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Travel Demand Estimation in a Multi-subnet Urban Road Network

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Learning and Intelligent Optimization (LION 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12931))

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Abstract

Today urban road network of a modern city can include several subnets. Indeed, bus lanes form a transit subnet available only for public vehicles. Toll roads form a subnet, available only for drivers who ready to pay fees for passage. The common aim of developing such subnets is to provide better urban travel conditions for public vehicles and toll-paying drivers. The present paper is devoted to the travel demand estimation problem in a multi-subnet urban road network. We formulate this problem as a bi-level optimization program and prove that it has a unique solution under quite a natural assumption. Moreover, for the simple case of a road network topology with disjoint routes, we obtain important analytical results that allow us to analyze different scenarios appearing within the travel demand estimation process in a multi-subnet urban road network. The findings of the paper contribute to the traffic theory and give fresh managerial insights for traffic engineers.

The work was jointly supported by a grant from the Russian Science Foundation (No. 20-71-00062 Development of artificial intelligence tools for estimation travel demand values between intersections in urban road networks in order to support operation of intelligent transportation systems).

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Author information

Authors and Affiliations

  1. Saint Petersburg State University, Saint Petersburg, Russia

    Alexander Krylatov & Anastasiya Raevskaya

  2. Institute of Transport Problems RAS, Saint Petersburg, Russia

    Alexander Krylatov

Authors
  1. Alexander Krylatov
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  2. Anastasiya Raevskaya
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Corresponding author

Correspondence to Alexander Krylatov .

Editor information

Editors and Affiliations

  1. SBA Research, Vienna, Austria

    Dimitris E. Simos

  2. University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

  3. Wilfrid Laurier University, Waterloo, ON, Canada

    Ilias S. Kotsireas

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Krylatov, A., Raevskaya, A. (2021). Travel Demand Estimation in a Multi-subnet Urban Road Network. In: Simos, D.E., Pardalos, P.M., Kotsireas, I.S. (eds) Learning and Intelligent Optimization. LION 2021. Lecture Notes in Computer Science(), vol 12931. Springer, Cham. https://doi.org/10.1007/978-3-030-92121-7_16

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  • DOI: https://doi.org/10.1007/978-3-030-92121-7_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-92120-0

  • Online ISBN: 978-3-030-92121-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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