McCluskey, T.L., Vallati, Mauro and Franco, Santiago (2017) Automated planning for urban traffic management. In: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence. IJCAI, pp. 5238-5240. ISBN 978-0-9992411-0-3
![]() |
PDF
- Published Version
Restricted to Repository staff only Download (240kB) |
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
Item Type: | Book Chapter |
---|---|
Subjects: | Q Science > QA Mathematics > QA76 Computer software |
Schools: | School of Computing and Engineering School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge |
Related URLs: | |
Depositing User: | Mauro Vallati |
Date Deposited: | 08 Jun 2017 08:30 |
Last Modified: | 28 Aug 2021 15:56 |
URI: | http://eprints.hud.ac.uk/id/eprint/32112 |
Downloads
Downloads per month over past year
Repository Staff Only: item control page
![]() |
View Item |