标题:Transformation mechanism of vehicle cluster situations under dynamic evolution of driver's propensity
作者:Wang, Xiaoyuan; Liu, Yaqi; Guo, Yongqing; Xia, Yuanyuan; Wu, Chaozhong
作者机构:[Wang, Xiaoyuan; Xia, Yuanyuan] Qingdao Univ Sci & Technol, Coll Electromech Engn, Qingdao 266000, Shandong, Peoples R China.; [Liu, Yaqi; Guo, Yong 更多
通讯作者:Wang, XY;Wang, Xiaoyuan
通讯作者地址:[Wang, XY]Qingdao Univ Sci & Technol, Coll Electromech Engn, Qingdao 266000, Shandong, Peoples R China.
来源:TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR
出版年:2019
卷:65
页码:665-684
DOI:10.1016/j.trf.2018.08.011
关键词:Vehicle cluster situation; Driver's propensity; Transfer mechanism;; Traffic state prediction
摘要:The vehicle cluster situation is a kind of dynamic arrangement of a target vehicle and the surrounding vehicles during driving. Revealing the transfer mechanism of vehicle clustering in complex environments is of great significant for studying automated driving systems and driver assist systems. Taking three-lane scenario as an example, vehicle cluster situations changing with driver's evolving propensity were studied. To this end, the data of vehicle cluster situations were collected and analyzed through driving experiments in different environments. In addition, the dual random variations of the vehicle cluster situation and driver's propensity were modeled to explore the transfer mechanism. The verification results show that the predicted outcomes of vehicle cluster situations using the evolution rule of driver's propensity are consistent with the real-time recognition. Therefore, the transfer mechanism of vehicle cluster situations was found to be effective and reasonable. It is important for the research of intelligent driving command system of Internet of Things (IOT). (C) 2018 Elsevier Ltd. All rights reserved.
收录类别:EI;SSCI
WOS核心被引频次:1
资源类型:期刊论文
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