Optimizing Stadium Evacuation by Integrating Geo-Computation and Affordance Theory

The purpose of this project was to optimize football stadium evacuation time by integrating geo-computation with affordance theory from perceptual psychology to account for evacuee characteristics: age, gender, physical fitness, alcohol consumption, and prior experience attending football games at The University of Southern Mississippi (USM), evacuating from large, outdoor public places, and with hazard events. According to the Uniting and Strengthening America by Providing Appropriate Tools Required to Intercept and Obstruct Terrorism (USA PATRIOT) Act, football stadiums are part of the country’s critical infrastructure warranting special government protection. Evacuation modeling was identified as an important component of game day emergency preparation. Research shows that: (1) the age, gender, and physical fitness of an individual impact his/her locomotion speed; (2) evacuation route choice is influenced by the perception of its safety and effectiveness; and (3) prior evacuation experience affects evacuation decision-making processes. By including these factors, this research, conducted at USM’s M.M. Roberts Stadium, represents the reality of evacuee movement and behaviors that influence stadium evacuation time. A questionnaire-based survey was administered to game attendees prior to a USM home game to gather evacuee attribute data that influenced locomotion speed. This data, plus secondary spatial data, were used in an agent-based model to model individual evacuee movement. The time required for all evacuees to exit the stadium and campus was 165.16 minutes. This time was significantly shorter than evacuation times from the same location using non-location-specific evacuee locomotion speeds, suggesting that use of local data is vital to accurately depicting evacuation time. The findings also indicated that age and gender were the two main factors that impacted locomotion speeds. The main contributions of this study were: (1) optimizing evacuation time by using location-specific locomotion speeds and (2) providing insights into how evacuees’ physical and mental health influence their evacuation decision-making processes. The U.S. government and sports management industry could use these findings to increase game day safety and security. Due to the spatio-temporal nature of evacuation modeling and perceptions of evacuees that impact evacuation time, this research contributed to the fields of geography, computer science, sport management, psychology, and emergency management

Perception-based analytical technique of evacuation behavior under radiological emergency: An illustration of the Kori area

A simulation-based approach is proposed to study the protective actions taken by residents during nuclear emergencies using cognitive findings. Human perception-based behaviors are not heavily incorporated in the evacuation study for nuclear emergencies despite their known importance. This study proposes a generic framework of perception-based behavior simulation, in accordance with the ecological concept of affordance theory and a formal representation of affordance-based finite state automata. Based on the generic framework, a simulation model is developed to allow an evacuee to perceive available actions and execute one of them according to Newton & rsquo;s laws of motion. The case of a shadow evacuation under nuclear emergency is utilized to demonstrate the applicability of the proposed framework. The illustrated planning algorithm enables residents to compute not only prior knowledge of the environmental map, but also the perception of dynamic surroundings, using widely observed heuristics. The simulation results show that the temporal and spatial dynamics of the evacuation behaviors can be analyzed based on individual perception of circumstances, while utilizing the findings in cognitive science under unavoidable data restriction of nuclear emergencies. The perception-based analysis of the proposed framework is expected to enhance nuclear safety technology by complementing macroscopic analyses for advanced protective measures. (c) 2020 Korean Nuclear Society, Published by Elsevier Korea LLC. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Crowd Simulation Incorporating Agent Psychological Models, Roles and Communication

We describe a new architecture to integrate a psychological model into a crowd simulation system in order to obtain believable emergent behaviors. Our existing crowd simulation system (MACES) performs high level wayfinding to explore unknown environments and obtain a cognitive map for navigation purposes, in addition to dealing with low level motion within each room based on social forces. Communication and roles are added to achieve individualistic behaviors and a realistic way to spread information about the environment. To expand the range of realistic human behaviors, we use a system (PMFserv) that implements human behavior models from a range of ability, stress, emotion, decision theoretic and motivation sources. An architecture is proposed that combines and integrates MACES and PMFserv to add validated agent behaviors to crowd simulations

