This paper explores the idea of smart building evacuation when evacuees can belong to different categories with respect to their ability to move and their health conditions. This leads to new algorithms that use the Cognitive Packet Network concept to tailor different quality of service needs to different evacuees. These ideas are implemented in a simulated environment and evaluated with regard to their effectiveness.
Much research in emergency navigation focuses on normal'' individuals with identical physical attributes such as mobility and health level, and conventional models such as flow-based models @cite_0 @cite_5 @cite_4 @cite_14 @cite_31 @cite_27 hypothesise evacuees as continuous homogeneous flows. Potential-maintenance approaches @cite_32 @cite_25 @cite_22 @cite_15 concentrate on the navigation algorithms that do not take the physical attributes of evacuees into account. The magnetic model'' in @cite_34 sets a walking velocity for each evacuee but ignores personal requirements as well as the effect of social interaction. The advent of multi-agent models makes it more convenient to customise physical attributes for individuals. However, previous work has focused on incorporating sociological factors due to the easiness of describing social behaviours such as coordination or stampede. Although in @cite_10 physical, psychological and moving attributes are considered for each evacuee, health factors such as initial health values and resistance to hazard which are influenced by gender, age, etc. are not considered. Queueing models can also be used to evaluate congestion in such systems @cite_13 @cite_7 .
@cite_13 @cite_14 @cite_4 @cite_22 @cite_7 @cite_15 @cite_32 @cite_0 @cite_27 @cite_5 @cite_31 @cite_34 @cite_10 @cite_25
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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. 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. We report that human walk patterns contain statistically similar features observed in Levy walks. These features include heavy-tail flight and pause-time distributions and the super-diffusive nature of mobility. Human walks are not random walks, but it is surprising that the patterns of human walks and Levy walks contain some statistical similarity. Our study is based on 226 daily GPS traces collected from 101 volunteers in five different outdoor sites. The heavy-tail flight distribution of human mobility induces the super-diffusivity of travel, but up to 30 min to 1 h due to the boundary effect of people's daily movement, which is caused by the tendency of people to move within a predefined (also confined) area of daily activities. These tendencies are not captured in common mobility models such as random way point (RWP). To evaluate the impact of these tendencies on the performance of mobile networks, we construct a simple truncated Levy walk mobility (TLW) model that emulates the statistical features observed in our analysis and under which we measure the performance of routing protocols in delay-tolerant networks (DTNs) and mobile ad hoc networks (MANETs). The results indicate the following. Higher diffusivity induces shorter intercontact times in DTN and shorter path durations with higher success probability in MANET. The diffusivity of TLW is in between those of RWP and Brownian motion (BM). Therefore, the routing performance under RWP as commonly used in mobile network studies and tends to be overestimated for DTNs and underestimated for MANETs compared to the performance under TLW. The objective of this study is the development of a computer simulation model for pedestrian movement in architectural and urban space. The characteristic of the model is the ability to visualize the movement of each pedestrian in a plan as an animation. So architects and designers can easily find and understand the problems in their design projects. In this model, the movement of each pedestrian is simulated by the motion of a magnetized object in a magnetic field. Positive magnetic pole is given to each pedestrian and obstacles like walls and columns. Negative magnetic pole is located at the goal of pedestrians. Each pedestrian moves to his goal by the attractive force caused by the negative magnetic pole at his goal, avoiding collisions with other pedestrians and obstacles by repulsive forces caused by the positive magnetic poles. The effectiveness of the simulation model is shown by the following two kinds of simulation examples. (1) Evacuation from an office building In this model pedestrians walk along the route from each starting point to the exit in case of evacuation. The example shows the places where stagnations and heavy congestions occur, and designers can see if the evacuation routes are appropriate. (2) Movement of pedestrians in queue spaces Three types of queuing behavior is classified in this model: movement in front of counters, movement passing through ratches, and movement of getting on and off in elevator halls. Simulation examples in a railway station and in a main floor of a resort hotel are shown where several kinds of queue spaces are included and complicated movements of hundreds of pedestrians occur.