A collision avoidance model for two-pedestrian groups: Considering random avoidance patterns

Zhou, Zhuping; Cai, Yifei; Ke, Ruimin; Yang, Jiwei

doi:10.1016/j.physa.2016.12.041

Cited by 27 publications

(11 citation statements)

References 16 publications

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“…They conclude that group size, intra-group structures, and inter-group relationships are important in crowd evacuation. Zhou et al 43 propose an agent-based model to simulate the group behavior of two different groups by providing collision avoidance. They use a velocity-obstacle method to simulate the locomotion of the crowd.…”

Section: Dossetti Et Almentioning

confidence: 99%

Modeling pedestrian group behavior in crowd evacuations

Turgut

Bozdag

2021

Fire and Materials

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Many models have been developed in recent years to describe pedestrian group behavior. Most prior research on group behavior focuses mainly on small groups and does not provide a general approach for grouping pedestrians with respect to different group sizes. They also analyze pedestrian group dynamics in normal circumstances. However, people's reactions who are aware of an emergency are not the same as how they respond to normal or usual situations. The central focus of this

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Section: Dossetti Et Almentioning

confidence: 99%

Modeling pedestrian group behavior in crowd evacuations

Turgut

Bozdag

2021

Fire and Materials

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“…In this study, the methods in the study of Zhou et al . [31] and Zhang et al . [32] are adopted to build the utility function.…”

Section: Vehicle–pedestrian Collision Prediction Modelmentioning

confidence: 99%

Vision‐based approach for predicting the probability of vehicle–pedestrian collisions at intersections

Zhou

Peng

Cai

2020

IET Intelligent Trans Sys

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Road accidents impose serious problems on society. Possible collisions between vehicles and pedestrians must be detected before they occur so that a timely warning may be issued. By using the vision‐based approach, this study presents an effective and efficient algorithm to estimate the vehicle–pedestrian collision probability at intersections. The real‐time trajectories and movement parameters (position, speed, acceleration or direction) of vehicles and pedestrians are obtained based on state‐of‐the‐art detection and tracking algorithm which include background subtraction method, faster regions with convolutional neural networks and optical flow method. To find the appropriate time to identify the latent collision risk for calculating the collision probability, this study defines the critical time based on different collision patterns of perception‐reaction failure and evasive action failure. In addition, based on discrete acceleration and discrete angle, the authors get different extended trajectories which can include most situation when the conflict happened. Trajectories generation probability are given by the discrete choice probability model based on the Logit model to get the accurate collision probability. Real‐world video data is implemented to demonstrate the approach. This proposed collision prediction method can provide some important results for designing the intelligent pedestrian signal timing schemes at intersections.

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“…One of the essential tasks of evacuation in a building is to represent the inherent link between facilities layout and human behavior [34,35]. e pedestrians' path finding behaviors in buildings and channels have been mainly focused on [36,37], and the behavior differences in path finding regarding the dynamic spatial availability have been considered [38,39]. Rogsch et al considered the difference in spatial knowledge of people in the building and analyzed the evacuation efficiency [12,40].…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling Human Evacuating Behavior in Limited Space Based on Cellular Automata Model

Wen

Zhao

et al. 2020

Complexity

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The study of evacuation for buildings with limited space is an important part of improving evacuation efficiency and preventing stampedes. A building evacuation model was proposed based on cellular automata simulation considering different crowd states. Different flow sizes under layout environments with the same facilities as well as evacuation efficiency, bottleneck area density, and escape routes choice under the orderly and disorderly distribution conditions have also been analyzed. The results show that the initial disorderly distribution state is superior to the orderly distribution state in terms of the evacuation efficiency index. The former provides evacuees with maximum room for the corridor and the exit, with the overall evacuation density being lower than that of the latter. Evacuation along the central corridor provides more room compared to that of the two flanks, which explains why evacuees prefer to occupy the central area when space is limited, and this is detrimental to the moving capacity.

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A collision avoidance model for two-pedestrian groups: Considering random avoidance patterns

Cited by 27 publications

References 16 publications

Modeling pedestrian group behavior in crowd evacuations

Modeling pedestrian group behavior in crowd evacuations

Vision‐based approach for predicting the probability of vehicle–pedestrian collisions at intersections

Modeling Human Evacuating Behavior in Limited Space Based on Cellular Automata Model

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