Comparative Study of Dissuasive Emergency Signage

This thesis investigates dissuasive emergency signage conveying a message of not utilizing a specific exit door. The thesis analyzes and highlights which features of dissuasive emergency signage have the largest impact on observer preference, interpretation and noticeability of the signage, in addition to analyzing the possibility and effects of causing an increased sense of urgency amongst the observers. It is shown that features which clearly negate the original exit- message of the original exit signage are most effective, for instance a red LED (light emitting diode) X-marking placed across the entirety of the exit signage conveys a clear dissuasive message which is easily understandable by observers. Other features of note are red flashing lights and alternation of color. Affecting the sense of urgency of the observer results in faster decision making times and a mindset more prone to searching for and following signs and instructions, which is considered a positive effect. The sense of urgency is largely affected by sensory inputs such as red flashing lights or other features which cause the signs to break the tendencies of normalcy.The Exit Sign Says NO! Is it possible to negate existing exit signage in a way that would affect egress route choice making it possible to reroute evacuating people? The answer is yes, and our current knowledge and technology makes it very much a possibility. Affecting egress route choice is possible in a number of ways. Earlier research has shown the possibilities of making certain egress routes more attractive to people by applying features such as green lights (Nilsson, 2009) and dynamic markings (Galea, Xie, & Lawrence, 2014). However, it has also been shown that it is possible to make egress routes less attractive to egressing occupants by providing negating features to the exit signage (Olander, 2015). It was found that the most efficient way to negate an existing exit sign was by providing a clear negating marking, such as a red cross over the sign, coupled with red flashing lights (Olander, 2015). Other negating options were also tested, but with much less effect. Alternating colors from a green background to a red background in an attempt to appeal to color association, which has been shown to follow the lines of green equals safety while red equals danger during an egress situation (Nilsson, Frantzich, & Saunders, 2005), only resulted in statements similar to the following: “The red exit sign looks just like a regular sign, but different. I would just try to exit there!” This is most likely the result of sending an ambiguous message, which proved to be a big issue when sorting out preference for a certain negating exit signage. Signs which provided an ambiguous message were rated very poorly when compared to signs with a more clear negating message (Olander, 2015). In addition to the above, the addition of sensory heavy features, such as the mentioned red flashing lights, should cause observers to sense a greater sense of urgency than they otherwise would (Kinateder, Kuligowski, Reneke, & Peacock, 2014). This would result in people becoming more prone to seek out and follow instructions, in addition to making the decision to evacuate faster (Day, Hulse, & Galea, 2013). In order to determine which negated exit signage was most preferred amongst people a paired comparison survey was carried out. Participants of the survey were shown a series of tests, where in each test two signs were viewed simultaneously. Participants were then asked to fill out a survey sheet consisting of a series of affordance based questions which gave insight into what specific features affected certain sensory, cognitive of functional thought patterns (Olander, 2015). With the help of these findings it is possible to create an evacuation system that has the ability to guide egressing people along certain paths, chosen in a way that leads the egressing people away from dangers and avoiding areas where critical conditions might have been reached or congestion is prominent. Current research projects suggest that endeavors such as this are not a too far off occurrence. Currently, similar ideas are being tested in real life full scale experiments (Bryant & Giachritsis, 2014). With the addition Figure 2. One of the most preferred negated signs of the study. Figure 1. The least preferred negated sign of the study, largely due to its ambiguous nature. It is implied that color coding in itself it not sufficient to alter the message of the original signage into a negated message. of the signage options mentioned, future research projects may be able to incorporate an even more effective exit sign design into their dynamic evacuation systems. With that said, I believe that the days of the old static evacuation systems are coming to an end and we will in the coming years be seeing an increase in the use of innovative evacuation solutions making use of dynamic signage to facilitate a safer evacuation and leading people out of harm’s way. Joakim Olander Fire Engineering Student, Lund Tekniska Högskola References Bryant, P., & Giachritsis, C. (2014). The GETAWAY Project - Improving Passenger Evacuation Techniques in Railway Stations. Paris: Transport Reasearch Arena. Day, R. C., Hulse, L. M., & Galea, E. R. (2013). Response Phase Behaviours and Response Time Predictors of the 9/11 World Trade Center Evacuation. Fire Technology(49), 657-678. Galea, E. R., Xie, H., & Lawrence, P. J. (2014). Experimental and Survey Studies on the Effectiveness of Dynamic Signage Systems. Fire Safety Science - Draft Proceedings of the Eleventh International Symposium. Kinateder, M. T., Kuligowski, E. D., Reneke, P. A., & Peacock, R. D. (2014). NIST Technical Note 1840 - A Review of Risk Perception in Building Fire Evacuation. U.S Department of Commerce: NIST National Institute of Standards and Technology. Nilsson, D. (2009). Exit Choice in Fire Emergencies - Influencing Choice of Exit with Flashing Lights. Lunds Universitet, Avdelningen för Brandteknik. Lund: Lunds Universitet. Nilsson, D., Frantzich, H., & Saunders, W. (2005). Coloured Flashing Lights to Mark Emergency Exits - Experiences from Evactuation Experiments. Fire Safety Science - Proceedings of the Eighth International Symposium, 569-579. Olander, J. (2015). Comparative Study of Dissuasive Emergency Signage. Lund: Department of Fire Safety Engineering, Lund University. Sime, J. D. (1985). Movement Towards the Familiar: Person and Place Affiliation in a Fire Entrapment Setting. Environment and Behaviour, v. 17, 697-724

