Evacuee routing algorithms in emergency typically adopt one single criterion to compute desired paths and ignore the specific requirements of users caused by different physical strength, mobility and level of resistance to hazard. In this paper, we present a quality of service (QoS) driven multi-path routing algorithm to provide diverse paths for different categories of evacuees. This algorithm borrows the concept of Cognitive Packet Network (CPN), which is a flexible protocol that can rapidly solve optimal solution for any user-defined goal function. Spatial information regarding the location and spread of hazards is taken into consideration to avoid that evacuees be directed towards hazardous zones. Furthermore, since previous emergency navigation algorithms are normally insensitive to sudden changes in the hazard environment such as abrupt congestion or injury of civilians, evacuees are dynamically assigned to several groups to adapt their course of action with regard to their on-going physical condition and environments. Simulation results indicate that the proposed algorithm which is sensitive to the needs of evacuees produces better results than the use of a single metric. Simulations also show that the use of dynamic grouping to adjust the evacuees' category and routing algorithms with regard for their on-going health conditions and mobility, can achieve higher survival rates.
The notion of effective length'' @cite_27 calculated as the product of the physical length and the hazard intensity, together with Dijkstra's algorithm can compute the best path to exits @cite_0 @cite_18 , and can include @cite_22 information about the spatial hazard. The Uniformity principle'' @cite_14 is also useful in showing that proper allocation of evacuees to routes, such that all exit routes have the same clearance time, is essential in minimizing evacuation time @cite_6 , while in @cite_2 @cite_4 network flow models mimic evacuation planning problems and convert the original network to time-expended networks. To reduce the high computational cost caused of these linear programming methods, in @cite_26 the Cognitive Packet Network is used for route discovery.
@cite_18 @cite_14 @cite_4 @cite_22 @cite_26 @cite_6 @cite_0 @cite_27 @cite_2
2462610560 2332141129 2951006828 2074026287 1874038193 2150843819 2027465986
Information systems that provide decision support in an efficient and timely manner can prove beneficial for emergency response operations. In this paper we propose the use of a system that provides movement decision support to evacuees by directing them through the shortest or less hazardous routes to the exit and evaluate it with a specialised software platform that we have developed for simulation of disasters in buildings. The system operates in a distributed manner, and computes the best evacuation routes in real-time while a hazard is spreading inside the building. It 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 use a multi-agent simulation platform for Building Evacuation that we developed, in order to evaluate our proposed system in various emergency scenarios. Our simulation results show that the overall outcome of the evacuation procedure is improved when the decision support system is in operation. 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. Exit paths in buildings are designed to minimise evacuation time when the building is at full capacity. We present an evacuation support system which does this regardless of the number of evacuees. The core concept is to even-out congestion in the building by diverting evacuees to less-congested paths in order to make maximal usage of all accessible routes throughout the entire evacuation process. The system issues a set of flow-optimal routes using a capacity-constrained routing algorithm which anticipates evolutions in path metrics using the concept of "future capacity reservation". In order to direct evacuees in an intuitive manner whilst implementing the routing algorithm's scheme, we use dynamic exit signs, i.e. whose pointing direction can be controlled. To make this system practical and minimise reliance on sensors during the evacuation, we use an evacuee mobility model and make several assumptions on the characteristics of the evacuee flow. We validate this concept using simulations, and show how the underpinning assumptions may limit the system's performance, especially in low-headcount evacuations. 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. Emergency response operations can benefit from the use of information systems that reduce decision making time and facilitate co-ordination between the participating units. We propose the use of two such systems and evaluate them with a specialised software platform that we have developed for simulation of disasters in buildings. The first system provides movement decision support to evacuees by directing them through the shortest or less hazardous routes to the exit. It is composed of a network of decision nodes and sensor nodes, positioned at specific locations inside the building. The recommendations of the decision nodes are computed in a distributed manner and communicated to the evacuees or rescue personnel in their vicinity. The second system uses wireless-equipped robots that move inside a disaster area and establish a network for two-way communication between trapped civilians and rescuers. They are autonomous and their goal is to maximise the number of civilians connected to the network. We evaluate both proposed information systems in various emergency scenarios, using the specialised simulation software that we developed. 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.