{"title":"Comparative study of different Fuzzy-Neural configurations for autonomous vehicle following algorithm","authors":"John Paolo A. Ramoso, M. Ramos","doi":"10.1109/ICCSCE.2016.7893609","DOIUrl":null,"url":null,"abstract":"This paper investigates modelling vehicle following using Fuzzy-Neural Network (FNN). Architecture, training sets, and learning rate are manipulated to create 24 combinations of FNN. Generating two sets of weights per combination yields 48 simulations. Acceleration and deceleration profiles from seven electrical tricycles are observed while navigating through the University of the Philippines. A force equation has been applied to simulate vehicular dynamics. Each combination is then subjected to test run simulations to examine vehicular reactions to distance maintenance, velocity matching, and change in applied force to the vehicle. Results show that two 2 hidden layer FN and two NN allow a vehicle to successfully follow a lead vehicle.","PeriodicalId":6540,"journal":{"name":"2016 6th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"19 1","pages":"413-418"},"PeriodicalIF":0.0000,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 6th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSCE.2016.7893609","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper investigates modelling vehicle following using Fuzzy-Neural Network (FNN). Architecture, training sets, and learning rate are manipulated to create 24 combinations of FNN. Generating two sets of weights per combination yields 48 simulations. Acceleration and deceleration profiles from seven electrical tricycles are observed while navigating through the University of the Philippines. A force equation has been applied to simulate vehicular dynamics. Each combination is then subjected to test run simulations to examine vehicular reactions to distance maintenance, velocity matching, and change in applied force to the vehicle. Results show that two 2 hidden layer FN and two NN allow a vehicle to successfully follow a lead vehicle.
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