To minimize property loss and death count in terror attacks and other emergent scenarios, attention given to timely and effective evacuation cannot be enough. Due to limited evacuation resource, i.e., number of available exits, there exists interdependence among pedestrians such as cooperation, competition and herd effect. Thus human factors - more specifically, pedestrians' behavior in emergency evacuation - play a significant role in evacuation research. Effective evacuation can only be reached when route planning are considered in conjunction with psychological dynamics, which is often ignored. As another drawback, previous research assumes the environment including available exits as stationary. However, we note that during emergency, some exits which are not often utilized in normal times are opened, which potentially helps if pedestrians are aware of them. In this paper, we analyze the effect of pedestrians' behavior, i.e., herd effect and knowledge of changing environment with Cellular Automata (CA) simulation. Results of the simulation show the harmful effect of herd effect as well as highlight the importance of timely informing pedestrians of environmental change. Accordingly, we propose policy and procedural recommendations for emergency management of large, crowded structures. Our future work includes considering more human factors and applying our model to log data provided by videos in public venues, which can further show effectiveness of our model in real scenarios.
@cite_8 emphasizes the need for greater participation from individuals with disabilities during the evacuation planning process. Understanding and addressing the psychological needs of individuals with disabilities during emergency evacuations will help ensure the safety of everyone.
@cite_8
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Emergency evacuation from airports is an important consideration given the continuing occurrence of both natural and human caused disasters. Unfortunately, the traditional evacuation-drill approach to prepare for emergency situations presents several practical challenges at the scale and magnitude required for airports. In this paper, we present an agent-based model (ABM) called exitus which is capable of determining the extent to which collective behavior and overall evacuation time of passenger groups is affected by changes in the built environment for large, complex structures. The model is unique because it explicitly considers the physical and psychological characteristics of individuals with disabilities. In our first experiment, several bomb simulation scenarios were conducted at an international airport using exitus. Several important findings were revealed including: 1) the importance of stairway and exit configurations; 2) the inherent weaknesses of the pier airport design in affecting timely evacuations; 3) who the most vulnerable groups of people are; 4) the particular risk engendered from crowded or complex building interiors for individuals with disabilities; and 5) the potential problems caused by locating explosive detection system machines near passenger processing areas. The results of a second exploratory experiment also revealed the importance of realistically modeling psychological attributes of individuals with disabilities and their potential impact on collective evacuation performance. Overall the findings demonstrated the model’s ability to generate a common operational picture capable of guiding preparedness efforts for both public and private organizations encompassing a wide variety of professional endeavor. Metro construction in China enjoyed and will continue to enjoy unprecedented development in the tenth 5 Year Plan period and the upcoming eleventh 5 Year Plan period. In China, cities are densely populated, and as a modernized urban rail transit means, metros have been undertaking increasingly important tasks of large passenger flow transportation, under which circumstance the injury and casualty will be enormous if an accident occurs. China's work safe laws and regulations have stipulated that safety evaluation must be carried out during planning, design, construction and operation of metros. As a part of the metro safety evaluation, occupant safe evacuation is a critical aspect to be assessed. This paper will first introduce the occupants evacuation design in the construction of metros in China based on Code for design of metro (CFDOM) (GB 50157-2003), including evacuation passage design, evacuation time and evacuation safe area as well as fire-engineering-based occupants evacuation design philosophy and calculation method. Finally, a computer simulation of the process of evacuation of occupants from deep buried metro station (DBMS) by using occupants evacuation dynamic model will be conducted on the example of DBMS of Guangzhou Metro Line 6, so as to study whether the occupants can be safely evacuated from DBMS in case of fire. Pedestrian evacuation is one open question in a myriad of scientific disciplines and has attracted considerable attention during the past decades. Aim to issue, various research approaches, such as mathematical modeling and simulation, experimental studied and socio-psychology surveys, have been extensively employed. Different from previous frameworks, here a behavior-based