{"title":"A ROUTING MODEL FOR EMERGENCY VEHICLES USING THE REAL TIME TRAFFIC DATA","authors":"N. Rathore, P. Jain, M. Parida","doi":"10.1109/SOLI.2018.8476771","DOIUrl":null,"url":null,"abstract":"In India, many semi-government emergency medical services (EMS) exist; one of them is 108 which operate in several states of the country. The efficiency of EMS depends on its timely responsiveness to the demand and the integration of available real time travel/traffic data into the vehicle scheduling and routing model. This paper focuses on designing the routes for emergency vehicles by developing an optimization model based on the available knowledge of real time traffic information using the Google Maps Distance Matrix API. The heuristic approach involves formulation of the vehicle routing problem as an integer programming model and optimizing it by integrating with Google API. The main components of the model are incident location, vehicle tracking, shortest path finding and dispatch optimization. This simulation strategy is validated by various samples and a series of tests.","PeriodicalId":424115,"journal":{"name":"2018 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOLI.2018.8476771","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
In India, many semi-government emergency medical services (EMS) exist; one of them is 108 which operate in several states of the country. The efficiency of EMS depends on its timely responsiveness to the demand and the integration of available real time travel/traffic data into the vehicle scheduling and routing model. This paper focuses on designing the routes for emergency vehicles by developing an optimization model based on the available knowledge of real time traffic information using the Google Maps Distance Matrix API. The heuristic approach involves formulation of the vehicle routing problem as an integer programming model and optimizing it by integrating with Google API. The main components of the model are incident location, vehicle tracking, shortest path finding and dispatch optimization. This simulation strategy is validated by various samples and a series of tests.