Modelling negative interactions among pedestrians in high density situations

Bandini, Stefania; Mondini, Matteo; Vizzari, Giuseppe

doi:10.1016/j.trc.2013.12.007

Cited by 75 publications

(37 citation statements)

References 31 publications

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“…These two works are considered the seminal references for CA applied to pedestrian dynamics. Other examples of adaptation of CA models for studying uni and bi-directional pedestrian flow can be found in the works by Meyer-König et al [2001], and Bandini et al [2014]. The evacuation problem has been extensively studied with this model in different scenarios: in buildings [Yang et al 2005], with obstacles [Varas et al 2007] or inside corridors [Yu and Song 2007].…”

Section: Cellular Automata Modelsmentioning

confidence: 99%

Modeling, Evaluation, and Scale on Artificial Pedestrians

et al. 2017

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Modeling pedestrian dynamics and their implementation in a computer are challenging and important issues in the knowledge areas of transportation and computer simulation. The aim of this paper is to provide a bibliographic outlook so that the reader could have a quick access to the most relevant works related with this problem. We have used three main axes to organise the paper contents: pedestrian models, validation techniques and multiscale approaches. The backbone of the paper is the classification of existing pedestrian models; we have organised the works in the literature under five categories, according to the techniques used for implementing the operational level in each pedestrian model. Then, the main existing validation methods, oriented to evaluate the behavioural quality of the simulation systems, are reviewed. Furthermore, we review the key issues that arise when facing multiscale pedestrian modeling, where we firstly focus on the behavioural scale (combinations of micro and macro pedestrian models) and secondly, on the scale size (from individuals to crowds). The paper begins introducing the main characteristics of walking dynamics and its analysis tools and concludes with a discussion about the contributions that different knowledge fields can do in a near future to this exciting area.

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Section: Cellular Automata Modelsmentioning

confidence: 99%

Modeling, Evaluation, and Scale on Artificial Pedestrians

et al. 2017

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“…3, with emphasis on data analysis and results about trajectories, speed and group proxemic behaviour. The paper concludes with remarks about results and their use for the validation of the simulation system ELIAS38 [4,5], with reference to the representation of different granulometric distributions of groups, heterogeneous speed profiles and group cohesion mechanism (Sec. 4).…”

Section: Introductionmentioning

confidence: 99%

Age and Group-driven Pedestrian Behaviour: from Observations to Simulations

2016

Self Cite

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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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“…Examples of microscopic models are cellular automata models (e.g., [10,[25][26][27][28][29][30][31]), lattice gas models (e.g., [32]), social force models (e.g., [4,11,[33][34][35]), motion planning with velocity obstacles (e.g., [36,37]), agent-based models (e.g., [38][39][40]), game theoretic models (e.g., [41][42][43]), approaches based on experiments with animals (e.g., [44][45][46][47]), and hybrid models (e.g., [48]). Cellular automata models and lattice gas models partition the space into grids or hexagons.…”

Section: Evacuation Models and Crowd Dynamicsmentioning

confidence: 99%

Integrating Decentralized Indoor Evacuation with Information Depositories in the Field

Zhao

Winter

Tomko

2017

IJGI

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Abstract:The lonelier evacuees find themselves, the riskier become their wayfinding decisions. This research supports single evacuees in a dynamically changing environment with risk-aware guidance. It deploys the concept of decentralized evacuation, where evacuees are guided by smartphones acquiring environmental knowledge and risk information via exploration and knowledge sharing by peer-to-peer communication. Peer-to-peer communication, however, relies on the chance that people come into communication range with each other. This chance can be low. To bridge between people being not at the same time at the same places, this paper suggests information depositories at strategic locations to improve information sharing. Information depositories collect the knowledge acquired by the smartphones of evacuees passing by, maintain this information, and convey it to other passing-by evacuees. Multi-agent simulation implementing these depositories in an indoor environment shows that integrating depositories improves evacuation performance: It enhances the risk awareness and consequently increases the chance that people survive and reduces their evacuation time. For evacuating dynamic events, deploying depositories at staircases has been shown more effective than deploying them in corridors.

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Modelling negative interactions among pedestrians in high density situations

Cited by 75 publications

References 31 publications

Modeling, Evaluation, and Scale on Artificial Pedestrians

Modeling, Evaluation, and Scale on Artificial Pedestrians

Age and Group-driven Pedestrian Behaviour: from Observations to Simulations

Integrating Decentralized Indoor Evacuation with Information Depositories in the Field

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