15,040 research outputs found
The Effect of Integrating Travel Time
This contribution demonstrates the potential gain for the quality of results
in a simulation of pedestrians when estimated remaining travel time is
considered as a determining factor for the movement of simulated pedestrians.
This is done twice: once for a force-based model and once for a cellular
automata-based model. The results show that for the (degree of realism of)
simulation results it is more relevant if estimated remaining travel time is
considered or not than which modeling technique is chosen -- here force-based
vs. cellular automata -- which normally is considered to be the most basic
choice of modeling approach.Comment: preprint of Pedestrian and Evacuation 2012 conference (PED2012)
contributio
Inflow process of pedestrians to a confined space
To better design safe and comfortable urban spaces, understanding the nature
of human crowd movement is important. However, precise interactions among
pedestrians are difficult to measure in the presence of their complex
decision-making processes and many related factors. While extensive studies on
pedestrian flow through bottlenecks and corridors have been conducted, the
dominant mode of interaction in these scenarios may not be relevant in
different scenarios. Here, we attempt to decipher the factors that affect human
reactions to other individuals from a different perspective. We conducted
experiments employing the inflow process in which pedestrians successively
enter a confined area (like an elevator) and look for a temporary position. In
this process, pedestrians have a wider range of options regarding their motion
than in the classical scenarios; therefore, other factors might become
relevant. The preference of location is visualized by pedestrian density
profiles obtained from recorded pedestrian trajectories. Non-trivial patterns
of space acquisition, e.g., an apparent preference for positions near corners,
were observed. This indicates the relevance of psychological and anticipative
factors beyond the private sphere, which have not been deeply discussed so far
in the literature on pedestrian dynamics. From the results, four major factors,
which we call flow avoidance, distance cost, angle cost, and boundary
preference, were suggested. We confirmed that a description of decision-making
based on these factors can give a rise to realistic preference patterns, using
a simple mathematical model. Our findings provide new perspectives and a
baseline for considering the optimization of design and safety in crowded
public areas and public transport carriers.Comment: 23 pages, 6 figure
Survey on Vision-based Path Prediction
Path prediction is a fundamental task for estimating how pedestrians or
vehicles are going to move in a scene. Because path prediction as a task of
computer vision uses video as input, various information used for prediction,
such as the environment surrounding the target and the internal state of the
target, need to be estimated from the video in addition to predicting paths.
Many prediction approaches that include understanding the environment and the
internal state have been proposed. In this survey, we systematically summarize
methods of path prediction that take video as input and and extract features
from the video. Moreover, we introduce datasets used to evaluate path
prediction methods quantitatively.Comment: DAPI 201
Human Motion Trajectory Prediction: A Survey
With growing numbers of intelligent autonomous systems in human environments,
the ability of such systems to perceive, understand and anticipate human
behavior becomes increasingly important. Specifically, predicting future
positions of dynamic agents and planning considering such predictions are key
tasks for self-driving vehicles, service robots and advanced surveillance
systems. This paper provides a survey of human motion trajectory prediction. We
review, analyze and structure a large selection of work from different
communities and propose a taxonomy that categorizes existing methods based on
the motion modeling approach and level of contextual information used. We
provide an overview of the existing datasets and performance metrics. We
discuss limitations of the state of the art and outline directions for further
research.Comment: Submitted to the International Journal of Robotics Research (IJRR),
37 page
Incorporating intelligence into exit choice model for typical evacuation
Integrating an exit choice model into a microscopic crowd dynamics model is an essential approach for obtaining more efficient evacuation model. We describe various aspects of decision-making capability of an existing rule-based exit choice model for evacuation processes. In simulations, however, the simulated evacuees clogging at exits have behaved non-intelligently, namely they do not give up their exits for better ones for safer egress. We refine the model to endow the individuals with the ability to leave their exits due to dynamic changes by modifying the model of their excitement resulted from the source of panic. This facilitates the approximately equal crowd size at exits for being until the end of the evacuation process, and thereby the model accomplishes more optimal evacuation. For further intelligence, we introduce the prediction factor that enables higher probability of equally distributing evacuees at exits. A simulation to validate the contribution is performed, and the results are analyzed and compared with the original model
Integrating a Human Behavior Model within an Agent-Based Approach for Blasting Evacuation
Several studies on Emergency Management are available in the literature, but most of them do not consider how the human behavior during an emergency can affect the evacuation process. Therefore, the novel contribution of this article is the implementation of an agentābased model to describe the evacuation, due to a blast in a public area, integrated with a human behavior analytical model. Each agent has its own behavior that is described in a layered framework. The first layer simulates the āagent's featuresā function. Then, an āindividual moduleā describes dynamically the emotional aspects using (i) the Decision Field Theory, (ii) a stationary stochastic model, and (iii) the results coming from a questionnaire. An agentābased model with integrated human behavior is proposed to test critical infrastructures in emergency conditions without performing full scale evacuation tests. Analyses could be performed both in real time with a hazard scenario and at the design level to predict the system response to identify the optimal configuration. Therefore, the development of the proposed methodology could support both designers and policy makers in the decisionāmaking process
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