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Early Detection of a Traffic Flow Breakdown in the Freeway Based on Dynamical Network Markers

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Abstract

This paper presents a novel model-free method based on the dynamical network markers (DNM) to detect the traffic flow breakdown at an early transition stage in the context of the freeway connected with an on-ramp under a connected vehicle environment. In this method, the vehicle states are frequently observed at several cells or segments on each lane. By processing the observed data, the standard deviations and the correlation coefficients among the cells are analyzed to determine the dominant cells, the ones that are mostly influenced during the transition. Finally, the standard deviations and absolute values of the correlation coefficients of the dominant cells are combined to form a scalar warning signal, which provides a very strong indication when the traffic is at the critical state. The proposed method is evaluated through simulation on freeway traffic, whose flows are disturbed by the on-ramp merging vehicles.

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Acknowledgments

This research is supported in part by JSPS Grant-in-Aids for Scientific Research JP15H05707, and JP18H03774 and CREST, JMPJCR14D2, JST. The authors would like to thank Prof. Martin Treiber, Technical University of Dresden, for his advice on selecting parameters of the traffic flow model.

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Authors and Affiliations

  1. Division of Mechanical Science and Technology, Graduate School of Science and Technology, Gunma University, Kiryu, 376-8515, Japan

    Md Abdus Samad Kamal

  2. Institute of Natural Medicine, University of Toyama, Toyama, 930–0194, Japan

    Makito Oku

  3. Department of Systems and Control, Tokyo Institute of Technology, Tokyo, 152-8552, Japan

    Tomohisa Hayakawa & Jun-ichi Imura

  4. Institute of Industrial Science, and Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, 113-8656, Japan

    Kazuyuki Aihara

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  1. Md Abdus Samad Kamal
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  5. Kazuyuki Aihara
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Correspondence to Md Abdus Samad Kamal.

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Kamal, M., Oku, M., Hayakawa, T. et al. Early Detection of a Traffic Flow Breakdown in the Freeway Based on Dynamical Network Markers. Int. J. ITS Res. 18, 422–435 (2020). https://doi.org/10.1007/s13177-019-00210-4

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  • DOI: https://doi.org/10.1007/s13177-019-00210-4

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