{"title":"Route planning in asymmetric military environments","authors":"T. Ruuben, Ove Kreison","doi":"10.1109/FGCT.2013.6767187","DOIUrl":null,"url":null,"abstract":"Current article gives an overview of how situation aware route planning can be used for improving route planning tasks in urban military operations. Unlike conventional route planning tasks that are usually used for finding shortest routes, present approach uses multiple parameters and categories for describing asymmetric threats emanating from surrounding urban environments and planning routes. These parameters can be combined together to find routes with different properties. Multiple tests were performed using A* and genetic algorithm to present how different parameter values and their combinations affect output routes and how different threats can be avoided by taking those parameters into account. Tests showed that both algorithms can be used for route planning, but A* would be the recommended choice, because the probability of it finding the global optimum is larger.","PeriodicalId":200083,"journal":{"name":"Second International Conference on Future Generation Communication Technologies (FGCT 2013)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Second International Conference on Future Generation Communication Technologies (FGCT 2013)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FGCT.2013.6767187","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Current article gives an overview of how situation aware route planning can be used for improving route planning tasks in urban military operations. Unlike conventional route planning tasks that are usually used for finding shortest routes, present approach uses multiple parameters and categories for describing asymmetric threats emanating from surrounding urban environments and planning routes. These parameters can be combined together to find routes with different properties. Multiple tests were performed using A* and genetic algorithm to present how different parameter values and their combinations affect output routes and how different threats can be avoided by taking those parameters into account. Tests showed that both algorithms can be used for route planning, but A* would be the recommended choice, because the probability of it finding the global optimum is larger.