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Travel Demand Estimation in a Multi-subnet Urban Road Network. / Krylatov, Alexander; Raevskaya, Anastasiya.

Learning and Intelligent Optimization - 15th International Conference, LION 15, 2021, Revised Selected Papers. ред. / Dimitris E. Simos; Panos M. Pardalos; Ilias S. Kotsireas. Springer Nature, 2021. стр. 183-197 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 12931 LNCS).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование

Harvard

Krylatov, A & Raevskaya, A 2021, Travel Demand Estimation in a Multi-subnet Urban Road Network. в DE Simos, PM Pardalos & IS Kotsireas (ред.), Learning and Intelligent Optimization - 15th International Conference, LION 15, 2021, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Том. 12931 LNCS, Springer Nature, стр. 183-197, 15th International Conference on Learning and Intelligent Optimization, LION 15 2021, Virtual, Online, 20/06/21. https://doi.org/10.1007/978-3-030-92121-7_16

APA

Krylatov, A., & Raevskaya, A. (2021). Travel Demand Estimation in a Multi-subnet Urban Road Network. в D. E. Simos, P. M. Pardalos, & I. S. Kotsireas (Ред.), Learning and Intelligent Optimization - 15th International Conference, LION 15, 2021, Revised Selected Papers (стр. 183-197). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 12931 LNCS). Springer Nature. https://doi.org/10.1007/978-3-030-92121-7_16

Vancouver

Krylatov A, Raevskaya A. Travel Demand Estimation in a Multi-subnet Urban Road Network. в Simos DE, Pardalos PM, Kotsireas IS, Редакторы, Learning and Intelligent Optimization - 15th International Conference, LION 15, 2021, Revised Selected Papers. Springer Nature. 2021. стр. 183-197. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-92121-7_16

Author

Krylatov, Alexander ; Raevskaya, Anastasiya. / Travel Demand Estimation in a Multi-subnet Urban Road Network. Learning and Intelligent Optimization - 15th International Conference, LION 15, 2021, Revised Selected Papers. Редактор / Dimitris E. Simos ; Panos M. Pardalos ; Ilias S. Kotsireas. Springer Nature, 2021. стр. 183-197 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{3689799442164add990788a1e4af33f2,
title = "Travel Demand Estimation in a Multi-subnet Urban Road Network",
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.",
keywords = "Bi-level optimization, Multi-subnet urban road network, Travel demand estimation",
author = "Alexander Krylatov and Anastasiya Raevskaya",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 15th International Conference on Learning and Intelligent Optimization, LION 15 2021 ; Conference date: 20-06-2021 Through 25-06-2021",
year = "2021",
doi = "10.1007/978-3-030-92121-7_16",
language = "English",
isbn = "9783030921200",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "183--197",
editor = "Simos, {Dimitris E.} and Pardalos, {Panos M.} and Kotsireas, {Ilias S.}",
booktitle = "Learning and Intelligent Optimization - 15th International Conference, LION 15, 2021, Revised Selected Papers",
address = "Germany",

}

RIS

TY - GEN

T1 - Travel Demand Estimation in a Multi-subnet Urban Road Network

AU - Krylatov, Alexander

AU - Raevskaya, Anastasiya

N1 - Publisher Copyright: © 2021, Springer Nature Switzerland AG.

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - Bi-level optimization

KW - Multi-subnet urban road network

KW - Travel demand estimation

UR - http://www.scopus.com/inward/record.url?scp=85121930125&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-92121-7_16

DO - 10.1007/978-3-030-92121-7_16

M3 - Conference contribution

AN - SCOPUS:85121930125

SN - 9783030921200

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 183

EP - 197

BT - Learning and Intelligent Optimization - 15th International Conference, LION 15, 2021, Revised Selected Papers

A2 - Simos, Dimitris E.

A2 - Pardalos, Panos M.

A2 - Kotsireas, Ilias S.

PB - Springer Nature

T2 - 15th International Conference on Learning and Intelligent Optimization, LION 15 2021

Y2 - 20 June 2021 through 25 June 2021

ER -

ID: 91114933