Innovative Smart Road Stud Sensor Network Development for Real-Time Traffic Monitoring

被引:4
|
作者
Tao, Zhimin [1 ]
Quan, Wei [2 ]
Wang, Hua [2 ]
机构
[1] Beihang Univ, Sch Transportat Sci & Engn, Beijing, Peoples R China
[2] Harbin Inst Technol, Sch Transportat & Sci Engn, Harbin, Peoples R China
基金
中国国家自然科学基金;
关键词
VEHICLE CLASSIFICATION; FLOW;
D O I
10.1155/2022/8830276
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Intelligent transportation infrastructure has gained significant research attention recently. In this paper, an innovative sensor network of smart road stud (SRS) is developed to enhance traffic detection infrastructure characterized by its functionality in traffic data collection, long/short range wireless data transmission, self-sustained power supply, and remote custom controlled lighting-based traffic guidance. Compared to the traditional traffic detectors and road studs, SRS nodes are installed on lane lines instead of lane center to enable the additional applications besides the detection function, such as traffic monitoring, congestion warning, routing guidance, and so on. SRS detects vehicles based on three-axis geomagnetic sensors. A vehicle detection algorithm is proposed correspondingly under different operation scenarios to count vehicles in two adjacent lanes. Its detecting accuracy can be further improved by a sensor network of multiple SRSs working cooperatively. Field test results show that the vehicle detection accuracy based on the SRS network is about 98% per lane, which is the same level as the commercial detector installed in center of lane, even under the non-standard driving behaviors such as crossing lane line. The high performance, value-added service, and low cost enable wide-range applications of SRS networks as part of intelligent traffic detection infrastructure.
引用
下载
收藏
页数:9
相关论文
共 50 条
  • [41] Supporting Random Real-Time Traffic in a Cognitive Radio Sensor Network
    Liang, Zhongliang
    Feng, Shan
    Zhao, Dongmei
    2010 IEEE 72ND VEHICULAR TECHNOLOGY CONFERENCE FALL, 2010,
  • [42] Real-Time Dense Wired Sensor Network Based on Traffic Shaping
    Loureiro, Joao
    Rangarajan, Raghuraman
    Nikolic, Borislav
    Indrusiak, Leandro
    Tovar, Eduardo
    2017 IEEE 23RD INTERNATIONAL CONFERENCE ON EMBEDDED AND REAL-TIME COMPUTING SYSTEMS AND APPLICATIONS (RTCSA), 2017,
  • [43] Real-Time Monitoring of Traffic Congestions
    Wiseman, Yair
    2017 IEEE INTERNATIONAL CONFERENCE ON ELECTRO INFORMATION TECHNOLOGY (EIT), 2017, : 501 - 505
  • [44] Real-time monitoring of traffic parameters
    Khazukov, Kirill
    Shepelev, Vladimir
    Karpeta, Tatiana
    Shabiev, Salavat
    Slobodin, Ivan
    Charbadze, Irakli
    Alferova, Irina
    JOURNAL OF BIG DATA, 2020, 7 (01)
  • [45] REAL-TIME DETECTION OF ROAD TRAFFIC INCIDENTS
    Skorput, Pero
    Mandzuka, Sadko
    Jelusic, Niko
    PROMET-TRAFFIC & TRANSPORTATION, 2010, 22 (04): : 273 - 283
  • [46] Real-time monitoring of the extended road network by utilising telematics technology
    Wessels, I.
    Steyn, W. J. vdM.
    FUNCTIONAL PAVEMENT DESIGN, 2016, : 194 - 194
  • [47] Development of a traffic measurement and analysis system for real-time network traffic engineering
    Oh, DE
    Lee, JK
    CCCT 2003 VOL, 2, PROCEEDINGS: COMMUNICATIONS SYSTEMS, TECHNOLOGIES AND APPLICATIONS, 2003, : 356 - 360
  • [48] Remote optical sensor for real-time residual salt monitoring on road surfaces
    Ruiz-Llata, Marta
    Martin-Mateos, Pedro
    Lopez, Jose R.
    Acedo, Pablo
    SENSORS AND ACTUATORS B-CHEMICAL, 2014, 191 : 371 - 376
  • [49] Development of A Real-Time On-Road Emissions Estimation and Monitoring System
    Liu, Hang
    Tok, Yeow Chern Andre
    Ritchie, Stephen G.
    2011 14TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2011, : 1821 - 1826
  • [50] Traffic volume measurement based on a single smart road stud
    Wang, Hua
    Sun, Yanli
    Quan, Wei
    Ma, Xiaolong
    Ochieng, Washington Yotto
    MEASUREMENT, 2022, 187