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Equilibration Operators for Accurate Traffic Flow Assignment in Urban Road Networks. / Krylatov, A.; Korol, M.; Raevskaya, A.

13th Computer Science Online Conference, CSOC 2024. Springer Nature, 2024. p. 526-535 (Lecture Notes in Networks and Systems; Vol. 1119).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Harvard

Krylatov, A, Korol, M & Raevskaya, A 2024, Equilibration Operators for Accurate Traffic Flow Assignment in Urban Road Networks. in 13th Computer Science Online Conference, CSOC 2024. Lecture Notes in Networks and Systems, vol. 1119, Springer Nature, pp. 526-535, 13th Computer Science On-line Conference 2024, 1/04/24. https://doi.org/10.1007/978-3-031-70300-3_39

APA

Krylatov, A., Korol, M., & Raevskaya, A. (2024). Equilibration Operators for Accurate Traffic Flow Assignment in Urban Road Networks. In 13th Computer Science Online Conference, CSOC 2024 (pp. 526-535). (Lecture Notes in Networks and Systems; Vol. 1119). Springer Nature. https://doi.org/10.1007/978-3-031-70300-3_39

Vancouver

Krylatov A, Korol M, Raevskaya A. Equilibration Operators for Accurate Traffic Flow Assignment in Urban Road Networks. In 13th Computer Science Online Conference, CSOC 2024. Springer Nature. 2024. p. 526-535. (Lecture Notes in Networks and Systems). https://doi.org/10.1007/978-3-031-70300-3_39

Author

Krylatov, A. ; Korol, M. ; Raevskaya, A. / Equilibration Operators for Accurate Traffic Flow Assignment in Urban Road Networks. 13th Computer Science Online Conference, CSOC 2024. Springer Nature, 2024. pp. 526-535 (Lecture Notes in Networks and Systems).

BibTeX

@inproceedings{18fc782b5ce5486eb7be7302964c3ed7,
title = "Equilibration Operators for Accurate Traffic Flow Assignment in Urban Road Networks",
abstract = "The traffic assignment problem is known as an optimization problem with a non-linear objective function and linear constraints, which allows one to estimate traffic congestion in an urban road network. Very early ideas on solving the traffic assignment problem concerned the concept of the existence of an equilibration operator. Such an operator was assumed to return assignment patterns that provide equal travel times on used routes between an origin-destination pair. Despite attempts to express this operator mathematically the first successful implementation of the idea came from computational techniques. The concept appeared to be fruitful and easy to apply from a computational perspective. Recently, a mathematical expression of the equilibration operator was found that generalized some of the previously obtained results. In the present paper, we discuss this operator and itemize key points to be paid attention to in the context of the equilibration operator application. Moreover, we demonstrate that the found operator, when applied to the problem, behaves very typically for path-equilibration techniques. The main advantage of the explicit form of the operator is the high accuracy of the solution. We believe this paper can clarify the matter and give fresh insights to traffic engineers. {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.",
keywords = "equilibration operator, traffic flow assignment, user-equilibrium, Air traffic control, Highway traffic control, Mathematical operators, Motor transportation, Optimization, Street traffic control, Traffic congestion, Transportation routes, Urban transportation, Equilibration operator, Linear constraints, Nonlinear objective functions, Objective function constraints, Optimization problems, Traffic assignment problem, Traffic flow assignment, Travel-time, Urban road networks, User equilibrium, Travel time",
author = "A. Krylatov and M. Korol and A. Raevskaya",
note = "Код конференции: 321789 Export Date: 10 November 2024; null ; Conference date: 01-04-2024",
year = "2024",
doi = "10.1007/978-3-031-70300-3_39",
language = "Английский",
isbn = "9783031702990",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Nature",
pages = "526--535",
booktitle = "13th Computer Science Online Conference, CSOC 2024",
address = "Германия",

}

RIS

TY - GEN

T1 - Equilibration Operators for Accurate Traffic Flow Assignment in Urban Road Networks

AU - Krylatov, A.

AU - Korol, M.

AU - Raevskaya, A.

N1 - Код конференции: 321789 Export Date: 10 November 2024

PY - 2024

Y1 - 2024

N2 - The traffic assignment problem is known as an optimization problem with a non-linear objective function and linear constraints, which allows one to estimate traffic congestion in an urban road network. Very early ideas on solving the traffic assignment problem concerned the concept of the existence of an equilibration operator. Such an operator was assumed to return assignment patterns that provide equal travel times on used routes between an origin-destination pair. Despite attempts to express this operator mathematically the first successful implementation of the idea came from computational techniques. The concept appeared to be fruitful and easy to apply from a computational perspective. Recently, a mathematical expression of the equilibration operator was found that generalized some of the previously obtained results. In the present paper, we discuss this operator and itemize key points to be paid attention to in the context of the equilibration operator application. Moreover, we demonstrate that the found operator, when applied to the problem, behaves very typically for path-equilibration techniques. The main advantage of the explicit form of the operator is the high accuracy of the solution. We believe this paper can clarify the matter and give fresh insights to traffic engineers. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

AB - The traffic assignment problem is known as an optimization problem with a non-linear objective function and linear constraints, which allows one to estimate traffic congestion in an urban road network. Very early ideas on solving the traffic assignment problem concerned the concept of the existence of an equilibration operator. Such an operator was assumed to return assignment patterns that provide equal travel times on used routes between an origin-destination pair. Despite attempts to express this operator mathematically the first successful implementation of the idea came from computational techniques. The concept appeared to be fruitful and easy to apply from a computational perspective. Recently, a mathematical expression of the equilibration operator was found that generalized some of the previously obtained results. In the present paper, we discuss this operator and itemize key points to be paid attention to in the context of the equilibration operator application. Moreover, we demonstrate that the found operator, when applied to the problem, behaves very typically for path-equilibration techniques. The main advantage of the explicit form of the operator is the high accuracy of the solution. We believe this paper can clarify the matter and give fresh insights to traffic engineers. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

KW - equilibration operator

KW - traffic flow assignment

KW - user-equilibrium

KW - Air traffic control

KW - Highway traffic control

KW - Mathematical operators

KW - Motor transportation

KW - Optimization

KW - Street traffic control

KW - Traffic congestion

KW - Transportation routes

KW - Urban transportation

KW - Equilibration operator

KW - Linear constraints

KW - Nonlinear objective functions

KW - Objective function constraints

KW - Optimization problems

KW - Traffic assignment problem

KW - Traffic flow assignment

KW - Travel-time

KW - Urban road networks

KW - User equilibrium

KW - Travel time

UR - https://www.mendeley.com/catalogue/6e98155e-a18d-3178-b53a-e7507f90a3d2/

U2 - 10.1007/978-3-031-70300-3_39

DO - 10.1007/978-3-031-70300-3_39

M3 - статья в сборнике материалов конференции

SN - 9783031702990

T3 - Lecture Notes in Networks and Systems

SP - 526

EP - 535

BT - 13th Computer Science Online Conference, CSOC 2024

PB - Springer Nature

Y2 - 1 April 2024

ER -

ID: 127213777