1,721,030 research outputs found
Multiscale probabilistic evaluation of the footbridge crowding. Part 2: Crossing Pedestrian position
Full text link\u3cp\u3eIn the previous Part of this study, an attempt to estimate the c.o.v. of the pedestrian density approaching a footbridge has been made. In analogy to wind engineering, where statistics on the incoming wind are complemented with the description of the flow around the obstacle to provide the aerodynamic forces on the structure, the obtained result is not conclusive. In pedestrian dynamics, the density along the footbridge cannot be confused with the incoming one if the pedestrian dynamics is affected by the walkway features (side barriers, walkway geometry, obstacles). On the other hand, differently from fluid dynamics, pedestrian motion is a multiscale phenomenon, which can be described both at the macroscopic scale (continuous medium) and at the microscopic scale (granular medium). The pedestrian density described in Part I can be ascribed to the former. Conversely, the uncertain location (in space and time) of each pedestrian at the entrance of the footbridge must be sampled and treated at the microscopic scale. Such uncertainty on positions further propagates spanwise along the walkway, being transported by pedestrians themselves. Evidences of this are available in literature based either on in-situ observations or on lab experiments. In this part of the study, the span-wise propagation of the uncertainty generated by the incoming pedestrian density is studied in the framework of the Monte Carlo method. In particular, a statistical analysis of repeated microscopic simulations of a first order crowd model accounting for body size is performed. Inlet conditions are prescribed on the basis of the statistics of the crowd density (described in part I), by assigning probability laws to the pedestrian chord-wise inlet positions and to the inter-arrival times. The final goal of the model is to estimate the propagation of the incoming variability along the footbridge. The application of the model to an ideal footbridge is provided.\u3c/p\u3
RSSi-based visitor tracking in museums via cascaded AI classifiers and coloured graph representations
Full text linkIndividual tracking of museum visitors based on portable radio beacons, an asset for behavioural analyses and comfort/performance improvements, is seeing increasing diffusion. Conceptually, this approach enables room-level localisation based on a network of small antennas (thus, without invasive modification of the existent structures). The antennas measure the intensity (RSSi) of self-advertising signals broadcasted by beacons individually assigned to the visitors. The signal intensity provides a proxy for the distance to the antennas and thus indicative positioning. However, RSSi signals are well-known to be noisy, even in ideal conditions (high antenna density, absence of obstacles, absence of crowd, ...). In this contribution, we present a method to perform accurate RSSi-based visitor tracking when the density of antennas is relatively low, e.g. due to technical constraints imposed by historic buildings. We combine an ensemble of "simple" localisers, trained based on ground-truth, with an encoding of the museum topology in terms of a total-coloured graph. This turns the localisation problem into a cascade process, from large to small scales, in space and in time. Our use case is visitors tracking in Galleria Borghese, Rome (Italy), for which our method manages >96% localisation accuracy, significantly improving on our previous work (J. Comput. Sci. 101357, 2021)
Multiscale probabilistic evaluation of the footbridge crowding. Part 1: Incoming Pedestrian density
No full textThe issue of human-induced load and related mechanical performance has become one of the leading research topics in structural dynamics during the last decade. Although the concept of variability and uncertainty is well developed in structural dynamics disciplines such as wind, wave and earthquake engineering, most of the human-induced force models developed so far in structural engineering are deterministic, despite the intrinsic randomness of the crowd behaviour. The probabilistic models proposed in the last years have recognized two main sources of uncertainties, namely the structural system and the human-induced force. The pedestrian-related random variables usually considered in the cited force models are walking frequency, step length, free walking speed, single pedestrian force magnitude and body weight. According to the authors, another source of uncertainty should be considered, namely the one associated to the pedestrian traffic approaching and crossing the footbridge. This may find an analogy to what is usually done in wind engineering, where uncertainties related to the incoming wind are due to the inborn variability of the latter. Pedestrian traffic uncertainty is expected to deeply affect the crowd load on the structure: the magnitude of the overall force depends on the number of incoming pedestrians, while the load spatial distribution follows from the position of each pedestrian at the footbridge entrance and subsequently along the walkway. Coherently, in this study, the uncertainty evaluation includes the description of the undisturbed incoming traffic in terms of pedestrian density and hence introduces the variability of each pedestrian position. A two parts paper follows. The current one proposes a general procedure to collect in-situ data about the incoming crowd density and extract statistics. As such measurements are currently missing, a first attempt to obtain such statistics from data available in literature is proposed. The coefficient of variation of the incoming density is obtained and compared with the one of other pedestrian-related random variables
Modeling Routing Choices in Unidirectional Pedestrian Flows
Full text linkIn this work we present a simple routing model capable of capturing pedestrians path choices in the presence of a herding effect. The model is tested and validated against data from a large scale tracking campaign which we have conducted during the GLOW 2019 festival. The choice between alternative paths is modeled as an individual cost minimization procedure, with the cost function being associated to the (estimated) traveling time. In order to trigger herding effects the cost function is supplemented with a penalty term, modulated as a function of the fraction of pedestrians walking along each route. The model is shown to provide an accurate quantitative description of the decision process
Pedestrian-structure interaction in the vertical direction: coupled model and application to lively footbridges
No full textModelling framework of pedestrian-footbridge interaction in vertical direction
