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

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

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Room: 23.HG 4.02.2

Profile

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

Publications

Courses 2024

Courses 2023

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Prizes

  • 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

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  • 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

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  • 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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Ancillary activities

Contact

Room: 23.HG 4.02.2