Studies related to crowds of pedestrians, both those of theoretical nature and application oriented ones, have generally focused on either the analysis or the synthesis of the phenomena related to the interplay between individual pedestrians, each characterised by goals, preferences and potentially relevant relationships with others, and the environment in which they are situated. The cases in which these activities have been systematically integrated for a mutual benefit are still very few compared to the corpus of crowd related literature. This paper presents a case study of an integrated approach to the definition of an innovative model for pedestrian and crowd simulation (on the side of synthesis) that was actually motivated and supported by the analyses of empirical data acquired from both experimental settings and observations in real world scenarios. In particular, we will introduce a model for the adaptive behaviour of pedestrians that are also members of groups, that strive to maintain their cohesion even in difficult (e.g. high density) situations. The paper will show how the synthesis phase also provided inputs to the analysis of empirical data, in a virtuous circle.
This paper presents a model to simulate unsignalized pedestrian crosswalks. Principal scope of the model is to develop a tool to be used by decision-makers to evaluate the necessity of introducing a new crosswalk and/or switching to a traffic light and estimate the potential benefits of such a measure in term of Level of Service. The model is based on empirical evidence gained during an observation of an unsignalized crosswalk in Milan. Pedestrian motion is simulated using a simple Cellular Automata model in which only static floor field is implemented. Vehicles use a continuous car following model inspired on Gipps equations in which driver's reaction time is considered. Pedestrian's decision-making process on crossing attempt and model parameters are directly obtained from the analysis of pedestrian-vehicle interactions observed in reality. The model developed employs small time steps, thus allowing the consideration of different pedestrian speeds (intrinsically allowing to consider elderly) and smoothly reproducing car-pedestrian interactions. In order to validate the model, delays (or waiting times) measured for both pedestrians and drivers were compared with simulated values. Results show a good agreement between empirically obtained time delay and values computed in the simulation.
The development of pedestrian simulation systems requires the acquisition of empirical evidences about human behaviour for sake of model validation. In this framework, the paper presents the results of an on field observation of pedestrian behaviour in an urban crowded walkway. The research was aimed at testing the potentially combined effect of ageing and grouping on speed and proxemic behaviour. In particular, we focused on dyads, as the most frequent type of groups in the observed scenario. Results showed that in situation of irregular flows elderly pedestrians walked the 40% slower than adults, due to locomotion skill decline. Dyads walked the 30% slower than singles, due to the need to maintain spatial cohesion to communicate (proxemics). Results contributed to refine the parametric validation of the agent-based simulation system ELIAS38.
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