山东大学学报 (工学版) ›› 2023, Vol. 53 ›› Issue (4): 37-47.doi: 10.6040/j.issn.1672-3961.0.2022.273
• 交通工程——智慧交通专题 • 上一篇
庄绪彩1,孙希滕2,张宁3,田源1*,殷敬敬4,宋修广1
ZHUANG Xucai1, SUN Xiteng2, ZHANG Ning3, TIAN Yuan1*, YIN Jingjing4, SONG Xiuguang1
摘要: 对雷视一体机安装位置、旋转角度等进行试验分析,基于主客观组合赋权评价方法提出一种较优的解决方案。在设计安装方案之前,分析影响安装方案的主要因素并作为单一变量设计5组工况;根据搭建的雷视一体机平台进行数据采集分析,选取9个指标构建评价体系;提出基于方差最大化主客观组合赋权法和基于熵权逼近理想解排序法对各安装方案进行综合评分和优选。选取2个实地场景进行试验验证,结果表明,提出的评价技术可成功地优选安装方案,但根据不同的安装场景,如车道宽度、安装高度等,安装优选方案会有所调整。本研究能够实现雷视一体机在道路上的布设优化,具有一定推广应用价值。
中图分类号:
[1] WANG Lefei, ZHANG Zhaoyu, DI Xin, et al. A roadside camera-radar sensing fusion system for intelligent transportation[C] //2020 17th European Radar Conference(EuRAD). Utrecht, Netherlands: IEEE, 2021: 282-285. [2] CHEN Zhiqiang, LIU Zhen, HUI Yilong, et al. Roadside sensorbased vehicle counting incomplex traffic environment[C] //2019 IEEE Globecom Workshops(GC Wkshps). Waikoloa, USA: IEEE, 2019: 1-5. [3] VU V Q, NGO V L, VU T T, et al. Vehicle speed estimation using two roadside passive infrared sensors[J]. International Journal of Modern Physics B, 2020, 34: 2040151. [4] YUE Rui, XU Hao, WU Jianqing, et al. Data registration with ground points for roadside LiDAR sensors[J]. Remote Sensing, 2019, 11(11): 1354. [5] ZHOU Yan, WEN Sijie, WANG Dongli, et al. Mobile YOLO: real-time object detection algorithm in autonomous driving scenarios[J]. Sensors, 2022, 22(9): 3349. [6] BUCHMAN D, DROZDV M. Pedestrian and animal recognition using doppler radar signature and deep learning[J]. Sensors, 2022, 22(9): 3456. [7] 李秀生. 基于毫米波雷达和摄像头融合的前行车辆信息识别[D]. 西安:长安大学, 2020. LI Xiusheng. Recognition of forward vehicle information based on fusion of millimeter-wave radar and camera[D]. Xi'an:Chang'an University, 2020. [8] WANG Zhangjing, MIAO Xianhan, HUANG Zhen, et al. Research of target detection and classification techniques using millimeter-wave radar and vision sensors[J]. Remote Sensing, 2021, 13(6): 1064. [9] LIU Tianbi, DU Shanshan, LIANG Chenchen, et al. A novel multi-sensor fusion based object detection and recognition algorithm for intelligent assisted driving[J]. IEEE Access, 2021, 9: 81564-81574. [10] WEI Zhiqing, ZHANG Fengkai, CHANG Shuo, et al. Mm wave radar and vision fusion for object detection in autonomous driving: a review[J]. Sensors, 2022, 22(7): 2542. [11] 吴方义, 刘卫东, 王爱春, 等. 基于ViCANdo的ADAS摄像头安装高度研究[J]. 汽车电器, 2021(10):25-27. WU Fangyi, LIU Weidong, WANG Aichun, et al. Research on the installation height of ADAS camera based on ViCANdo[J]. Automotive Electrical Appliances, 2021(10): 25-27. [12] 檀雷. 毫米波FMCW路面目标探测雷达关键技术与系统研究[D]. 南京:东南大学,2018. TAN Lei. Research on key technology and system of millimeter-wave FMCW road target detection radar[D]. Nanjing: Southeast University, 2018. [13] 汤从衡. 基于路侧摄像头的车辆跟踪技术研究[D]. 武汉:武汉理工大学, 2019. TANG Congheng. Research on vehicle tracking technology based on roadside camera[D]. Wuhan:Wuhan University of Technology, 2019. [14] 肖波, 胡启新, 边振华. 基于3DCS的ACC雷达安装角度建模分析研究[C] //2021中国汽车工程学会年会论文集(4). 