Software agents & human behavior

People make important decisions in emergencies. Often these decisions involve high stakes in terms of lives and property. Bhopal disaster (1984), Piper Alpha disaster (1988), Montara blowout (2009), and explosion on Deepwater Horizon (2010) are a few examples among many industrial incidents. In these incidents, those who were in-charge took critical decisions under various ental stressors such as time, fatigue, and panic. This thesis presents an application of naturalistic decision-making (NDM), which is a recent decision-making theory inspired by experts making decisions in real emergencies. This study develops an intelligent agent model that can be programed to make human-like decisions in emergencies. The agent model has three major components: (1) A spatial learning module, which the agent uses to learn escape routes that are designated routes in a facility for emergency evacuation, (2) a situation recognition module, which is used to recognize or distinguish among evolving emergency situations, and (3) a decision-support module, which exploits modules in (1) and (2), and implements an NDM based decision-logic for producing human-like decisions in emergencies. The spatial learning module comprises a generalized stochastic Petri net-based model of spatial learning. The model classifies routes into five classes based on landmarks, which are objects with salient spatial features. These classes deal with the question of how difficult a landmark turns out to be when an agent observes it the first time during a route traversal. An extension to the spatial learning model is also proposed where the question of how successive route traversals may impact retention of a route in the agent’s memory is investigated. The situation awareness module uses Markov logic network (MLN) to define different offshore emergency situations using First-order Logic (FOL) rules. The purpose of this module is to give the agent the necessary experience of dealing with emergencies. The potential of this module lies in the fact that different training samples can be used to produce agents having different experience or capability to deal with an emergency situation. To demonstrate this fact, two agents were developed and trained using two different sets of empirical observations. The two are found to be different in recognizing the prepare-to-abandon-platform alarm (PAPA ), and similar to each other in recognition of an emergency using other cues. Finally, the decision-support module is proposed as a union of spatial-learning module, situation awareness module, and NDM based decision-logic. The NDM-based decision-logic is inspired by Klein’s (1998) recognition primed decision-making (RPDM) model. The agent’s attitudes related to decision-making as per the RPDM are represented in the form of belief, desire, and intention (BDI). The decision-logic involves recognition of situations based on experience (as proposed in situation-recognition module), and recognition of situations based on classification, where ontological classification is used to guide the agent in cases where the agent’s experience about confronting a situation is inadequate. At the planning stage, the decision-logic exploits the agent’s spatial knowledge (as proposed in spatial-learning module) about the layout of the environment to make adjustments in the course of actions relevant to a decision that has already been made as a by-product of situation recognition. The proposed agent model has potential to be used to improve virtual training environment’s fidelity by adding agents that exhibit human-like intelligence in performing tasks related to emergency evacuation. Notwithstanding, the potential to exploit the basis provided here, in the form of an agent representing human fallibility, should not be ignored for fields like human reliability analysis

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

A NATURALISTIC COMPUTATIONAL MODEL OF HUMAN BEHAVIOR IN NAVIGATION AND SEARCH TASKS

Planning, navigation, and search are fundamental human cognitive abilities central to spatial problem solving in search and rescue, law enforcement, and military operations. Despite a wealth of literature concerning naturalistic spatial problem solving in animals, literature on naturalistic spatial problem solving in humans is comparatively lacking and generally conducted by separate camps among which there is little crosstalk. Addressing this deficiency will allow us to predict spatial decision making in operational environments, and understand the factors leading to those decisions. The present dissertation is comprised of two related efforts, (1) a set of empirical research studies intended to identify characteristics of planning, execution, and memory in naturalistic spatial problem solving tasks, and (2) a computational modeling effort to develop a model of naturalistic spatial problem solving. The results of the behavioral studies indicate that problem space hierarchical representations are linear in shape, and that human solutions are produced according to multiple optimization criteria. The Mixed Criteria Model presented in this dissertation accounts for global and local human performance in a traditional and naturalistic Traveling Salesman Problem. The results of the empirical and modeling efforts hold implications for basic and applied science in domains such as problem solving, operations research, human-computer interaction, and artificial intelligence

DEVELOPMENT OF A MIXED-FLOW OPTIMIZATION SYSTEM FOR EMERGENCY EVACUATION IN URBAN NETWORKS

In most metropolitan areas, an emergency evacuation may demand a potentially large number of evacuees to use transit systems or to walk over some distance to access their passenger cars. In the process of approaching designated pick-up points for evacuation, the massive number of pedestrians often incurs tremendous burden to vehicles in the roadway network. Hence, one critical issue in a multi-modal evacuation planning is the effective coordination of the vehicle and pedestrian flows by considering their complex interactions. The purpose of this research is to develop an integrated system that is capable of generating the optimal evacuation plan and reflecting the real-world network traffic conditions caused by the conflicts of these two types of flows. The first part of this research is an integer programming model designed to optimize the control plans for massive mixed pedestrian-vehicle flows within the evacuation zone. The proposed model, integrating the pedestrian and vehicle networks, can effectively account for their potential conflicts during the evacuation. The model can generate the optimal routing strategies to guide evacuees moving toward either their pick-up locations or parking areas and can also produce a responsive plan to accommodate the massive pedestrian movements. The second part of this research is a mixed-flow simulation tool that can capture the conflicts between pedestrians, between vehicles, and between pedestrians and vehicles in an evacuation network. The core logic of this simulation model is the Mixed-Cellular Automata (MCA) concept, which, with some embedded components, offers a realistic mechanism to reflect the competing and conflicting interactions between vehicle and pedestrian flows. This study is expected to yield the following contributions * Design of an effective framework for planning a multi-modal evacuation within metropolitan areas; * Development of an integrated mixed-flow optimization model that can overcome various modeling and computing difficulties in capturing the mixed-flow dynamics in urban network evacuation; * Construction and calibration of a new mixed-flow simulation model, based on the Cellular Automaton concept, to reflect various conflicting patterns between vehicle and pedestrian flows in an evacuation network