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科技导报 |专题:交通强国建设 2020 , 38 (9) : 82 -88
车路协同+自动驾驶助力郑州智慧岛交通强国示范
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任永利, 董航瑞
作者信息
    郑州宇通客车股份有限公司, 郑州 450000
作者简介:
任永利,高级工程师,研究方向为智能网联公共交通,电子信箱:renyl@yutong.com
To build a powerful transportation demonstration of China: Zhengzhou Smart Island with the help of vehicle-road coordination and self-driving
  • REN Yongli, DONG Hangrui
  • Affiliations
      Zhengzhou Yutong Bus Co., Ltd., Zhengzhou 450000, China
    出版时间: 2020-05-13 doi: 10.3981/j.issn.1000-7857.2020.09.011
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    从传统智能交通发展现状及瓶颈着手,结合车路协同技术的发展现状,提出了车-路-云-法一体化智慧交通解决方案,并在郑州智慧岛开放道路条件下实现了L4级自动驾驶公交示范运营,面向乘客实现常态化运营。项目成功落地验证了车路协同核心应用(盲区预警和信号协同)方案的可行性,为车路协同技术创新发展奠定了实践基础。结合国家最新5G及交通强国政策要求,对车路协同发展进行了展望。
    车路协同  /  自动驾驶  /  盲区监测  /  信号协同
    This paper discusses the development status and bottleneck of traditional intelligent transportation at first, then combined with the development of motor road coordination technology it puts forward an integrated intelligent transportation solution of car, road and cloud. Next, it presents the L4 self-driving bus demonstration operation under open road condition of Zhengzhou Smart Island, which has been put into normal operations for passengers. The successful landing of the project has verified the feasibility of the road coordination core application scheme(blind zone early warning and signal coordination), and laid a practical foundation for the development of road cooperative technology innovation. Finally the paper visions the future of the coordinated development of the road in terms of the country's latest 5G and transportation power policy.
    vehicle-road coordination  /  autonomous vehicles  /  blind spot monitoring  /  traffic signal collaboration
    任永利, 董航瑞. 车路协同+自动驾驶助力郑州智慧岛交通强国示范. 科技导报, 2020 , 38 (9) : 82 -88 . DOI: 10.3981/j.issn.1000-7857.2020.09.011
    REN Yongli, DONG Hangrui. To build a powerful transportation demonstration of China: Zhengzhou Smart Island with the help of vehicle-road coordination and self-driving[J]. Science & Technology Review, 2020 , 38 (9) : 82 -88 . DOI: 10.3981/j.issn.1000-7857.2020.09.011

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    doi: 10.3981/j.issn.1000-7857.2020.09.011
    • 接收时间:2020-03-29
    • 首发时间:2020-06-05
    • 出版时间:2020-05-13
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    • 修回日期:2020-04-27
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    species
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    Percentage of
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    Percentage of total
    species (%)
    鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
    小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
    多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
    红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
    小菇属 Mycena 11 5.26
    光柄菇属 Pluteus 5 2.39
    红菇属 Russula 17 8.13
    栓菌属 Trametes 5 2.39
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