Deployable Yet Effective Traffic Signal Optimisation via Automated Planning

Anas El Kouaiti, Francesco Percassi, Alessandro Saetti, Lee McCluskey, Mauro Vallati

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The use of planning techniques in traffic signal optimisation has proven effective in managing unexpected traffic conditions as well as typical traffic patterns. However, significant challenges concerning the deployability of generated signal plans remain, as planning systems need to consider constraints and features of the actual real-world infrastructure on which they will be implemented. To address this challenge, we introduce a range of PDDL+ models embodying technological requirements as well as insights from domain experts. The proposed models have been extensively tested on historical data using a range of well-known search strategies and heuristics, as well as alternative encodings. Results demonstrate their competitiveness with the state of the art.

Original languageEnglish
Title of host publicationProceedings of the 17th International Symposium on Combinatorial Search (SoCS 2024)
EditorsAriel Felner, Jiaoyang Li
PublisherAAAI press
Pages269-270
Number of pages2
Volume17
Edition1
ISBN (Print)9781577358916
DOIs
Publication statusPublished - 1 Jun 2024
Event17th International Symposium on Combinatorial Search - Pomeroy Kananaskis Mountain Lodge , Kananaskis, Canada
Duration: 6 Jun 20248 Jun 2024
Conference number: 17
https://socs24.search-conference.org/

Publication series

NameInternational Symposium on Combinatorial Search
PublisherAAAI
Volume2024
ISSN (Print)2832-9171
ISSN (Electronic)2832-9163

Conference

Conference17th International Symposium on Combinatorial Search
Abbreviated titleSoCS 2024
Country/TerritoryCanada
CityKananaskis
Period6/06/248/06/24
Internet address

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