Full text linkThis study presents a modelling framework of human-structure interaction in the vertical direction, which integrates the three following key issues: crowd dynamics, pedestrian-structure interaction (PSI) and inter-subject and intra-subject variability of pedestrian walking loads. The framework comprises two main models: a microscopic model of crowd dynamics and a coupled dynamic model of the PSI. The latter is composed of three sub-models: a SDOF system having the dynamic properties of the empty structure, a SDOF system for each pedestrian and a stochastic force model. Each pedestrian SDOF moves along the footbridge following the trajectory and at the velocity simulated by the crowd model and is accompanied by a stochastic walking force time-history that accounts for inter- and intra-subject variability. Performance of the suggested modelling framework is studied through simulations of the vibration responses of four virtual footbridges due to different traffic scenarios
Pedestrian-structure interaction in the vertical direction: Coupled oscillator-force model for vibration serviceability assessment
No full textDespite a lot of effort has gone into research on human-induced vibrations of footbridges in the last decade, there is still a lack of reliable models and adequate design guideline pertinent to dynamic loading due to multiple pedestrians. There are three key issues that a new generation of models should urgently address: (i) interaction between pedestrians and the structure they occupy and dynamically excite; (ii) pedestrian intelligent behaviour; (iii) inter-subject and intra-subject variability of pedestrian walking loads. This paper presents a model of pedestrian-structure dynamic interaction in the vertical direction which addresses the first two issues. The model comprises three sub-models: (1) a model of a footbridge featuring a SDOF system having the dynamic properties of an empty structure, (2) a microscopic model of multiple pedestrian traffic that simulates position and velocity of each individual pedestrian in space and time, and (3) a model of individual pedestrian actuator featuring a periodic force model coupled with a spring-mass-damper oscillator which move together along the structure. The proposed model is applied to a lively footbridge with known modal properties and results are compared to the measured vibration response due to a light pedestrian traffic
Multiscale Crowd Dynamics: Physical Analysis, Modeling and Applications
Full text linkIn this thesis we investigate the dynamics of pedestrian crowds in a fundamental and applied perspective. Envisioning a quantitative understanding we employ ad hoc large-scale experimental measurements as well as analytic and numerical models. Moreover, we analyze current regulations in matter of pedestrians structural actions (structural loads), in view of the need of guaranteeing pedestrian safety in serviceable built environments. This work comes in three complementary parts, in which we adopt distinct perspectives and conceptually different tools, respectively from statistical physics, mathematical modeling and structural engineering. Chapter 1 introduces these perspectives and gives an outline of the thesis. The statistical dynamics of individual pedestrians is the subject of Part I. Although individual trajectories may appear random, once we analyze them in large ensembles we expect ``preferred'' behaviors to emerge. Thus, we envisage individual paths as fluctuations around such established routes. To investigate this aspect, we perform year-long 24/7 measurements of pedestrian trajectories in real-life conditions, which we analyze statistically and via Langevin-like models. Two measurement locations have been considered: a corridor-shaped landing in the Metaforum building at Eindhoven University of Technology and the main walkway within Eindhoven Train Station. The measurement technique we employ, based on overhead Microsoft \Kinect\ 3D-range sensors and on ad hoc tracking algorithms, is introduced in Chapter 2. In Chapter 3 we describe the low density pedestrian flows in the Metaforum landing. In this location hundreds of thousands of high-resolution trajectories have been collected. First, we discuss standard crowd-traffic descriptions based on average quantities such as fundamental diagrams. Then, thanks to our large dataset, we address the dynamics beyond average values via probability distributions of pedestrian positions and velocities. Chapter 4 focuses on the dynamics of pedestrians crossing the landing alone, i.e. undisturbed by peers. The simple crossing dynamics is affected by stochastic fluctuations due to the variability of individuals' behavior as well as external factors. In the chapter we propose a quantitative Langevin-like model for these stochastic fluctuations, that we compare with the experimental data in terms of stationary velocity distributions and time correlation functions. The avoidance regime which takes place when two pedestrians walk simultaneously in the landing and in opposite directions is addressed in Chapter 5. In this regime, the statistical features of pedestrian motion change from the undisturbed case (Chapter 4). Here, we study the avoidance dynamics as a linear superposition of the undisturbed motion and an interaction force. First, we estimate average interaction force fields from the data. Then, we extend the Langevin model of Chapter 4 to reproduce statistics of the pair-wise interactions. Finally, in Chapter 6, we discuss in brief the measurements collected at Eindhoven Train Station in view of future dense crowd analyses. In Part II we zoom out from the perspective of individual pedestrians and we look at crowds, adopting a genuine mathematical modeling point of view. In this context a microscopic, i.e. particle-like, or a macroscopic, i.e. fluid-like, observation scale can be employed. In Chapter 7, we establish a general background of crowd dynamics modeling, which includes an introduction of the modeling framework by Cristiani, Piccoli and Tosin (CPT framework, in use in Chapters 8,9,11 and 12. This framework is suitable to model systems governed by social interactions and stands on a first order measure-valued evolution equation. The use of measures is crucial in the following, as it enables a unified treatment of crowd flows at the microscopic and macroscopic scales. Chapter 8 comprises a co
From individual behaviour to an evaluation of the collective evolution of crowds along footbridges
Full text linkThis paper proposes a crowd dynamic macroscopic model grounded on microscopic phenomenological observations which are upscaled by means of a formal mathematical procedure. The actual applicability of the model to real-world problems is tested by considering the pedestrian traffic along footbridges, of interest for Structural and Transportation Engineering. The genuinely macroscopic quantitative description of the crowd flow directly matches the engineering need of bulk results. However, three issues beyond the sole modelling are of primary importance: the pedestrian inflow conditions, the numerical approximation of the equations for non trivial footbridge geometries and the calibration of the free parameters of the model on the basis of in situ measurements currently available. These issues are discussed, and a solution strategy is proposed
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