PDDL+ Models for Deployable yet Effective Traffic Signal Optimisation

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

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

2 Citations (Scopus)


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 Thirty-Forth International Conference on Automated Planning and Scheduling
EditorsSara Bernardini, Christian Muise
PublisherAAAI press
Number of pages10
ISBN (Electronic)9781577358893
Publication statusPublished - 30 May 2024
Event34th International Conference on Automated Planning and Scheduling - Banff, Canada
Duration: 1 Jun 20246 Jun 2024
Conference number: 34

Publication series

NameProceedings International Conference on Automated Planning and Scheduling, ICAPS
PublisherAAAI Press
ISSN (Print)2334-0835
ISSN (Electronic)2334-0843


Conference34th International Conference on Automated Planning and Scheduling
Abbreviated titleICAPS 2024
Internet address

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