cellular automaton model is proposed, which involves the environmental characteristics and neighbors' behaviors. Given the certain range of degree of emergency, it is shown that enhancing the degree of emergency will shorten evacuation time yet decrease cooperation enthusiasm. The larger the degree of familiarity is, the shorter the evacuation time will be. In variance, larger the dependence of pedestrians will prolong the evacuation time. Besides, the novel model also produces some interesting self-organization phenomena, such as the collective behavior at the beginning of the evacuation and arch-like blocking at the end of the evacuation. When our model is finally applied to the evacuation scenario where a room has two symmetrically located exits, the symmetry breaking effect takes place. Our model may shed new light to the study of pedestrian dynamics in realistic world. Given a large city represented by nodes and arcs, with a subset of these nodes having people required to be evacuated in a disaster situation, and a subset of destination nodes where the people may be taken for safety, the evacuation route planner finds routes in this network to evacuate the people in minimum possible time. Evacuation route planning in pre-known disasters such as hurricanes is of utmost importance for civic authorities. Computing such evacuation routes in a large graph with road infrastructure constraints such as road capacities and travelling times can be challenging. The Capacity Constrained Route Planner (CCRP) is a well studied heuristic algorithm proposed by Lu, George and Shekhar for solving this problem. It uses shortest path computations as a basis for finding and scheduling possible evacuation paths in the graph. However, the algorithm fails to scale to very large graphs. Other algorithms based on CCRP like CCRP++ and Incremental Data Structure based CCRP have been proposed to scale them to larger graphs. In this paper, we analyze these algorithms from performance perspective and suggest a faster algorithm by extending the CCRP algorithm that avoids recomputing partial paths. We have carried out experiments on various graph structures which show a vast improvement in runtime without impacting the optimality of CCRP results. For instance, for the city of Oldenburg with 382285 people, 6105 nodes and 7034 edges, our algorithm produced an evacuation plan in 2.6 seconds as compared to 123.8 seconds by CCRP and 9.3 seconds by CCRP++. The evacuation of a building is a challenging problem, since the evacuees most of the times do not know or do not follow the optimal evacuation route. Especially during an ongoing hazard present in the building, finding the best evacuation route becomes harder as the conditions along the paths change in the course of the evacuation procedure. In this paper we propose a distributed system that will compute the best evacuation routes in real-time, while a hazard is spreading inside the building. The system is composed of a network of decision nodes and sensor nodes, positioned in specific locations inside the building. The recommendations of the decision nodes are computed in a distributed manner, at each of the decision nodes, which then communicate them to evacuees or rescue personnel located in their vicinity. We evaluate our proposed system in various emergency scenarios, using a multi-agent simulation platform for Building Evacuation. Our results indicate that the presence of the system improves the outcome of the evacuation with respect to the evacuation time and the injury level of the evacuees. This paper proposes a group-based framework with dedicated path planning for emergency guiding based on Internet of Things (IoT) technologies. The proposed framework can model the spatiotemporal mobility of indoor people to determine and relieve the congestion of corridors and exits. A dedicated path can be determined to provide the shortest evacuation time for each group of nearby people. The corridor and exit capacities, corridor lengths, clustering motion of a group, concurrent moving of different groups, and up-to-date distribution of group people are considered together to accurately estimate the evacuation time for each group. Based on the estimated evacuation time, evacuation load can be evenly distributed among corridors and exits to alleviate the congestion of all corridors and exits for minimizing total evacuation time. The performance of the proposed framework is evaluated by conducting mathematical analysis and computer simulations, which outperforms existing schemes and can achieve the shortest evacuation time for group-based emergency guiding. In addition, an Android-based prototype with indoor IoT localization technologies is implemented to verify the feasibility of our framework. EVACNET+ is a user-friendly interactive computer program that allows the modeling of emergency building evacuations. An EVACNET+ model is a network consisting of a set of nodes connected by arcs. The nodes represent building components such as rooms, halls, landings, stairs and lobbies. The arcs represent the passageways between the building components. The program identifies optimal evacuation plans for user defined buildings. Emergency rescues require that first responders provide support to evacuate injured and other civilians who are obstructed