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New frontiers of freeway traffic control and estimation

Delle Monache, M. L. (author)
Univ Calif Berkeley, Dept Civil & Environm Engn, Berkeley, CA 94720 USA.
Pasquale, C. (author)
Univ Genoa, Dept Informat Bioengn Robot & Syst Engn, Genoa, Italy.
Barreau, Matthieu (author)
KTH,Reglerteknik
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Stern, R. (author)
Univ Minnesota, Dept Civil Environm & Geoengn, Minneapolis, MN 55455 USA.
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Univ Calif Berkeley, Dept Civil & Environm Engn, Berkeley, CA 94720 USA Univ Genoa, Dept Informat Bioengn Robot & Syst Engn, Genoa, Italy. (creator_code:org_t)
Institute of Electrical and Electronics Engineers (IEEE), 2022
2022
English.
In: 2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 6910-6925
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • This article provides an overview of the classical and new techniques in traffic flow control and estimations. The overview begins with a description of the most used traffic flow models for estimation and control. Then, it shifts towards using those models for traffic flow estimation using physics-informed machine learning techniques. Lastly, it focuses on traffic flow control describing the most classical techniques and the new advancement in traffic control using autonomous vehicles.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Samhällsbyggnadsteknik -- Transportteknik och logistik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Civil Engineering -- Transport Systems and Logistics (hsv//eng)

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