AI Techniques for Urban Traffic Control and Mobility

Saumya Bhatnagar

doi:10.24963/ijcai.2023/812

AI Techniques for Urban Traffic Control and Mobility

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

Abstract

The growing population has accelerated the process of urbanisation, and is putting under stress the urban transport infrastructure. This results in increased traffic congestion, with significant health, economy, and social issues. Artificial Intelligence techniques are increasingly demonstrating their capabilities in predicting and supporting urban traffic control, by extending the abilities of traffic authorities in planning and reacting to different traffic conditions. In this context, our main research topic fits in the autonomic traffic control theme, with the aim of supporting the design of autonomous traffic control systems.

Original language	English
Title of host publication	Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence
Editors	Edith Elkind
Publisher	International Joint Conferences on Artificial Intelligence
Pages	7075-7076
Number of pages	2
ISBN (Electronic)	9781956792034
DOIs	https://doi.org/10.24963/ijcai.2023/812
Publication status	Published - 19 Aug 2023
Event	32nd International Joint Conference on Artificial Intelligence - Cotai Macao, Macao Duration: 19 Aug 2023 → 25 Aug 2023 Conference number: 32 https://ijcai-23.org/

Publication series

Name	IJCAI International Joint Conference on Artificial Intelligence
Volume	2023-August
ISSN (Print)	1045-0823

Conference

Conference	32nd International Joint Conference on Artificial Intelligence
Abbreviated title	IJCAI 2023
Country/Territory	Macao
City	Cotai Macao
Period	19/08/23 → 25/08/23
Internet address	https://ijcai-23.org/

UN SDGs

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

SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities

Access to Document

10.24963/ijcai.2023/812Licence: Unspecified

Cite this

Bhatnagar, S. (2023). AI Techniques for Urban Traffic Control and Mobility. In E. Elkind (Ed.), Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (pp. 7075-7076). (IJCAI International Joint Conference on Artificial Intelligence; Vol. 2023-August). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2023/812

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title = "AI Techniques for Urban Traffic Control and Mobility",

abstract = "The growing population has accelerated the process of urbanisation, and is putting under stress the urban transport infrastructure. This results in increased traffic congestion, with significant health, economy, and social issues. Artificial Intelligence techniques are increasingly demonstrating their capabilities in predicting and supporting urban traffic control, by extending the abilities of traffic authorities in planning and reacting to different traffic conditions. In this context, our main research topic fits in the autonomic traffic control theme, with the aim of supporting the design of autonomous traffic control systems.",

keywords = "MDA, Transportation Machine Learning, ML, Applications, Multidisciplinary Topics and Applications",

author = "Saumya Bhatnagar",

note = "Publisher Copyright: {\textcopyright} 2023 International Joint Conferences on Artificial Intelligence. All rights reserved.; 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023 ; Conference date: 19-08-2023 Through 25-08-2023",

year = "2023",

month = aug,

day = "19",

doi = "10.24963/ijcai.2023/812",

language = "English",

series = "IJCAI International Joint Conference on Artificial Intelligence",

publisher = "International Joint Conferences on Artificial Intelligence",

pages = "7075--7076",

editor = "Edith Elkind",

booktitle = "Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence",

address = "United States",

url = "https://ijcai-23.org/",

}

Bhatnagar, S 2023, AI Techniques for Urban Traffic Control and Mobility. in E Elkind (ed.), Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence. IJCAI International Joint Conference on Artificial Intelligence, vol. 2023-August, International Joint Conferences on Artificial Intelligence, pp. 7075-7076, 32nd International Joint Conference on Artificial Intelligence, Cotai Macao, Macao, 19/08/23. https://doi.org/10.24963/ijcai.2023/812

AI Techniques for Urban Traffic Control and Mobility. / Bhatnagar, Saumya.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence. ed. / Edith Elkind. International Joint Conferences on Artificial Intelligence, 2023. p. 7075-7076 (IJCAI International Joint Conference on Artificial Intelligence; Vol. 2023-August).

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

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AB - The growing population has accelerated the process of urbanisation, and is putting under stress the urban transport infrastructure. This results in increased traffic congestion, with significant health, economy, and social issues. Artificial Intelligence techniques are increasingly demonstrating their capabilities in predicting and supporting urban traffic control, by extending the abilities of traffic authorities in planning and reacting to different traffic conditions. In this context, our main research topic fits in the autonomic traffic control theme, with the aim of supporting the design of autonomous traffic control systems.

KW - MDA

KW - Transportation Machine Learning

KW - ML

KW - Applications

KW - Multidisciplinary Topics and Applications

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DO - 10.24963/ijcai.2023/812

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BT - Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence

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ER -

AI Techniques for Urban Traffic Control and Mobility

Abstract

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Conference

UN SDGs

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