| 智能网联车即插即用组网模型及决策融合算法 |
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| 引用本文： | 周晓春,梁军,陈龙,王亚飞,龚进峰. 智能网联车即插即用组网模型及决策融合算法[J]. 中国机械工程, 2021, 32(16): 1983-1993. DOI: 10.3969/j.issn.1004-132X.2021.16.011 |
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| 作者姓名： | 周晓春 梁军 陈龙 王亚飞 龚进峰 |
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| 作者单位： | 1.江苏大学汽车工程研究院,镇江,2120132.上海交通大学机械与动力工程学院,上海,2002403.中国汽车技术研究中心汽车工程研究院,天津,300300 |
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| 基金项目： | 国家重点研发计划(2017YFB0102503);国家自然科学基金(U1664258,51875255,61601203);江苏省高等学校自然科学研究重大项目(18KJA580002) |
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| 摘 要： | 针对智能网联车(ICV)多传感器融合前组网流程繁琐的问题,提出了一种车载即插即用(PnP)环境感知传感器自搜索(SS)-自识别(SI)-自标定(SC)组网模型(简称S-SIC).采用深度优先搜索规划算法自搜索PnP传感器并接入ADAS域;采用广播报文自识别PnP传感器并进行初始化;采用车体坐标系坐标转换矩阵及补...
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| 关 键 词： | 智能网联车 多传感器 即插即用 信息融合 聚类 |
Intelligent Connected Vehicle PnP Networking Model and Decision Fusion Algorithm |
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| ZHOU Xiaochun,LIANG Jun,CHEN Long,WANG Yafei,GONG Jinfeng. Intelligent Connected Vehicle PnP Networking Model and Decision Fusion Algorithm[J]. China Mechanical Engineering, 2021, 32(16): 1983-1993. DOI: 10.3969/j.issn.1004-132X.2021.16.011 |
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| Authors: | ZHOU Xiaochun LIANG Jun CHEN Long WANG Yafei GONG Jinfeng |
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| Affiliation: | 1.School of Automotive and Traffic Engineering,Jiangsu University,Zhenjiang,Jiangsu,2120132.School of Mechanical and Power Engineering,Shanghai Jiao Tong University,Shanghai,2002403.China Automotive Technology Research Center Co.,Ltd.,Tianjin,300300 |
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| Abstract: | To simplify the networking processes of ICVs before multi-sensor fusion, a networking model of self-search—self-identification—self-calibration(S-SIC) was proposed for a PnP environmental sensing sensor. The PnP sensors were searched and connected to ADAS domain by using the depth-first search planning algorithm. The PnP sensors were identified and initialized by using the broadcast messages. The PnP sensors were calibrated by the coordinate transformation matrix of the vehicle body coordinate system and compensation algorithm. Aiming at the incompatibility of ICV multi-sensor data-level and feature-level fusion, a K-m.AW decision-level fusion algorithm was proposed. The experimental results show that the S-SIC model search success rate reaches 92%, and the average search time is as 1.79 s. In the trajectory estimation of the preceding vehicle, the multi-scene fusion estimation based on K-m.AW algorithm is increased by 7.6% and 11.8% respectively compared with contrast algorithms. |
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| Keywords: | intelligent connected vehicle(ICV) multi-sensor plug-and-play(PnP) information fusion clustering |
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