上海, 中国:中国汽车工程学会, 2021:595-597. XIAO Bo, HU Qixin, BIAN Zhenhua. Modeling and analysis of ACC radar installation angle based on 3DCS[C] //Proceedings of the 2021 Annual Meeting of the Society of Automotive Engineers of China(4). Shanghai, China: China Society of Automotive, Engineers, 2021: 595-597. [15] ZHAO Junxuan, XU Hao, TIAN Yuan, et al. Towards application of light detection and ranging sensor to traffic detection: an investigation of its built-in features and installation techniques[J]. Journal of Intelligent Transportation Systems, 2022, 26(2): 213-234. [16] 刁望成, 宋宇博. 传感器布置优化方法研究[J]. 兰州交通大学学报, 2020, 39(5):55-63. DIAO Wangcheng, SONG Yubo. Research on optimization method of sensor layout[J]. Journal of Lanzhou Jiaotong University, 2020, 39(5):55-63. [17] ROSHAN V, JIM C, RACHID R, et al. Optimal placement of roadside infrastructure sensors towards safer autonomous vehicle deployments[C] //2021 IEEE International Intelligent Transportation Systems Conference(ITSC). Indianapolis, USA: IEEE, 2021: 2589-2595. [18] WANG Xiaobin, LAN Zhu, LI Zhengjie, et al. A practical application of runway foreign object debris detection system at the airport[C] //2018 International Conference on Microwave and Millimeter Wave Technology(ICMMT). Chengdu, China: IEEE, 2018: 1-3. [19] KIM J C, JEONG H G, LEE S. Simultaneous target classification and moving direction estimation in millimeter-wave radar system[J]. Sensors, 2021, 21(15): 5228. [20] 田文豪. TOD模式下轨道交通站点地区土地利用评价研究[D]. 广州:华南理工大学, 2019. TIAN Wenhao. Study on land use evaluation of rail transit station area under TOD mode[D]. Guangzhou: South China University of Technology, 2019. [21] LYU H M, ZHOU W H, SHEN S L, et al. Inundation risk assessment of metro system using AHP and TFN-AHP in Shenzhen[J]. Sustainable Cities and Society, 2020, 56: 102103. [22] ABDEL-BASSET M, MOHAMED R.A novel plithogenic TOPSIS-CRITIC model for sustainable supply chain risk management[J]. Journal of Cleaner Production, 2020, 247: 119586. [23] XU H, MA C, LIAN J, et al. Urban flooding risk assessment based on an integrated k-means cluster algorithm and improved entropy weight method in the region of Haikou, China[J]. Journal of Hydrology, 2018, 563: 975-986. [24] ASLAM B, MAQSOOM A, KHALIL U, et al. Evaluation of different landslide susceptibility models for a local scale in the Chitral District, Northern Pakistan[J]. Sensors, 2022, 22(9): 3107. [25] 程璇. 城市轨道交通效率评价方法研究[D]. 北京:北京交通大学, 2021. CHENG Xuan.Research on evaluation method of urban rail transit efficiency[D]. Beijing: Beijing Jiaotong University, 2021. [26] 金骆松, 沈广, 王伟, 等. 基于极差最大化AHP-CRITIC的现货市场监测评估研究[J]. 华北电力大学学报(自然科学版), 2022:1-8. JIN Luosong, SHEN Guang, WANG Wei, et al. Research on spot market monitoring and evaluation based on range maximization AHP-CRITIC[J]. Journal of North China Electric Power University(Natural Science Edition), 2022: 1-8. [27] 许传西. 基于熵权TOPSIS法对家电企业业绩评价的研究[D]. 武汉:华中科技大学, 2015. XU Chuanxi. Research on performance evaluation of household appliance enterprises based on entropy weight TOPSIS method[D]. Wuhan: Huazhong University of Science and Technology, 2015. |
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