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Virtual speed sensors based algorithm for expressway traffic state estimation

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Abstract

The accurate estimation of expressway traffic state can provide decision-making for both travelers and traffic managers. The speed is one of the most representative parameter of the traffic state. So the expressway speed spatial distribution can be taken as the expressway traffic state equivalent. In this paper, an algorithm based on virtual speed sensors (VSS) is presented to estimate the expressway traffic state (the speed spatial distribution). To gain the spatial distribution of expressway traffic state, virtual speed sensors are defined between adjacent traffic flow sensors. Then, the speed data extracted from traffic flow sensors in time series are mapped to space series to design virtual speed sensors. Then the speed of virtual speed sensors can be calculated with the weight matrix which is related with the speed of virtual speed sensors and the speed data extracted from traffic flow sensors and the speed data extracted from traffic flow sensors in time series. Finally, the expressway traffic state (the speed spatial distribution) can be gained. The acquisition of average travel speed of the expressway is taken for application of this traffic state estimation algorithm. One typical expressway in Beijing is adopted for the experiment analysis. The results prove that this traffic state estimation approach based on VSS is feasible and can achieve a high accuracy.

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Authors and Affiliations

  1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, 100044, China

    DongWei Xu, HongHui Dong, LiMin Jia & Yong Qin

  2. School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China

    DongWei Xu, HongHui Dong, LiMin Jia & Yong Qin

Authors
  1. DongWei Xu
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  2. HongHui Dong
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  3. LiMin Jia
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  4. Yong Qin
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Correspondence to LiMin Jia.

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Xu, D., Dong, H., Jia, L. et al. Virtual speed sensors based algorithm for expressway traffic state estimation. Sci. China Technol. Sci. 55, 1381–1390 (2012). https://doi.org/10.1007/s11431-012-4814-9

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  • DOI: https://doi.org/10.1007/s11431-012-4814-9

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