A stochastic process model for daily travel patterns and traffic information

Yongtaek Lim; Seung Jae Lee; Joohwan Kim

doi:10.1007/978-3-540-72830-6_11

A stochastic process model for daily travel patterns and traffic information

Yongtaek Lim
, Seung Jae Lee
, Joohwan Kim

Department of Transportation Engineering

Chonnam National University
K-Center

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Sudden changes on road networks, including new roads, bridge construction, road blockage or traffic accidents cause travelers to switch their routes to less costly ones as compared to alternative routes. Travelers, however, tend to take higher cost routes due to insufficient information and errors in perceived travel time. This may cause severe congestion on a certain route. Conventional models, however, are unable to adequately simulate travelers' behavior under such suddenly changing network conditions. The objective of this paper is to analyze travelers' daily travel behavior in such cases via a stochastic process, the Markov-chain approach, which is considered to be a suitable method for representing sudden changes in states. This model is based on agent and we assumes that travelers select their route via learning process of travel time that they had previously experienced.

Original language	English
Title of host publication	Agent and Multi-Agent Systems
Subtitle of host publication	Technologies and Applications - First KES International Symposium, KES-AMSTA 2007, Proceedings
Publisher	Springer Verlag
Pages	102-110
Number of pages	9
ISBN (Print)	9783540728290
DOIs	https://doi.org/10.1007/978-3-540-72830-6_11
State	Published - 2007
Event	1st KES International Symposium on Agent and Multi-Agent Systems - Technologies and Applications, KES-AMSTA 2007 - Wroclaw, Poland Duration: 31 May 2007 → 1 Jun 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4496 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	1st KES International Symposium on Agent and Multi-Agent Systems - Technologies and Applications, KES-AMSTA 2007
Country/Territory	Poland
City	Wroclaw
Period	31/05/07 → 1/06/07

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Access to Document

10.1007/978-3-540-72830-6_11

Cite this

Lim, Y., Lee, S. J., & Kim, J. (2007). A stochastic process model for daily travel patterns and traffic information. In Agent and Multi-Agent Systems: Technologies and Applications - First KES International Symposium, KES-AMSTA 2007, Proceedings (pp. 102-110). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4496 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-540-72830-6_11

Lim, Yongtaek ; Lee, Seung Jae ; Kim, Joohwan. / A stochastic process model for daily travel patterns and traffic information. Agent and Multi-Agent Systems: Technologies and Applications - First KES International Symposium, KES-AMSTA 2007, Proceedings. Springer Verlag, 2007. pp. 102-110 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A stochastic process model for daily travel patterns and traffic information",

abstract = "Sudden changes on road networks, including new roads, bridge construction, road blockage or traffic accidents cause travelers to switch their routes to less costly ones as compared to alternative routes. Travelers, however, tend to take higher cost routes due to insufficient information and errors in perceived travel time. This may cause severe congestion on a certain route. Conventional models, however, are unable to adequately simulate travelers' behavior under such suddenly changing network conditions. The objective of this paper is to analyze travelers' daily travel behavior in such cases via a stochastic process, the Markov-chain approach, which is considered to be a suitable method for representing sudden changes in states. This model is based on agent and we assumes that travelers select their route via learning process of travel time that they had previously experienced.",

author = "Yongtaek Lim and Lee, \{Seung Jae\} and Joohwan Kim",

year = "2007",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "102--110",

booktitle = "Agent and Multi-Agent Systems",

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note = "1st KES International Symposium on Agent and Multi-Agent Systems - Technologies and Applications, KES-AMSTA 2007 ; Conference date: 31-05-2007 Through 01-06-2007",

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Lim, Y, Lee, SJ & Kim, J 2007, A stochastic process model for daily travel patterns and traffic information. in Agent and Multi-Agent Systems: Technologies and Applications - First KES International Symposium, KES-AMSTA 2007, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4496 LNAI, Springer Verlag, pp. 102-110, 1st KES International Symposium on Agent and Multi-Agent Systems - Technologies and Applications, KES-AMSTA 2007, Wroclaw, Poland, 31/05/07. https://doi.org/10.1007/978-3-540-72830-6_11

A stochastic process model for daily travel patterns and traffic information. / Lim, Yongtaek; Lee, Seung Jae; Kim, Joohwan.
Agent and Multi-Agent Systems: Technologies and Applications - First KES International Symposium, KES-AMSTA 2007, Proceedings. Springer Verlag, 2007. p. 102-110 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4496 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A stochastic process model for daily travel patterns and traffic information

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AU - Lee, Seung Jae

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N2 - Sudden changes on road networks, including new roads, bridge construction, road blockage or traffic accidents cause travelers to switch their routes to less costly ones as compared to alternative routes. Travelers, however, tend to take higher cost routes due to insufficient information and errors in perceived travel time. This may cause severe congestion on a certain route. Conventional models, however, are unable to adequately simulate travelers' behavior under such suddenly changing network conditions. The objective of this paper is to analyze travelers' daily travel behavior in such cases via a stochastic process, the Markov-chain approach, which is considered to be a suitable method for representing sudden changes in states. This model is based on agent and we assumes that travelers select their route via learning process of travel time that they had previously experienced.

AB - Sudden changes on road networks, including new roads, bridge construction, road blockage or traffic accidents cause travelers to switch their routes to less costly ones as compared to alternative routes. Travelers, however, tend to take higher cost routes due to insufficient information and errors in perceived travel time. This may cause severe congestion on a certain route. Conventional models, however, are unable to adequately simulate travelers' behavior under such suddenly changing network conditions. The objective of this paper is to analyze travelers' daily travel behavior in such cases via a stochastic process, the Markov-chain approach, which is considered to be a suitable method for representing sudden changes in states. This model is based on agent and we assumes that travelers select their route via learning process of travel time that they had previously experienced.

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

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BT - Agent and Multi-Agent Systems

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Lim Y, Lee SJ, Kim J. A stochastic process model for daily travel patterns and traffic information. In Agent and Multi-Agent Systems: Technologies and Applications - First KES International Symposium, KES-AMSTA 2007, Proceedings. Springer Verlag. 2007. p. 102-110. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-72830-6_11

A stochastic process model for daily travel patterns and traffic information

Abstract

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UN SDGs

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