摘要
在经济全球化以及工业4.0背景下,物流企业面临需求复杂化、产品多样化以及运输全球化难题,但随着政策环境的持续引导,物联网、云计算等新一代ICT技术的成功应用,以及B2B,C2B商业模式的冲击,传统物流行业正逐步由集中控制向分散控制转变,由反应性物流向智慧化物流转变。中国是制造业大国,在人口红利消失、资源短缺的现状下,制造业自动化智能化升级势在必行,同样也必将带动物流运输进行资源整合,向自动化、智慧化发展。德国作为工业4.0的提出者,在工业4.0与智慧物流的融合发展方面具有一定的先进性和前瞻性,通过对德国人工智能、自动驾驶、智慧物流等先进技术的研究分析,对比中国智慧物流发展现状,分析了当前存在的问题,并提出了中国智慧物流发展建议。
In the context of economic globalization and industry 4.0,logistics enterprises are facing the problems of complex demand,product diversification and transport globalization.However,with the continuous guidance of the policy environment and the successful application of new-generation ICT technologies such as Internet of Things and cloud computing as well as the impact of B2 B and C2 B business models,the traditional logistics industry is gradually changing from centralized control to decentralized control,from reactive logistics to smart logistics.China is a big manufacturing country.Under the current situation of the disappearance of demographic dividend and resource shortage,it is imperative to upgrade the automation and intelligence of the manufacturing industry.It will also promote the integration of logistics and transport resources,and develop towards automation and intelligence.As the proponent of Industry 4.0,Germany has certain advanced and forward-looking in the integration and development of Industry 4.0 and smart logistics.Through the research and analysis of advanced technologies of Germany such as artificial intelligence,autonomous driving and smart logistics,the development status and the current problems of China’s smart logistics are compared and analyzed,and suggestions for the development of China’s smart logistics are put forward.
作者
赵佳海
杨凤满
刘楠
衣倩
ZHAO Jia-hai;YANG Feng-man;LIU Nan;YI Qian(Research Institute of Highway,Ministry of Transport,Beijing 100088,China)
出处
《公路交通科技》
CAS
CSCD
北大核心
2020年第S01期35-39,45,共6页
Journal of Highway and Transportation Research and Development
基金
中央级公益性科研院所基本科研业务费项目(2020-9018)
“科技助力经济2020”重点专项项目(SQ2020YFF0426379)
关键词
物流工程
智慧物流
人工智能
自动驾驶
多式联运
Logistics engineering
smart logistics
artificial intelligence
autonomous driving
multimodal transport