MODELING OF TASK COMPLEXITY IN HUMAN-CENTERED SYSTEMS

Department of System Design & Control EngineeringThroughout the years, technological expansion has been coupled with complex work allocation in Human-Centered System (HCS). In spite of the recent advances in automation, role of humans in the HCS is still regarded a key factor for adaptability and flexibility. Meanwhile, due to advances in computing, computer simulations have been the indispensable tool in the study of complex systems. However, due to the inability to accurately represent human dynamic behavior, the majority of HCS simulations have often failed to meet expectations. The failure of HCS simulations can be traced in poor or inaccurate representation of key aspect of system. Whereas the machine component of HCS is often accurately simulated, research claims that human component is often the cause of a large percentage of the disparity between simulation predictions and real-world performance. This dissertation introduces a novel human behavioral modeling framework that systematically simulates human action behavior in HCS. The proposed modeling framework is demonstrated with a case study using simulation in which a set of feasible human actions are generated from the affordance-effectivity duals in a spatial-temporal dimension. The model employs Markov Decision Process (MDP) in which NASA-TLX (Task Load Index) is used as cost estimates. The action selection process of human agents, i.e., triggering of state transitions, is stochastically modeled in accordance with the action-state cost (load) values. A series of affordance-based numerical values are calculated for predicting prospective actions in the system. Finally, an evacuation simulation example based on the proposed model is illustrated to verify the proposed human behavioral modeling framework. The incorporation of human modeling in HCS simulation offers a wide range of benefits in representing human???s goal directed action. However due to the complexity and the cost of representing every aspect of human behavior in computable terms, the proposed framework is better fit in simplified and controllable environment. Thus, we then propose a human in the loop (HIL) approach to investigate the operator???s performance in HCSparticularly, the mixed model assembly line (MMAL). In HCS such as MMAL, human operators are often required to carry out tasks according to instructions. In the proposed methodology, rather than a mathematical representation of human, a real human plays a core role in system operation for the simulation and consequently influences the outcome in such a way that is difficult if not impossible to reproduce via traditional methods. At the initial stage of the simulation, various features are extracted after which, a stepwise feature selection is used to identify the most relevant features affecting human performance. The selected features are in turn used to build a regression model used to generate human performance parameters in the HCS simulation. Finally, we explore the analytical relationship between the flexibility (variation) and the complexity of human role in HCS. As the number of alternative choices (or actions) available to human increases, the choice process becomes complex, rending human modeling and predictability more difficult. The dissertation will particularly utilize the visual choice complexity to convey the proposed computation of task complexity as a function of flexibility. Thus, we propose a method to quantify task complexity for effective management of the semi-automated systems such a MMAL. Based on the concept of information entropy, our model considers both the variety in the system and the similarity among the varieties. The proposed computational model along with an illustrative case study not only serve as a tool to quantitatively assess the impact of the task complexity on the total system performance, but also provide an insight on how the complexity can be mitigated without worsening the flexibility and throughput of the system.ope

A Highway-Driving System Design Viewpoint using an Agent-based Modeling of an Affordance-based Finite State Automata

This paper presents an agent-based modeling framework for affordance-based driving behaviors during the exit maneuver of driver agents in human-integrated transportation problems. We start our discussion from one novel modeling framework based on the concept of affordance called the Affordance-based Finite State Automata (AFSA) model, which incorporates the human perception of resource availability and action capability. Then, the agent-based simulation illustrates the validity of the AFSA framework for the Highway-Lane-Driver System. Next, the comparative study between real driving data and agent-based simulation outputs is provided using the transition diagram. Finally, we perform a statistical analysis and a correlation study to analyze affordance-based driving behavior of driver agents. The simulation results show that the AFSA model well represents the perception-based human actions and drivers??? characteristics, which are essential for the design viewpoint of control framework of human driver modeling. This study is also expected to benefit a designed control for autonomous/self-driving car in the future

Interim Report: Flashing Lights for Road Tunnel Emergency Exit Portals - A Virtual Reality Experiment

