{"title":"A Driver Lateral and Longitudinal Control Model Based on Queuing Network Cognitive Architecture","authors":"Luzheng Bi, Cuie Wang, Xuerui Yang","doi":"10.1109/GCIS.2013.50","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new computational model of driver car-following control with lateral control based on the Queuing Network (QN) cognitive architecture. A driver car-following model within the framework of the QN cognitive architecture is first developed based on the time headway and then integrated with a QN-based driver lateral control model previously validated. The comparison between human driver data and the integrated model simulation data suggests that this computational model can perform car-following control with lateral control well, and its performance is in agreement with that of drivers under straight and curved roads. This proposed model can compute and simulate car-following behavior and thus has the potential to help develop driver assistance systems for the car-following scenario.","PeriodicalId":366262,"journal":{"name":"2013 Fourth Global Congress on Intelligent Systems","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth Global Congress on Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GCIS.2013.50","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
In this paper, we propose a new computational model of driver car-following control with lateral control based on the Queuing Network (QN) cognitive architecture. A driver car-following model within the framework of the QN cognitive architecture is first developed based on the time headway and then integrated with a QN-based driver lateral control model previously validated. The comparison between human driver data and the integrated model simulation data suggests that this computational model can perform car-following control with lateral control well, and its performance is in agreement with that of drivers under straight and curved roads. This proposed model can compute and simulate car-following behavior and thus has the potential to help develop driver assistance systems for the car-following scenario.
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