{"title":"Artificial-intelligent-powered safety and efficiency improvement for controlling and scheduling in integrated railway systems","authors":"Jun Liu , Gehui Liu , Yu Wang , Wanqiu Zhang","doi":"10.1016/j.hspr.2024.06.002","DOIUrl":null,"url":null,"abstract":"<div><div>The multi-mode integrated railway system, anchored by the high-speed railway, caters to the diverse travel requirements both within and between cities, offering safe, comfortable, punctual, and eco-friendly transportation services. With the expansion of the railway networks, enhancing the efficiency and safety of the comprehensive system has become a crucial issue in the advanced development of railway transportation. In light of the prevailing application of artificial intelligence technologies within railway systems, this study leverages large model technology characterized by robust learning capabilities, efficient associative abilities, and linkage analysis to propose an Artificial-intelligent (AI)-powered railway control and dispatching system. This system is elaborately designed with four core functions, including global optimum unattended dispatching, synergetic transportation in multiple modes, high-speed automatic control, and precise maintenance decision and execution. The deployment pathway and essential tasks of the system are further delineated, alongside the challenges and obstacles encountered. The AI-powered system promises a significant enhancement in the operational efficiency and safety of the composite railway system, ensuring a more effective alignment between transportation services and passenger demands.</div></div>","PeriodicalId":100607,"journal":{"name":"High-speed Railway","volume":"2 3","pages":"Pages 172-179"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"High-speed Railway","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949867824000473","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The multi-mode integrated railway system, anchored by the high-speed railway, caters to the diverse travel requirements both within and between cities, offering safe, comfortable, punctual, and eco-friendly transportation services. With the expansion of the railway networks, enhancing the efficiency and safety of the comprehensive system has become a crucial issue in the advanced development of railway transportation. In light of the prevailing application of artificial intelligence technologies within railway systems, this study leverages large model technology characterized by robust learning capabilities, efficient associative abilities, and linkage analysis to propose an Artificial-intelligent (AI)-powered railway control and dispatching system. This system is elaborately designed with four core functions, including global optimum unattended dispatching, synergetic transportation in multiple modes, high-speed automatic control, and precise maintenance decision and execution. The deployment pathway and essential tasks of the system are further delineated, alongside the challenges and obstacles encountered. The AI-powered system promises a significant enhancement in the operational efficiency and safety of the composite railway system, ensuring a more effective alignment between transportation services and passenger demands.