Dr.ir. S.C. (Simeon) Calvert

Dr.ir. S.C. (Simeon) Calvert

Contact

Ruimte: 23.HG 4.02.2

Profiel

Simeon maintains a broad interest in a vast number of traffic flow related topics and has a particular interest in traffic management and the analysis of traffic flow, as well as the impact of automated and cooperative driving towards the future.

Expertise

Publicaties

Onderwijs 2024

Onderwijs 2023

Media

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Prijzen

  • 2023-9-28

    Best Student Paper Runner-up Award (IEEE ITSC 2023)

    Won the Best Student Runner-up Award at 26th IEEE International Conference on Intelligent Transportation Systems ITSC 2023
    26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023

    Lees meer Best Student Paper Runner-up Award (IEEE ITSC 2023)
  • 2016-12-16

    Best paper award ACSEE 2016

    Best paper award at International Conference on Advances in Civil, Structural and Environmental Engineering - ACSEE 2016, for paper 'Considering knowledge gaps for automated driving in conventional traffic'
    http://www.traffic-quest.nl/images/stories/Plaatjes/Fotos/ascee_2.jpg
    4th International Conference on Advances in Civil, Structural and Environmental Engineering

    Lees meer Best paper award ACSEE 2016
  • 2015

    Greenshields Prize 2015

    This paper proposes a real time travel time prediction framework designed for large urban area including both arterial and urban roads. This framework makes it possible to test a wide variety of prediction models based either on theoretical or data-driven approaches. The results are demonstrated in a large test case corresponding to the Amsterdam Practical Trial. Data-driven approaches were then favor because their are easier to calibrate and require less computations. For short-term prediction, it appears that the simplest data driven approach (naive approach) performs the best. For larger-time window, a refined method (historic median prediction) provides the more accurate results. In most cases, the average absolute relative error is below 20%. The main contributions of this paper are (i) the formulation of the global framework and (ii) the extensive test of different methods on a large and heterogeneous operational test cases. The operational feedbacks from this study provide a good state of the art of the performance of data-driven methods in a mixed context and pave the way of further methodological developments

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  • 4-2-29

    Certificate of appreciation

    Awarded by the Vehicle-Highway Automation Committee at the 2021 TRB Annual Meeting with appreciation and respect for great work as an organizer of the Automated Vehicles Symposium 2020 ~ July 27–30, 2020

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Meer prijzen

Nevenwerkzaamheden

Contact

Ruimte: 23.HG 4.02.2