车辆荷载信息识别技术发展现状及趋势研究  

Development and Trends of Vehicle Load Information Identification Technologies

作　　者：赵千 胡明伟[1,2,3] 陈湘生 杨海露[4,5] 汪林兵 宋尚霖 Zhao Qian;Hu Mingwei;Chen Xiangsheng;Yang Hailu;Wang Linbing;Song Shanglin(College of Civil and Transportation Engineering,Shenzhen University,Shenzhen 518060,China;Underground Polis Academy,Shenzhen University,Shenzhen 518060,China;State Key Laboratory of Intelligent Geotechnics and Tunnelling,Shenzhen 518060,China;National Center for Materials Service Safety,University of Science and Technology Beijing,Beijing 100083,China;Scientific Observation and Research Base of Transport Industry of Long Term Performance of Highway Infrastructure in Northwest Cold and Arid Regions(Gansu Provincial Highway Development Group Co.,Ltd.,),Lanzhou 730070,China;The Sensing and Perception Lab,University of Georgia,Athens 30602,USA)

机构地区：[1]深圳大学土木与交通工程学院,广东深圳518060 [2]深圳大学未来地下城市研究院,广东深圳518060 [3]极端环境岩土和隧道工程智能建养全国重点实验室,广东深圳518060 [4]北京科技大学国家材料服役安全科学中心,北京100083 [5]西北寒旱区公路基础设施长期性能交通运输行业野外科学观测研究基地(甘肃省公路发展集团有限公司),甘肃兰州730070 [6]佐治亚大学传感与感知实验室,佐治亚州雅典30602

出　　处：《市政技术》2025年第1期1-10,共10页Journal of Municipal Technology

基　　金：广东省重点领域研发计划项目(2022B0101070001);西北寒旱区公路基础设施长期性能交通运输行业野外科学观测研究基地(甘肃省公路发展集团有限公司)开放基金资助(No.JDKF202302)。

摘　　要：随着我国公路运输需求的增长和极端天气的频发,道路基础设施的维护与管理面临严峻挑战。笔者探讨了在政策背景、气候变化和技术进步的推动下车辆荷载识别技术的需求;分析了车辆荷载识别技术的理论研究进展、传感感知手段及误差影响;最终提出了车辆荷载识别技术未来可能的发展方向,包括精细化的理论模型、多传感器融合、非接触式感知、人工智能算法优化和数据资源整合。这些技术进步将为道路与桥梁提供更精准的运维策略和可靠的安全保障措施,提升交通基础设施的功能性、耐久性和经济性。With the increasing demand for road transportation and the growing frequency of extreme weather events in China,it has become increasingly challenging to maintain and manage road infrastructure.Under the influence of policies,climate change,and technological advancements,the demands for vehicle load-identification technology was discussed in this paper;The progress in vehicle load-identification theory,sensing technologies and error analysis were analyzed;Finally,the potential directions about the vehicle load identification in future have been put forward,including refined theoretical models,multi-sensor integration,non-contact sensing,AI intelligent algorithms optimization and data integration,which are expected to improve the precision of maintenance strategies and enhance the safety and efficiency of road and bridge infrastructure.

关 键 词：车辆荷载识别 称重传感器 车-路(桥)耦合 多传感器融合 计算机视觉 

分 类 号：U492.3[交通运输工程—交通运输规划与管理] TP212.9[交通运输工程—道路与铁道工程]