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  • 标题:Research on the Impacts of Generalized Preceding Vehicle Information on Traffic Flow in V2X Environment
  • 本地全文:下载
  • 作者:Xiaoyuan Wang ; Junyan Han ; Chenglin Bai
  • 期刊名称:Future Internet
  • 电子版ISSN:1999-5903
  • 出版年度:2021
  • 卷号:13
  • 期号:4
  • 页码:88
  • DOI:10.3390/fi13040088
  • 出版社:MDPI Publishing
  • 摘要:With the application of vehicles to everything (V2X) technologies, drivers can obtain massive traffic information and adjust their car-following behavior according to the information. The macro-characteristics of traffic flow are essentially the overall expression of the micro-behavior of drivers. There are some shortcomings in the previous researches on traffic flow in the V2X environment, which result in difficulties to employ the related models or methods in exploring the characteristics of traffic flow affected by the information of generalized preceding vehicles (GPV). Aiming at this, a simulation framework based on the car-following model and the cellular automata (CA) is proposed in this work, then the traffic flow affected by the information of GPV is simulated and analyzed utilizing this framework. The research results suggest that the traffic flow, which is affected by the information of GPV in the V2X environment, would operate with a higher value of velocity, volume as well as jamming density and can maintain the free flow state with a much higher density of vehicles. The simulation framework constructed in this work can provide a reference for further research on the characteristics of traffic flow affected by various information in the V2X environment.
  • 关键词:traffic flow; V2X environment; cellular automata; car-following model; numerical simulation traffic flow ; V2X environment ; cellular automata ; car-following model ; numerical simulation
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