: Design and evaluation of a model based on empirical observations

Several issues in transferring AI results in crowd modeling and simulation are due to the fact that control applications are aimed achieving optimal solutions, whereas simulations have to deal with the notions of plausibility and validity. The latter requires empirical evidences that, for some specific phenomena, are still scarce and hard to acquire. To face this issue, the present work presents an investigation on the route choice decisions of pedestrians, by producing empirical evidences with an experiment executed in a controlled setting. The experiment involves human participants facing a relatively simple choice among different paths (i.e. choose one of two available gateways leading to the same target area) in which, however, they face a trade-off situation between length of the trajectory to be covered and estimated travel time, considering the level of congestion in the different paths. The data achieved with the experiment are used to design and evaluate a general simulation model for pedestrian route choice. The proposed model firstly considers the fact that other pedestrians are generally perceived as repulsive and that choice of route is generally aimed at avoiding congestion (as for proxemics theory). On the other hand, we also introduce an additional mechanism due to the conjecture that the decision of a pedestrian to reconsider the adopted path is a locally perceivable event that is able to trigger a similar reconsideration by nearby pedestrians, that can imitate the former one. The model is experimented and evaluated in the experiment scenario, for calibration and validation, as well as in a larger scale environment, for exploring the implications of the modeling choices in a more complex situation.

Pedestrian Simulation: Considering Elderlies in the Models and in the Simulation Results

This paper presents improvements to the computational model of MakkSim aimed at allowing the simulation of aged people and persons with mobility impairments. In particular, a method for modelling heterogeneity in speed is discussed and two special objects of the environment (i.e., stairs and seats), have been defined; in addition, a proposal for modelling the presence of a caretaker is described as a particular type of group of pedestrians. Finally, the paper presents a way of computing social costs implied by the environment taking into account the characteristics of pedestrians moving throughout the related facilities. The overall objective is to achieve a system usable for the evaluation of the usability and accessibility of planned environments and facilities by means of simulation, by also taking into account this category of people.