Stochastic Parameter Identification Method for Driving Trajectory Simulation Processes Based on Mobile Edge Computing and Self-Organizing Feature Mapping | |
Yang JF(杨敬锋)6,7,8; Luo, Zhiyong6; Zhang, Nanfeng5; Xiao JC(肖金超)7,8; Wang, Honggang4; Zhou, Shengpei7,8; Liu, Xiaosong3; Li, Ming1,2 | |
刊名 | Complexity |
2021 | |
卷号 | 2021页码:1-8 |
ISSN号 | 1076-2787 |
产权排序 | 1 |
英文摘要 | With the rapid development of sensor technology for automated driving applications, the fusion, analysis, and application of multimodal data have become the main focus of different scenarios, especially in the development of mobile edge computing technology that provides more efficient algorithms for realizing the various application scenarios. In the present paper, the vehicle status and operation data were acquired by vehicle-borne and roadside units of electronic registration identification of motor vehicles. In addition, a motion model and an identification system for the single-vehicle lane-change process were established by mobile edge computing and self-organizing feature mapping. Two scenarios were modeled and tested: lane change with no vehicles in the target lane and lane change with vehicles in the target lane. It was found that the proposed method successfully identified the stochastic parameters in the process of driving trajectory simulation, and the standard deviation between simulation and the measured results obeyed a normal distribution. The proposed methods can provide significant practical information for improving the data processing efficiency in automated driving applications, for solving single-vehicle lane-change applications, and for promoting the formation of a closed loop from sensing to service. |
资助项目 | National Key Research and Development Program[2017YFD0700602] ; Key Research and Development Plan of Shaanxi Province[2018ZDXM-GY-041] ; Foshan Entrepreneurship and Innovation Team Project[2017IT100032] |
WOS研究方向 | Mathematics ; Science & Technology - Other Topics |
语种 | 英语 |
WOS记录号 | WOS:000611823000007 |
资助机构 | National Key Research and Development Program [2017YFD0700602] ; Key Research and Development Plan of Shaanxi Province [2018ZDXM-GY-041] ; Foshan Entrepreneurship and Innovation Team Project [2017IT100032] |
内容类型 | 期刊论文 |
源URL | [http://ir.sia.cn/handle/173321/28312] |
专题 | 沈阳自动化研究所_广州中国科学院沈阳自动化研究所分所 |
通讯作者 | Luo, Zhiyong; Li, Ming |
作者单位 | 1.South China Agricultural University, Guangzhou 510642, China 2.Yaz Technology Co., Ltd., Guangzhou 510630, China 3.Guangdong Zhongke Zhenheng Information Technology Co., Ltd, Foshan 528225, China 4.School of Communications and Information Engineering, Xi'An University of Posts and Telecommunications, Xi'an 710061, China 5.Huangpu Customs District Technical Center, Guangzhou 510730, China 6.School of Electronics and Communication Engineering, Sun Yat-Sen University, Guangzhou 510006, China 7.Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang 110016, China 8.Shenyang Institute of Automation Chinese (Guangzhou) Academy of Sciences, Guangzhou 511458, China |
推荐引用方式 GB/T 7714 | Yang JF,Luo, Zhiyong,Zhang, Nanfeng,et al. Stochastic Parameter Identification Method for Driving Trajectory Simulation Processes Based on Mobile Edge Computing and Self-Organizing Feature Mapping[J]. Complexity,2021,2021:1-8. |
APA | Yang JF.,Luo, Zhiyong.,Zhang, Nanfeng.,Xiao JC.,Wang, Honggang.,...&Li, Ming.(2021).Stochastic Parameter Identification Method for Driving Trajectory Simulation Processes Based on Mobile Edge Computing and Self-Organizing Feature Mapping.Complexity,2021,1-8. |
MLA | Yang JF,et al."Stochastic Parameter Identification Method for Driving Trajectory Simulation Processes Based on Mobile Edge Computing and Self-Organizing Feature Mapping".Complexity 2021(2021):1-8. |
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