Online Map-Matching for Traffic Sensing on Highway Network with Call Detail Record

Mobile phone detection technology is considered to be promising for traffic data acquisition with the advantages of Call Detail Record (CDR) data: all-weather collection, wide coverage and low cost, which is a good supplement to the existing traffic sensing methods on highway network. Online map-matching with CDR data is a crucial step and a big challenge for the application of mobile phone in traffic sensing. In this paper, the authors propose an online map-matching algorithm framework for traffic sensing on highway network with CDR data. This algorithm can solve two problem which cause traditional GPS online map-matching algorithm failure: (1) the oscillation and drifting of CDR data, and (2) CDR trajectories near highway will be mismatched onto highway. Based on Hidden Markov Model (HMM), this algorithm can output the maximum likelihood path over the Markov chain for highway trajectories while no output for non-highway trajectories. The authors utilize 100 CDR trajectories on highway and 100 trajectories near highway to evaluate this algorithm.The experiment result shows that the accuracy of our algorithm can reach 90.5% with 259.2s output delay, which is viable for traffic sensing.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ABJ60 Standing Committee on Geographic Information Science and Applications.
• Corporate Authors:

  Transportation Research Board

  ,    
• Authors:
  • Wang, Yiming
  • Dong, Honghui
  • Jia, Limin
  • Pan, Hanzhong
  • Qiu, Hongtong
  • Qin, Yong
• Conference:
  • Transportation Research Board 98th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2019-1-13 to 2019-1-17
• Date: 2019

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Maps; References;
• Pagination: 19p

Subject/Index Terms

• TRT Terms: Computer online services; Data fusion; Digital mapping; Smartphones; Traffic surveillance
• Uncontrolled Terms: Map matching
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01697348
• Record Type: Publication
• Report/Paper Numbers: 19-04478
• Files: TRIS, TRB, ATRI
• Created Date: Mar 1 2019 3:50PM