{"title":"Route selection based on real time traffic condition using Ant Colony System and fuzzy inference system","authors":"Erick Alfons Lisangan, Sean Coonery Sumarta","doi":"10.1109/ICSITECH.2017.8257087","DOIUrl":null,"url":null,"abstract":"Route selection from the point of origin to destination today is not only considering the shortest distance but also traffic conditions, such as average speed and vehicle intensity. In this research, we propose method of the ant's location selection using Fuzzy Inference System in the Ant Colony System. The location selection not only consider the distance but also the probability of next location. The probability of next location is the output of fuzzy inference system with the input is the traffic conditions between current location and next location. The dataset is data of traffic condition in the area of Aarhus, Denmark. The results show that the route selection is not only based on the distance location but also the traffic condition between locations. The proposed method is expected to be the basis to develop the real-time location searching's application with input coming from sensors by considering the average execution less than one second in finding route.","PeriodicalId":165045,"journal":{"name":"2017 3rd International Conference on Science in Information Technology (ICSITech)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 3rd International Conference on Science in Information Technology (ICSITech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSITECH.2017.8257087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Route selection from the point of origin to destination today is not only considering the shortest distance but also traffic conditions, such as average speed and vehicle intensity. In this research, we propose method of the ant's location selection using Fuzzy Inference System in the Ant Colony System. The location selection not only consider the distance but also the probability of next location. The probability of next location is the output of fuzzy inference system with the input is the traffic conditions between current location and next location. The dataset is data of traffic condition in the area of Aarhus, Denmark. The results show that the route selection is not only based on the distance location but also the traffic condition between locations. The proposed method is expected to be the basis to develop the real-time location searching's application with input coming from sensors by considering the average execution less than one second in finding route.