首页|Data from Beijing University of Technology Advance Knowledge in Intelligent Tran sportation Systems (Modeling Human-like Driving Behavior At a Signal Intersectio n Based On Driver Risk Field Model)
Data from Beijing University of Technology Advance Knowledge in Intelligent Tran sportation Systems (Modeling Human-like Driving Behavior At a Signal Intersectio n Based On Driver Risk Field Model)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Data detailed on Transportation - Intelligent Tra nsportation Systems have been presented. According to news reporting originating from Beijing, People’s Republic of China, by NewsRx correspondents, research st ated, “Autonomous intersection management systems aim to efficiently control con nected and autonomous vehicles at urban intersections. However, current driving behavior models face challenges in accurately capturing the distinctive human dr iver characteristics specific to intersection interactions.” Financial supporters for this research include National Key Research & Development Program of China, China Postdoctoral Science Foundation. Our news editors obtained a quote from the research from the Beijing University of Technology, “This article introduces a human-like driving behavior model base d on the driver’s risk field (DRF) for intersection scenarios. The DRF represent s the driver’s belief regarding the likelihood of an event occurring, and the as sociated cost function is determined by the consequences of said event. A drivin g simulation experiment was conducted at a signalized intersection to evaluate t he model, and the results were compared with a human-like driving behavior model . The results show that the proposed model has a high degree of fit.”
BeijingPeople’s Republic of ChinaAsi aIntelligent Transportation SystemsTransportationBeijing University of Tec hnology
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