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An approach to urban traffic condition estimation by aggregating GPS data

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Abstract

It has been found that the traffic speed is most direct reflection of traffic state. The speed of individual vehicle, however, is inadequate to estimate accurately actual traffic status. Thereby the speeds from several vehicles should be aggregated in order to arrive at a good approximation of actually travel speed for total traffic. In this paper, with the GPS data, a series of technologies are combined with the geographic information systems for transportation map to compute the road average-speed, which is computed by aggregating all of the instantaneous speeds in interested road section. And after that, an evaluation index of traffic situations is introduced to estimate the real traffic state based on the road average-speeds and free-flow speeds. At same time, some key factors influencing traffic state are considered in order to get more accurate estimations. The illustration and experimental results indicate that the proposed method can characterize the actual traffic speeds well and provide an accurate estimation of traffic state.

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Acknowledgements

The authors would like to thank the Chongqing Municipal Transportation Information Centre and the Chongqing SUOMEI Intelligent Transportation Communications Services CO. LTD for providing real traffic data used in this paper. This research is jointly sponsored by the China Postdoctoral Science Foundation (2016M592645) and Chongqing Research Program of Application Foundation and Advanced Technology (cstc2016jcyjA0010).

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Authors and Affiliations

  1. School of Traffic and Transportation, Chongqing Jiaotong University, Chongqing, 400074, China

    Qinglu Ma & Zheng Zou

  2. Key Laboratory of Traffic System & Safety in Mountain Cities, Chongqing, 400074, China

    Qinglu Ma

  3. Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, 64200, Pakistan

    Saleem Ullah

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  1. Qinglu Ma
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  2. Zheng Zou
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  3. Saleem Ullah
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Correspondence to Qinglu Ma.

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Ma, Q., Zou, Z. & Ullah, S. An approach to urban traffic condition estimation by aggregating GPS data. Cluster Comput 22 (Suppl 3), 5421–5434 (2019). https://doi.org/10.1007/s10586-017-1262-0

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  • DOI: https://doi.org/10.1007/s10586-017-1262-0

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