2 Citations (Scopus)

Abstract

There is a growing interest in the use of AI techniques for urban traffic control, with a particular focus on traffic signal optimisation. Model-based approaches such as planning demonstrated to be capable of dealing in real-time with unexpected or unusual traffic conditions, as well as with the usual traffic patterns. Further, the knowledge models on which such techniques rely to generate traffic signal strategies are in fact simulation models of traffic, hence can be used by traffic authorities to test and compare different approaches. In this work, we present a framework that relies on automated planning to generate and simulate traffic signal strategies in a urban region. To demonstrate the capabilities of the framework, we consider real-world data collected from sensors deployed in a major corridor of the Kirklees region of the United Kingdom.
Original languageEnglish
Title of host publicationProceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
EditorsEdith Elkind
PublisherInternational Joint Conferences on Artificial Intelligence
Pages7119-7122
Number of pages4
ISBN (Electronic)9781956792034
DOIs
Publication statusPublished - 19 Aug 2023
Event32nd International Joint Conference on Artificial Intelligence - Cotai Macao, Macao
Duration: 19 Aug 202325 Aug 2023
Conference number: 32
https://ijcai-23.org/

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
PublisherInternational Joint Conferences on Artificial Intelligence
Volume2023-August
ISSN (Print)1045-0823

Conference

Conference32nd International Joint Conference on Artificial Intelligence
Abbreviated titleIJCAI 2023
Country/TerritoryMacao
CityCotai Macao
Period19/08/2325/08/23
Internet address

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