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To build China's strength in transportation it is importank to make better use of big data technology to promote intelligent transportation. Aiming at the shortcomings of the traditional signal control system such as low optimization frequency and poor integrity of data acquisition equipment this paper develops an intelligent signal control system using ride hailing vehicle trajectory data. The architecture and characteristics of the control system, as well as optimization techniques, are introduced. Field experiments in Jinan, Wuhan and Liuzhou, respectively, have demonstrated that without relying on channelization and intersection reconstruction, only through signal control optimization and software upgrades, the average delay times of morning and evening peak hours and vehicle stop times are decreased by 10%-20%, thus effectively alleviating traffic congestion across the whole city level., authors=ZHANG Bo, PANG Jimin, ZHANG Wensong, QIE Xiaohu, LIU Xianghong, authorsList=ZHANG Bo, PANG Jimin, ZHANG Wensong, QIE Xiaohu, LIU Xianghong, authorCompany=Beijing DiDi Infinity Technology and Development Co., Ltd., Beijing 100193, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=hXHYEkSMdm9STH/o+oel/Q==, pdfFileSize=5492054, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, 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互联网大数据技术在智慧交通发展中的应用
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张博, 庞基敏, 章文嵩, 郄小虎, 刘向宏
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    北京嘀嘀无限科技发展有限公司, 北京 100193
Application of big data technology in the development of intelligent transportation
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出版时间: 2020-05-13 doi: 10.3981/j.issn.1000-7857.2020.09.007
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随着互联网大数据技术的发展,各种互联网+交通的新业态不断涌现,行业内出现了大量丰富的数据资源。在交通强国建设背景下,更好地利用互联网大数据技术为智慧交通发展赋能成为重要任务。针对传统信号控制系统优化频率低,数据采集设备完备度差等缺陷,采用网约车轨迹大数据技术研究智慧信号控制优化系统,介绍了系统架构、特征和信号控制优化技术。该系统在济南、武汉和柳州等城市的实践结果表明,在不依赖渠化及路口改造的前提下,仅通过信号控制优化及软件升级的方式,能有效地降低重点路段和路口的工作日早晚高峰平均延误时间和停车次数等关键指标,其降幅可达10%~20%,能够有效缓解交通拥堵现状。
交通强国  /  轨迹大数据  /  智慧信号控制  /  网约车
Various new types of Internet plus transportation are emerging and a large number of data resources have appeared. To build China's strength in transportation it is importank to make better use of big data technology to promote intelligent transportation. Aiming at the shortcomings of the traditional signal control system such as low optimization frequency and poor integrity of data acquisition equipment this paper develops an intelligent signal control system using ride hailing vehicle trajectory data. The architecture and characteristics of the control system, as well as optimization techniques, are introduced. Field experiments in Jinan, Wuhan and Liuzhou, respectively, have demonstrated that without relying on channelization and intersection reconstruction, only through signal control optimization and software upgrades, the average delay times of morning and evening peak hours and vehicle stop times are decreased by 10%-20%, thus effectively alleviating traffic congestion across the whole city level.
country with strong transportation  /  trajectory data  /  intelligent signal control  /  ride hailing
张博, 庞基敏, 章文嵩, 郄小虎, 刘向宏. 互联网大数据技术在智慧交通发展中的应用. 科技导报, 2020 , 38 (9) : 47 -54 . DOI: 10.3981/j.issn.1000-7857.2020.09.007
ZHANG Bo, PANG Jimin, ZHANG Wensong, QIE Xiaohu, LIU Xianghong. Application of big data technology in the development of intelligent transportation[J]. Science & Technology Review, 2020 , 38 (9) : 47 -54 . DOI: 10.3981/j.issn.1000-7857.2020.09.007
2020年第38卷第9期
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doi: 10.3981/j.issn.1000-7857.2020.09.007
  • 接收时间:2020-03-11
  • 首发时间:2020-06-05
  • 出版时间:2020-05-13
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  • 收稿日期:2020-03-11
  • 修回日期:2020-04-20
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2种不同金属材料的力学参数

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Number of
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Percentage of total
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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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