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Towards real-time density estimation using vehicle-to-vehicle communications

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  • Florin, Ryan
  • Olariu, Stephan

Abstract

Traffic state estimation is a fundamental task of Intelligent Transportation Systems (ITS). Recent advances in sensor technology and emerging computer and vehicular communications paradigms have brought the task of estimating traffic state parameters in real time within reach. Recognizing this, the US-DOT started promoting the Connected Vehicles (CV) initiative. By using wireless connectivity between the vehicles participating in the traffic, the CV initiative aims to promote an increased awareness of real-time traffic conditions and, as a result, to reduce the number and severity of crashes.

Suggested Citation

  • Florin, Ryan & Olariu, Stephan, 2020. "Towards real-time density estimation using vehicle-to-vehicle communications," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 435-456.
    • Handle: RePEc:eee:transb:v:138:y:2020:i:c:p:435-456
    DOI: 10.1016/j.trb.2020.06.001
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    References listed on IDEAS

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    1. Zheng, Fangfang & Jabari, Saif Eddin & Liu, Henry X. & Lin, DianChao, 2018. "Traffic state estimation using stochastic Lagrangian dynamics," Transportation Research Part B: Methodological, Elsevier, vol. 115(C), pages 143-165.
    2. Seo, Toru & Kawasaki, Yutaka & Kusakabe, Takahiko & Asakura, Yasuo, 2019. "Fundamental diagram estimation by using trajectories of probe vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 40-56.
    3. Yu, Chunhui & Sun, Weili & Liu, Henry X. & Yang, Xiaoguang, 2019. "Managing connected and automated vehicles at isolated intersections: From reservation- to optimization-based methods," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 416-435.
    4. Yasuji Makigami & G. F. Newell & Richard Rothery, 1971. "Three-Dimensional Representation of Traffic Flow," Transportation Science, INFORMS, vol. 5(3), pages 302-313, August.
    5. van Erp, Paul B.C. & Knoop, Victor L. & Hoogendoorn, Serge P., 2018. "Macroscopic traffic state estimation using relative flows from stationary and moving observers," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 281-299.
    6. Wang, Yibing & Papageorgiou, Markos, 2005. "Real-time freeway traffic state estimation based on extended Kalman filter: a general approach," Transportation Research Part B: Methodological, Elsevier, vol. 39(2), pages 141-167, February.
    7. Wang, Yibing & Papageorgiou, Markos & Messmer, Albert, 2008. "Real-time freeway traffic state estimation based on extended Kalman filter: Adaptive capabilities and real data testing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(10), pages 1340-1358, December.
    8. Comert, Gurcan & Cetin, Mecit, 2009. "Queue length estimation from probe vehicle location and the impacts of sample size," European Journal of Operational Research, Elsevier, vol. 197(1), pages 196-202, August.
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    Cited by:

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