by the hazards. In this case, the emergency personnel can take actions strategically in order to rescue people maximally, efficiently and quickly. The paper studies the effectiveness of a random neural network (RNN)-based task assignment algorithm involving optimally matching emergency personnel and injured civilians, so that the emergency personnel can aid trapped people to move towards evacuation exits in real-time. The evaluations are run on a decision support evacuation system using the Distributed Building Evacuation Simulator (DBES) multi-agent platform in various emergency scenarios. The simulation results indicate that the RNN-based task assignment algorithm provides a near-optimal solution to resource allocation problems, which avoids resource wastage and improves the efficiency of the emergency rescue process. Many activities of daily living, such as picking up glasses, holding a fork or opening a door, which most people do without thinking, can become insurmountable for people who have upper extremity disabilities. The alternative to asking for human help is to use some assistive devices to compensate their loss of mobility; however, many of those devices are limited in terms of functionality. Robotics may provide a better approach for the development of assistive devices, by allowing greater functionality. In this paper, we present results of a study (n=31) which objectives were to evaluate the efficacy of a new joystick-controlled seven-degree of freedom robotic manipulator and assess its potential economic benefits. Results show that JACO is easy to use as the majority of the participants were able to accomplish the testing tasks on their first attempt. The economic model results inferred that the use of the JACO arm system could potentially reduce caregiving time by 41 . These study results are expected to provide valuable data for interested parties, such as individuals with disabilities, their family or caregivers. Abstract This paper explores the likely behaviours of train passengers in an emergency evacuation and examines four crucial theoretical issues on the passengers’ evacuation, including reactive vs. proactive behaviours, cooperative vs. competitive behaviours, symmetry breaking, and route exit choice. A survey of 1134 train passengers shows that respondents are not homogeneous in their likely behaviours. Overall, they are more likely to be reactive (e.g., wait for instruction from station staff) than proactive (e.g., move to exit) in an emergency situation. We also find that people are more likely to be co-operative (e.g., helping other people) than competitive (e.g., push other passengers). Although passengers are likely to show herding or symmetry breaking behaviour (e.g., following other passengers) than symmetric behaviour (e.g., choose least crowded exit), the degree of symmetry breaking behaviour is not as high as assumed in previous mathematical models. They are also unlikely to use escalators, lifts and train tunnels in their exit route choice during an emergency escape. In terms of demographic differences in behaviours, results from the ordered logit models demonstrate that there are significant differences in the evacuation behaviours between males and females but not among the different age groups. Besides providing valuable information for developing mathematical models intended to simulate passengers’ evacuation in a train station, our findings can assist managers of emergency response in developing appropriate strategies and training, and in designing solutions and education campaigns for effective evacuation. Opportunistic communications (oppcomms) use low-cost human wearable mobile nodes allowing the exchange of packets at a close range of a few to some tens of meters with limited or no infrastructure. Typically cheap pocket devices which are IEEE 802.15.4-2006 compliant can be used and they can communicate at 2m to 10m range, with local computational capabilities and some local memory. In this paper we consider the application of such devices to emergency situations when other means of communication have broken down. This paper evaluates whether oppcomms can improve the outcome of emergency evacuation in directing civilians safely. We describe an autonomous emergency support system (ESS) based on oppcomms to support evacuation of civilians in a built environment such as a building or supermarket. The proposed system uses a fixed infrastructure of sensor nodes (SNs) to monitor the environment. Hazard information obtained via SNs is disseminated to the individuals, and they spread among the people who are located in this built environment using oppcomm devices carried by these people. The information received by these people can then guide them safely to the exits as the emergency situation evolves over time. We evaluate our scheme using a distributed multi-agent building evacuation simulator (DBES) in the context of evacuation scenarios of a multi-storey office building in the presence of a fire that is spreading. The results show the degree of improvement that the oppcomms can offer. c � 2011 Published by Elsevier Ltd. In this review, we provide an overview of emerging trends and challenges in the field of intelligent and autonomous, or self-driving, vehicles. Recent advances in the field of