Embedding Automated Planning within Urban Traffic Management Operations

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

11 Citations (Scopus)

Abstract

This paper is an experience report on the results of an industry-led collaborative project aimed at automating the control of traffic flow within a large city centre. A major focus of the automation was to deal with abnormal or unexpected events such as roadworks, road closures or excessive demand, resulting in periods of saturation of the network within some region of the city. We describe the resulting system which works by sourcing and semantically enriching urban traffic data, and uses the derived knowledge as input to an automated planning component to generate light signal control strategies in real time. This paper reports on the development surrounding the planning component, and in particular the engineering, configuration and validation issues that arose in the application. It discusses a range of lessons learned from the experience of deploying automated planning in the road transport area, under the direction of transport operators and technology developers.
Original languageEnglish
Title of host publicationProceedings of the 27th International Conference on Automated Planning and Scheduling
Subtitle of host publication (ICAPS 2017)
EditorsLaura Barbulescu, Jeremy Frank, Mausam , Stephen F. Smith
PublisherAssociation for the Advancement of Artificial Intelligence
Number of pages9
Publication statusPublished - 2017
Event27th International Conference on Automated Planning and Scheduling - Pittsburgh, United States
Duration: 18 Jun 201723 Jun 2017
Conference number: 27
http://icaps17.icaps-conference.org/ (Link to Conference Website)

Conference

Conference27th International Conference on Automated Planning and Scheduling
Abbreviated titleICAPS 2017
CountryUnited States
CityPittsburgh
Period18/06/1723/06/17
Internet address

    Fingerprint

Cite this

McCluskey, T., & Vallati, M. (2017). Embedding Automated Planning within Urban Traffic Management Operations. In L. Barbulescu, J. Frank, M., & S. F. Smith (Eds.), Proceedings of the 27th International Conference on Automated Planning and Scheduling: (ICAPS 2017) Association for the Advancement of Artificial Intelligence.