Automated planning for urban traffic management

Thomas McCluskey, Mauro Vallati, Santiago Franco Aixela

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The global growth in urbanisation increases the demand for services including road transport infrastructure, presenting challenges in terms of mobility. Optimising the exploitation of urban road network, while attempting to minimise the effects of traffic emissions, is a great challenge. SimplyfAI was a UK research council grant funded project which was aimed towards solving air quality problems caused by road traffic emissions. Large cities such as Manchester struggle to meet air quality limits as the range of available traffic management devices is limited. In the study, we investigated the application of linked data to enrich environmental and traffic data feeds, and we used this with automated planning tools to enable traffic to be managed at a region level. The management will have the aim of avoiding air pollution problems before they occur. This demo focuses on the planning component, and in particular the engineering and validation aspects, that were pivotal for the success of the project.
Original languageEnglish
Title of host publicationProceedings of the 2017 International Joint Conference on Artificial Intelligence
EditorsCarles Sierra
PublisherInternational Joint Conferences on Artificial Intelligence
Pages5238-5240
Number of pages3
ISBN (Electronic)9780999241103
Publication statusPublished - Aug 2017
Event26th International Joint Conference on Artificial Intelligence - Melbourne Convention Centre, Melbourne, Australia
Duration: 19 Aug 201725 Aug 2017
Conference number: 26
https://ijcai-17.org/ (Link to Conference Website )

Conference

Conference26th International Joint Conference on Artificial Intelligence
Abbreviated titleIJCAI 2017
CountryAustralia
CityMelbourne
Period19/08/1725/08/17
Internet address

Fingerprint

Air quality
Planning
Air pollution

Cite this

McCluskey, T., Vallati, M., & Franco Aixela, S. (2017). Automated planning for urban traffic management. In C. Sierra (Ed.), Proceedings of the 2017 International Joint Conference on Artificial Intelligence (pp. 5238-5240). International Joint Conferences on Artificial Intelligence.
McCluskey, Thomas ; Vallati, Mauro ; Franco Aixela, Santiago. / Automated planning for urban traffic management. Proceedings of the 2017 International Joint Conference on Artificial Intelligence. editor / Carles Sierra. International Joint Conferences on Artificial Intelligence, 2017. pp. 5238-5240
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McCluskey, T, Vallati, M & Franco Aixela, S 2017, Automated planning for urban traffic management. in C Sierra (ed.), Proceedings of the 2017 International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence, pp. 5238-5240, 26th International Joint Conference on Artificial Intelligence, Melbourne, Australia, 19/08/17.

Automated planning for urban traffic management. / McCluskey, Thomas; Vallati, Mauro; Franco Aixela, Santiago.

Proceedings of the 2017 International Joint Conference on Artificial Intelligence. ed. / Carles Sierra. International Joint Conferences on Artificial Intelligence, 2017. p. 5238-5240.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - The global growth in urbanisation increases the demand for services including road transport infrastructure, presenting challenges in terms of mobility. Optimising the exploitation of urban road network, while attempting to minimise the effects of traffic emissions, is a great challenge. SimplyfAI was a UK research council grant funded project which was aimed towards solving air quality problems caused by road traffic emissions. Large cities such as Manchester struggle to meet air quality limits as the range of available traffic management devices is limited. In the study, we investigated the application of linked data to enrich environmental and traffic data feeds, and we used this with automated planning tools to enable traffic to be managed at a region level. The management will have the aim of avoiding air pollution problems before they occur. This demo focuses on the planning component, and in particular the engineering and validation aspects, that were pivotal for the success of the project.

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McCluskey T, Vallati M, Franco Aixela S. Automated planning for urban traffic management. In Sierra C, editor, Proceedings of the 2017 International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence. 2017. p. 5238-5240