A virtual reality (VR) experiment with 96 participants was carried out to provide recommendations on the design of flashing lights on emergency exit portals for road tunnel emergency evacuation. The experiment was carried out in a Cave Automatic Virtual Environment (CAVE) laboratory at Lund University. A set of variables has been investigated, namely 1) Colour of flashing lights, 2) Flashing rate, 3) The type of light source, 4) the number and layout of the lights on the portal (1 light on top of the exit door, 3 lights of which 1 on top and 2 on the sides of the exit door, or 2 bars on the sides of the exit door). An additional portal design variable has also been investigated, i.e. 5) the use of a window vs a painted running man on the exit door. Participants were immersed in a VR road tunnel emergency evacuation scenario and they were then asked to rank different portal designs using a questionnaire based on the Theory of Affordances. Results show that green or white flashing lights perform better than blue lights in the emergency exit portals. Flashing rate of 1 Hz and 4 Hz performed better than flashing rates at 0.5 Hz. A LED light source performed better than single and double strobe lights. Although the three layouts of the lights under consideration performed similarly, the use of a higher number of lights is deemed to be beneficial. If the door is visible (i.e., if no smoke is taken into consideration in the emergency scenario), the scenario with the running man painted on the door provides equal results than a door with a window. Nevertheless, the use of the window is recommended since it allows seeing behind the door (including the possibility to see the traffic), and reduce people’s hesitation

Traffic Information Signs, Colour Scheme of Emergency Exit Portals and Acoustic Systems for Road Tunnel Emergency Evacuations

This work presents a literature review and a questionnaire study with 62 participants aimed at providing recommendations on the design of a set of evacuation systems for road tunnels: 1) Traffic Information Sign (TIS) - message and size of the sign (large or small), colour scheme, and use of pictograms and/or flashing lights, 2) Emergency exit portal layout - colour scheme, 3) Acoustic systems - voice message and/or warning signals. The TIS is recommended to include the use of two panels which present text (in amber) and flashing lights in one panel and the emergency exit pictorial symbol in green in the other panel. An increased size of the panels has a positive effect on capturing participants’ attention. The recommended colour scheme for the emergency exit portal is safety green for the portal and a “green darker than the safety green” for the door. Vocal messages are not recommended since they may be quite difficult to perceive in tunnels. The use of a warning signal (F_SAW signal) based on British Standards is recommended

A perception-based emotion contagion model in crowd emergent evacuation simulation

With the increasing number of emergencies, the crowd simulation technology has attracted wide attention in recent years. Existing emergencies have shown that individuals are easy to be influenced by other’s emotion during the evacuation. This will make it easier for people to aggregate together and increase security risks. Some of the existing evacuation models without considering emotion are therefore not suitable for describing crowd behaviors in emergencies. We propose a perception-based emotion contagion model and use multi-agent technology to simulate the crowd behaviors. Navigation points are introduced to guide the movement of the agents. Based on the proposed model, a prototype simulation system for crowd emotion contagion is developed. The comparative simulation experiments verify that the model can effectively deduct the evacuation time and crowd emotion contagion. The proposed model could be an assistant analysis method for crowd management in emergencies

Analyzing Human-Building Interactions in Virtual Environments Using Crowd Simulations

This research explores the relationship between human-occupancy and environment designs by means of human behavior simulations. Predicting and analyzing user-related factors during environment designing is of vital importance. Traditional Computer-Aided Design (CAD) and Building Information Modeling (BIM) tools mostly represent geometric and semantic aspects of environment components (e.g., walls, pillars, doors, ramps, and floors). They often ignore the impact that an environment layout produces on its occupants and their movements. In recent efforts to analyze human social and spatial behaviors in buildings, researchers have started using crowd simulation techniques for dynamic analysis of urban and indoor environments. These analyses assist the designers in analyzing crowd-related factors in their designs and generating human-aware environments. This dissertation focuses on developing interactive solutions to perform spatial analytics that can quantify the dynamics of human-building interactions using crowd simulations in the virtual and built-environments. Partially, this dissertation aims to make these dynamic crowd analytics solutions available to designers either directly within mainstream environment design pipelines or as cross-platform simulation services, enabling users to seamlessly simulate, analyze, and incorporate human-centric dynamics into their design workflows