01697348

Component

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.

This paper was sponsored by TRB committee ABJ60 Standing Committee on Geographic Information Science and Applications.

19-04478

English

19p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

Figures; Maps; References

Computer online services; Data fusion; Digital mapping; Smartphones; Traffic surveillance

Map matching

Data and Information Technology; Highways; Operations and Traffic Management

Transportation Research Board Annual Meeting 2019 Paper #19-04478

TRIS, TRB, ATRI

Dec 7 2018 9:24AM