The Impact of Sea Level Rise on Roadway Design and Evacuation Routes in Delaware

As the global temperature continues to increase, the sea level continues to rise at a rapid rate that has never been seen before. This becomes an issue for many facets of life but one of the most impacted is the transportation infrastructure. Many people living in low elevation coastal areas can become trapped by flooding with no way in or out. With Delaware being a coastal state, this would affect a large portion of the population and will have detrimental effects over time if nothing is done to combat sea level rise. The issue with sea level rise in transportation is that once the roads become flooded, they become virtually unusable and detour routes would be needed. If all the roads in a coastal area were to be affected by sea level rise, the options for detours would become limited. This article looks at direct solutions to combat sea level rise and indirect solutions that would specifically help transportation infrastructure and evacuation routes in Delaware. There is not one solution that can fix every problem, so many solutions are laid out to see what is applicable to each affected area. Some solutions include defense structures that would be put close to the coast, raising the elevation of vulnerable roads throughout the state and including pumping stations to drain the water on the surface of the road. With an understanding of all these solutions around the world, the ultimate conclusion came in the form of a six-step plan that Delaware should take in order to best design against sea level rise in these coastal areas.

Safety Evaluation Method of Evacuation Routes in Areas in Case of Earthquake Disasters Using Ant Optimization Algorithm and Geographic Information Systems

The present study aims to propose the method for the quantitative evaluation of safety concerning evacuation routes in case of earthquake disasters in urban areas using ACO （Ant Colony Optimization） algorithm and GIS （Geographic Information Systems）. Regarding the safety evaluation method, firstly, the similarity in safety was focused on while taking into consideration road blockage probability, and after classifying roads by means of the hierarchical cluster analysis, the congestion rates of evacuation routes using ACO simulations were estimated. Based on these results, the multiple evacuation routes extracted were visualized on digital maps by means of GIS, and its safety was evaluated. Furthermore, the selection of safe evacuation routes between evacuation sites, for cases when the possibility of large-scale evacuation after an earthquake disaster is high, is made possible. As the safety evaluation method is based on public information, by obtaining the same geographic information as the present study, it is effective in other areas regardless of whether the information is of the past and future. Therefore, in addition to spatial reproducibility, the safety evaluation method also has high temporal reproducibility. Because safety evaluations are conducted on evacuation routes based on quantified data, highly safe evacuation routes that are selected have been quantitatively evaluated, and thus serve as an effective indicator when selecting evacuation routes.

Search Methods for Evacuation Routes during Torrential Rain Disasters Using Genetic Algorithms and GIS

The present study aims to propose a method to search for the most appropriate evacuation routes that take calorie consumption required for evacuees to reach evacuation sites into consideration, by focusing on disasters caused by heavy rainfall, and using genetic algorithm (GA) and geographic information system (GIS). Specifically, GA was used to design and develop an evacuation route search algorithm and 4 parameters including the number of generations, mutation rate number of individuals and crossover rate were set by conducting sensitivity analyses. Additionally, GIS was also used to create road network data and contour data for digital maps and calculate the altitude of each crossover point. Based on these, the necessary calorie consumption to reach evacuation sites for each route was calculated, and that made it possible to derive the several evacuation routes with the small values unlike other methods. By using GA and GIS to suggest detailed evacuation routes, which take the necessary calories required to reach evacuation sites into consideration, it can be expected that the present study should contribute to the decision-making of evacuees. Additionally, as the method is based on public information, the method has high spatial and temporal repeatability. Because evacuation routes are proposed based on quantified data, the selected evacuation routes are quantitatively evaluated, and are an effective indicator for deciding on an evacuation route. Additionally, evacuation routes that accurately reflect current conditions can be derived by utilizing detailed information as data.

Optimal Evacuation Scheme Based on Dam-Break Flood Numerical Simulation

The optimal evacuation scheme is studied based on the dam-break flood numerical simulation. A three- dimensional dam-break mathematical model combined with the volume of fluid （VOF） method is adopted. According to the hydraulic information obtained from numerical simulation and selecting principles of evacuation emergency scheme, evacuation route analysis model is proposed, which consists of the road right model and random degree model. The road right model is used to calculate the consumption time in roads, and the random degree model is used to judge whether the roads are blocked. Then the shortest evacuation route is obtained based on Dijstra algorithm. Gongming Reservoir located in Shenzhen is taken as a case to study. The results show that industrial area I is flooded at 2 500 s, and after 5 500 s, most of industrial area II is submerged. The Hushan, Loucun Forest and Chaishan are not flooded around industrial area I and II. Based on the above analysis, the optimal evacuation scheme is determined.

Intelligent fire information system based on 3D GIS

Background This work aims to build a comprehensive and effective fire emergency management system based on the Internet of Things(IoT)and achieve an actual intelligent fire rescue.A smart fire protection information system was designed based on the IoT.A detailed analysis was conducted on the problem of rescue vehicle scheduling and the evacuation of trapped persons in the process of fire rescue.Methods The intelligent fire visualization platform based on the three-dimensional(3D)Geographic Information Science(GIS)covers project overview,equipment status,equipment classification,equipment alarm information,alarm classification,alarm statistics,equipment account information,and other modules.The live video accessed through the visual interface can clearly identify the stage of the fire,which facilitates the arrangement of rescue equipment and personnel.The vehicle scheduling model in the system primarily used two objective functions to solve the Pareto Non-Dominated Solution Set Optimization:emergency rescue time and the number of vehicles.In addition,an evacuation path optimization method based on the Improved Ant Colony(IAC)algorithm was designed to realize the dynamic optimization of building fire evacuation paths.Results The experimental results indicate that all the values of detection signals were significantly larger in the smoldering fire scene at t=17s than the initial value.In addition,the probability of smoldering fire and the probability of open fire were relatively large according to the probability function of the corresponding fire situation,demonstrating that this model could detect fire.Conclusions The IAC algorithm reported here avoided the passages near the fire and spreading areas as much as possible and took the safety of the trapped persons as the premise when planning the evacuation route.Therefore,the IoT-based fire information system has important value for ensuring fire safety and carrying out emergency rescue and is worthy of popularization and application.