How the OCEAN Personality Model Affects the Perception of Crowds

Cataloged from PDF version of article.A personality model named High-Density Autonomous Crowds (HiDAC) simulation system provides individual differences by assigning each person different psychological and physiological traits. Users normally set these parameters to model a crowd's nonuniformity and diversity. The approach creates plausible variations in the crowd and enables novice users to dictate these variations by combining a standard personality model with a high-density crowd simulation. HiDAC addresses the simulation of local behaviors and the global wayfinding of crowds in a dynamically changing environment. It directs autonomous agents' behavior by combining geometric and psychological rules. HiDAC handles collisions through avoidance and response forces. Over long distances, the system applies collision avoidance so that agents can steer around obstacles. HiDAC assigns people specific behaviors. The number of actions they complete depends on their curiosity

Environmental effect on egress simulation

Abstract. Evacuation and egress simulations can be a useful tool for studying the effect of design decisions on the flow of agent movement. This type of simulation can be used to determine before hand the effect of design decisions and enable exploration of potential improvements. In this work, we study at how agent egress is affected by the environment in real world and large scale virtual environments and investigate metrics to analyze the flow. Our work differs from many evacuation systems in that we support grouping restrictions between agents (e.g., families or other social groups traveling together), and model scenarios with multiple modes of transportation with physically realistic dynamics (e.g., individuals walk from a building to their own cars and leave only when all people in the group arrive).

A Synthetic-Vision Based Steering Approach for Crowd Simulation

International audienceIn the everyday exercise of controlling their locomotion, humans rely on their optic flow of the perceived environment to achieve collision-free navigation. In crowds, in spite of the complexity of the environment made of numerous obstacles, humans demonstrate remarkable capacities in avoiding collisions. Cognitive science work on human locomotion states that relatively succinct information is extracted from the optic flow to achieve safe locomotion. In this paper, we explore a novel vision-based approach of collision avoidance between walkers that fits the requirements of interactive crowd simulation. By simulating humans based on cognitive science results, we detect future collisions as well as the level of danger from visual stimuli. The motor-response is twofold: a reorientation strategy prevents future collision, whereas a deceleration strategy prevents imminent collisions. Several examples of our simulation results show that the emergence of self-organized patterns of walkers is reinforced using our approach. The emergent phenomena are visually appealing. More importantly, they improve the overall efficiency of the walkers' traffic and avoid improbable locking situations

Creating crowd variation with the OCEAN personality model

Most current crowd simulators animate homogeneous crowds, but include underlying parameters that can be tuned to create variations within the crowd. These parameters, however, are specific to the crowd models and may be difficult for an animator or naive user to use. We propose mapping these parameters to personality traits. In this paper, we extend the HiDAC (High-Density Autonomous Crowds) system by providing each agent with a personality model in order to examine how the emergent behavior of the crowd is affected. We use the OCEAN personality model as a basis for agent psychology. To each personality trait we associate nominal behaviors; thus, specifying personality for an agent leads to an automation of the low-level parameter tuning process. We describe a plausible mapping from personality traits to existing behavior types and analyze the overall emergent crowd behaviors. Copyright © 2008, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved

Фразеологизм как особый тип терминологической номинации

Анализируется когнитивная специфика фразеологизмов в сфере терминологической номинации, выявляется соотношение данных единиц с различными типами знания. Особое внимание уделяется причинам и факторам выбора фразеологической номинации при передаче специального знания. Автор статьи утверждает, что термин-фразеологизм вербализует комплексную информацию о внеположенном профессиональном объекте, воспринятом номинатором в его нерасчлененной целостности.The article examines the cognitive nature of phraseologisms in terminological nomination, reveals correlation of these units with different types of knowledge. Special attention is paid to the reasons and factors of choosing of phraseological nomination when transmitting special knowledge. The author of the article claims that the term-phraseologism verbalizes comprehensive information about outer professional object, perceived by the nominator in its nonsegmented integrity

Effects of communication and utility-based decision making in a simple model of evacuation

We present a simple cellular automaton based model of decision making during evacuation. Evacuees have to choose between two different exit routes, resulting in a strategic decision making problem. Agents take their decisions based on utility functions, these can be revised as the evacuation proceeds, leading to complex interaction between individuals and to jamming transitions. The model also includes the possibility to communicate and exchange information with distant agents, information received may affect the decision of agents. We show that under a wider range of evacuation scenarios performance of the model system as a whole is optimal at an intermediate fraction of evacuees with access to communication.Comment: 9 pages, 9 figure

Computer simulation of leadership, consensus decision making and collective behaviour in humans

The aim of this study is to evaluate the reliability of a crowd simulation model developed by the authors by reproducing Dyer et al.’s experiments(published in Philosophical Transactions in 2009) on human leadership and consensus decision-­making in a computer-­based environment. The theoretical crowd model of the simulation environment is presented, and its results are compared and analysed against Dyer et al.’s original experiments. It is concluded that the results are 11 largely consistent with the experiments, which demonstrates the reliability of the crowd model. Furthermore, the simulation data also reveals several additional new findings, namely: 1) the phenomena of sacrificing accuracy to reach a quicker consensus decision found in ants colonies was also discovered in the simulation; 2) the ability of reaching consensus in groups has a direct impact on the time and accuracy of arriving at the target position; 3) the positions of the informed individuals or leaders in the crowd could have significant impact on the overall crowd movement; 4) the simulation also confirmed Dyer et al.’s anecdotal evidence of the proportion of the leadership in large crowds and its effect on crowd movement. The potential applications of these findings are highlighted in the final discussion of this paper

The Rocketbox Library and the Utility of Freely Available Rigged Avatars

As part of the open sourcing of the Microsoft Rocketbox avatar library for research and academic purposes, here we discuss the importance of rigged avatars for the Virtual and Augmented Reality (VR, AR) research community. Avatars, virtual representations of humans, are widely used in VR applications. Furthermore many research areas ranging from crowd simulation to neuroscience, psychology, or sociology have used avatars to investigate new theories or to demonstrate how they influence human performance and interactions. We divide this paper in two main parts: the first one gives an overview of the different methods available to create and animate avatars. We cover the current main alternatives for face and body animation as well introduce upcoming capture methods. The second part presents the scientific evidence of the utility of using rigged avatars for embodiment but also for applications such as crowd simulation and entertainment. All in all this paper attempts to convey why rigged avatars will be key to the future of VR and its wide adoption

Comparing and Evaluating Real Time Character Engines for Virtual Environments

As animated characters increasingly become vital parts of virtual environments, then the engines that drive these characters increasingly become vital parts of virtual environment software. This paper gives an overview of the state of the art in character engines, and proposes a taxonomy of the features that are commonly found in them. This taxonomy can be used as a tool for comparison and evaluation of different engines. In order to demonstrate this we use it to compare three engines. The first is Cal3D, the most commonly used open source engine. We also introduce two engines created by the authors, Piavca and HALCA. The paper ends with a brief discussion of some other popular engines