Md Abdus Samad Kamal, M. Mukai, J. Murata, T. Kawabe
{"title":"On board eco-driving system for varying road-traffic environments using model predictive control","authors":"Md Abdus Samad Kamal, M. Mukai, J. Murata, T. Kawabe","doi":"10.1109/CCA.2010.5611196","DOIUrl":null,"url":null,"abstract":"This paper presents model predictive control of a vehicle in a varying road-traffic environment for ecological (eco) driving. The vehicle control input is derived by rigorous reasoning approach of model based anticipation of road, traffic and fuel consumption in a crowded road network regulated by traffic signals. Model predictive control with Continuation and generalized minimum residual method for optimization is used to calculate the sequence of control inputs aiming at long run fuel economy maintaining a safe driving. Performance of the proposed eco-driving system is evaluated through simulations in AIMSUN microscopic transport simulator. In spite of nonlinearity and discontinuous movement of other traffic and signals, the proposed system is robust enough to control the vehicle safely. The driving behavior with fuel saving aspects is graphically illustrated, compared and analyzed to signify the prospect of the proposed eco-driving of a vehicle.","PeriodicalId":284271,"journal":{"name":"2010 IEEE International Conference on Control Applications","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"87","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Control Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCA.2010.5611196","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 87
Abstract
This paper presents model predictive control of a vehicle in a varying road-traffic environment for ecological (eco) driving. The vehicle control input is derived by rigorous reasoning approach of model based anticipation of road, traffic and fuel consumption in a crowded road network regulated by traffic signals. Model predictive control with Continuation and generalized minimum residual method for optimization is used to calculate the sequence of control inputs aiming at long run fuel economy maintaining a safe driving. Performance of the proposed eco-driving system is evaluated through simulations in AIMSUN microscopic transport simulator. In spite of nonlinearity and discontinuous movement of other traffic and signals, the proposed system is robust enough to control the vehicle safely. The driving behavior with fuel saving aspects is graphically illustrated, compared and analyzed to signify the prospect of the proposed eco-driving of a vehicle.