perception, planning, and decision-making for autonomous vehicles have led to great improvements in functional capabilities, with several prototypes already driving on our roads and streets. Yet challenges remain regarding guaranteed performance and safety under all driving circumstances. For instance, planning methods that provide safe and system-compliant performance in complex, cluttered environments while modeling the uncertain interaction with other traffic participants are required. Furthermore, new paradigms, such as interactive planning and end-to-end learning, open up questions regarding safety and reliability that need to be addressed. In this survey, we emphasize recent approaches for integrated perception and planning and for behavior-aware planning, many of which rely on machine learning. This raises the question of ver... The Great East Japan Earthquake and the Fukushima nuclear accident cause large human population movements and evacuations. Understanding and predicting these movements is critical for planning effective humanitarian relief, disaster management, and long-term societ al reconstruction. In this paper, we construct a large human mobility database that stores and manages GPS records from mobile devices used by approximately 1.6 million people throughout Japan from 1 August 2010 to 31 July 2011. By mining this enormous set of Auto-GPS mobile sensor data, the short-term and long-term evacuation behaviors for individuals throughout Japan during this disaster are able to be automatically discovered. To better understand and simulate human mobility during the disasters, we develop a probabilistic model that is able to be effectively trained by the discovered evacuations via machine learning technique. Based on our training model, population mobility in various cities impacted by the disasters throughout the country is able to be automatically simulated or predicted. On the basis of the whole database, developed model, and experimental results, it is easy for us to find some new features or population mobility patterns after the recent severe earthquake, tsunami and release of radioactivity in Japan, which are likely to play a vital role in future disaster relief and management worldwide. The main purpose of this work is to present a formulation of the building evacuation problem that incorporates evacuation routes and applies the functions developed by Nelson and McLennan [H.E. Nelson, H.A. McLennan (Eds.), Emergency Movement, The SFPE Handbook of Fire Protection Engineering, 1996, pp. 3.286-3.295 (Section 3 Chapter 14)] to model the movement of people. These considerations lead to significant changes in the form of the evacuation and inverse evacuation functions, so it is necessary to develop a new procedure for solving the building evacuation problem. Abstract Statistics show that worldwide motor vehicle collisions lead to significant deaths and disabilities as well as substantial financial costs to both society and the individuals involved. Unintended lane departure is a leading cause of road fatalities by the collision. To reduce the number of traffic accidents and to improve driver’s safety lane departure warning (LDW), the system has emerged as a promising tool. Vision-based lane detection and departure warning system has been investigated over two decades. During this period, many different problems related to lane detection and departure warning have been addressed. This paper provides an overview of current LDW system, describing in particular pre-processing, lane models, lane de Ntection techniques and departure warning system. Limb repositioning is necessary for individuals with severe physical disabilities to sustain muscle strength and prevent pressure sores. As robotic technologies become ubiquitous, these tools offer promise to support the repositioning process. However, research has yet to focus on ways in which individuals with severe physical disabilities can control robots for these tasks. This paper presents a study that examines the needs and attitudes of potential users with physical disabilities to control a robotic aid for limb repositioning. Subjects expressed interest in using brain---computer interface (BCI) and speech recognition technologies for purposes of executing robotic tasks. The performance of four subjects controlling arm movements on an avatar through the keyboard, mouse, BCI, and Dragon NaturallySpeaking speech recognition was evaluated. Although BCI and speech technologies may limit physical fatigue, more challenges were faced using BCI and speech conditions compared to the keyboard and mouse. This research promotes accessibility into mainstream robotic technologies and represents the first step in the development of a robotic prototype using a BCI and speech recognition technologies for limb repositioning. A method for requirements analysis is proposed that accounts for individual and personal goals, and the effect of time and context on personal requirements. First a framework to analyse the issues inherent in requirements that change over time and location is proposed. The implications of the framework on system architecture are considered as three implementation pathways: functional specifications, development of customisable features and automatic adaptation by the system. These pathways imply