Dalibor Procházka, V Šedivcová, J Melichar, A Tesař, H Schvach
{"title":"用于医疗后送的自主地面车辆:基于主体建模的能力评估。","authors":"Dalibor Procházka, V Šedivcová, J Melichar, A Tesař, H Schvach","doi":"10.1136/military-2024-002885","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Medical evacuation (MEDEVAC) is a crucial component of military healthcare, and the time during which evacuation of the wounded, injured and ill individuals happens is one of the most critical factors. The article focuses on the initial phase of ground evacuation from the Point of Injury to the casualty collection point (CCP). Casualty transport is the combat unit's task, triggered by a 9-liner MEDEVAC request. Two variants are considered: evacuation by means of one armoured vehicle per CCP according to the actual doctrine and potential evacuation using a fleet of autonomous unmanned vehicles.</p><p><strong>Methods: </strong>The analysis and comparison are based on data (injury time and position) obtained from computer-assisted exercises, and a simulation combining agent-based modelling and discrete events simulation methods is applied to compare two approaches.</p><p><strong>Results: </strong>The simulation results show that using distributed transport capability, represented by unmanned ground vehicles (UGVs), is more effective because it allows for prioritising casualties based on the injury category. The evacuation effectiveness is quantified in relation to the number of UGVs used.</p><p><strong>Conclusions: </strong>The use of UGVs can improve the care of the wounded, assuming the involvement of advanced technologies, including artificial intelligence. Information about the time and place of casualties is the key for decision makers to achieve the benefit, which should be ensured through potential monitoring of the physical condition of the wounded (body sensors and data transmission in case of injury).</p>","PeriodicalId":48485,"journal":{"name":"Bmj Military Health","volume":" ","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Autonomous ground vehicles for MEDEVAC: capability assessment based on agent-based modelling.\",\"authors\":\"Dalibor Procházka, V Šedivcová, J Melichar, A Tesař, H Schvach\",\"doi\":\"10.1136/military-2024-002885\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Medical evacuation (MEDEVAC) is a crucial component of military healthcare, and the time during which evacuation of the wounded, injured and ill individuals happens is one of the most critical factors. The article focuses on the initial phase of ground evacuation from the Point of Injury to the casualty collection point (CCP). Casualty transport is the combat unit's task, triggered by a 9-liner MEDEVAC request. Two variants are considered: evacuation by means of one armoured vehicle per CCP according to the actual doctrine and potential evacuation using a fleet of autonomous unmanned vehicles.</p><p><strong>Methods: </strong>The analysis and comparison are based on data (injury time and position) obtained from computer-assisted exercises, and a simulation combining agent-based modelling and discrete events simulation methods is applied to compare two approaches.</p><p><strong>Results: </strong>The simulation results show that using distributed transport capability, represented by unmanned ground vehicles (UGVs), is more effective because it allows for prioritising casualties based on the injury category. The evacuation effectiveness is quantified in relation to the number of UGVs used.</p><p><strong>Conclusions: </strong>The use of UGVs can improve the care of the wounded, assuming the involvement of advanced technologies, including artificial intelligence. Information about the time and place of casualties is the key for decision makers to achieve the benefit, which should be ensured through potential monitoring of the physical condition of the wounded (body sensors and data transmission in case of injury).</p>\",\"PeriodicalId\":48485,\"journal\":{\"name\":\"Bmj Military Health\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2025-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bmj Military Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1136/military-2024-002885\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bmj Military Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1136/military-2024-002885","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Autonomous ground vehicles for MEDEVAC: capability assessment based on agent-based modelling.
Introduction: Medical evacuation (MEDEVAC) is a crucial component of military healthcare, and the time during which evacuation of the wounded, injured and ill individuals happens is one of the most critical factors. The article focuses on the initial phase of ground evacuation from the Point of Injury to the casualty collection point (CCP). Casualty transport is the combat unit's task, triggered by a 9-liner MEDEVAC request. Two variants are considered: evacuation by means of one armoured vehicle per CCP according to the actual doctrine and potential evacuation using a fleet of autonomous unmanned vehicles.
Methods: The analysis and comparison are based on data (injury time and position) obtained from computer-assisted exercises, and a simulation combining agent-based modelling and discrete events simulation methods is applied to compare two approaches.
Results: The simulation results show that using distributed transport capability, represented by unmanned ground vehicles (UGVs), is more effective because it allows for prioritising casualties based on the injury category. The evacuation effectiveness is quantified in relation to the number of UGVs used.
Conclusions: The use of UGVs can improve the care of the wounded, assuming the involvement of advanced technologies, including artificial intelligence. Information about the time and place of casualties is the key for decision makers to achieve the benefit, which should be ensured through potential monitoring of the physical condition of the wounded (body sensors and data transmission in case of injury).