the need to analyse system architecture requirements. A scenario-based analysis method is described for specifying requirements goals and their potential change. The method addresses goal setting for measurement and monitoring, and conflict resolution when requirements at different layers (group, individual) and from different sources (personal, advice from an external authority) conflict. The method links requirements analysis to design by modelling alternative solution pathways. Different implementation pathways have cost–benefit implications for stakeholders, so cost–benefit analysis techniques are proposed to assess trade-offs between goals and implementation strategies. The use of the framework is illustrated with two case studies in assistive technology domains: e-mail and a personalised navigation system. The first case study illustrates personal requirements to help cognitively disabled users communicate via e-mail, while the second addresses personal and mobile requirements to help disabled users make journeys on their own, assisted by a mobile PDA guide. In both case studies the experience from requirements analysis to implementation, requirements monitoring, and requirements evolution is reported. Hajj is one of the largest mass gatherings where Muslims from all over the world gather in Makah each year for pilgrimage. A mass assembly of such scale bears a huge risk of disaster either natural or man-made. In the past few years, thousands of casualties have occurred while performing different Hajj rituals, especially during the Circumambulation of Kaba (Tawaf) due to stampede or chaos. During such calamitous situations, an appropriate evacuation strategy can help resolve the problem and mitigate further risk of causalities. It is however a daunting research problem to identify an optimal course of action based on several constraints. Modeling and analyzing such a problem of real-time and spatially explicit complexity requires a microscale crowd simulation and analysis framework. Which not only allows the modeler to express the spatial dimensions and features of the environment in real scale, but also provides modalities to capture complex crowd behaviors. In this paper, we propose an Agent-based Crowd Simulation & Analysis framework that incorporates the use of Anylogic Pedestrian library and integrates interoperate Anylogic Simulation environment with the external modules for optimization and analysis. Hence provides a runtime environment for analyzing complex situations, e.g., emergency evacuation strategies. The key features of the proposed framework include: (i) Ability to model large crowd in a spatially explicit environment at real-scale; (ii) Simulation of complex crowd behavior such as emergency evacuation; (iii) Interoperability of optimization and analysis modules with simulation runtime for evaluating evacuation strategies. We present a case study of Hajj scenario as a proof of concept and a test bed for identifying and evaluating optimal strategies for crowd evacuation In this paper we present a model based on the parallel computational tool of cellular automata CA capable of simulating the process of disembarking in a small airplane seat layout, corresponding to Airbus A320 Boeing 737 layout, in search of ways to make it faster and safer under normal evacuation conditions, as well as emergency scenarios. The proposed model is highly customizable, with the number of exits, the walking speed of passengers, depending on their sex, age and height, and the effects of retrieving and carrying luggage. Additionally, the presence of obstacles in the aisles as well as the emergence of panic being parameters whose values can be varied in order to enlighten the disembarking and emergency evacuation processes are considered in detail. The simulation results were compared to existing aircraft disembarking and evacuation times and indicate the efficacy of the proposed model in investigating and revealing passenger attributes during these processes in all the examined cases. Moreover, we parallelized our code in order to run on a graphics processing unit GPU using the CUDA programming language, speeding up the simulation process. Finally, in order to present a fully dynamical anticipative real-time system helpful for decision-making we implemented the proposed CA model in a field programmable gate array FPGA device, and recreated the results given by the software simulations in a fraction of the time. We then compared and exported the performance results among a sequential software implementation, the implementation running on a GPU, and a hardware implementation, proving the consequent acceleration that results from the parallel CA implementation in specific hardware. This paper establishes what might be called a "uniformity principle" for building evacuation problems. The principle may be stated as follows: given a building for which each occupant has reasonable access to every evacuation route, if the building is evacuated in minimum time, then the allocation of evacuees to routes is such that the route evacuation times are all the same. That is, there is a uniformity of route evacuation times. Also, analytical expressions for the minimum time to evacuate a building, and for the corresponding allocation of evacuees to routes, are obtained.