Traffic Signal Plans Explorer: A General Framework for Visualising Traffic Evolution

Francesco Doria; Francesco Percassi; Marco Maratea; Mauro Vallati

doi:10.1609/aaai.v40i48.42343

Traffic Signal Plans Explorer: A General Framework for Visualising Traffic Evolution

Francesco Doria, Francesco Percassi, Marco Maratea, Mauro Vallati

University of Calabria

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We present the Traffic Signal Plans Explorer, a framework for visualising and exploring traffic signal plans generated via PDDL+ planning. Designed to support both traffic experts and non-specialists, the tool offers a web-based interface for high-level network analysis and a SUMO-based adapter for detailed simulation. Users can inspect junction settings and link dynamics, and simulate plan execution step by step. The system bridges planning technology with practical traffic control, enhancing the transparency and usability of automatically generated solutions.

Original language	English
Title of host publication	The Fortieth AAAI Conference on Artificial Intelligence
Subtitle of host publication	Thirty-Eighth Conference on Innovative Applications of Artificial Intelligence, Sixteenth Symposium on Educational Advances in Artificial Intelligence
Editors	Sven Koenig, Chad Jenkins, Matthew E. Taylor
Publisher	AAAI press
Pages	41571-41573
Number of pages	3
Volume	40
Edition	48
ISBN (Electronic)	9781577359067
ISBN (Print)	1577359062
DOIs	https://doi.org/10.1609/aaai.v40i48.42343
Publication status	Published - 14 Mar 2026
Event	The 40th Annual AAAI Conference on Artificial Intelligence - Singapore EXPO, Singapore Duration: 20 Jan 2026 → 27 Jan 2026 https://aaai.org/conference/aaai/aaai-26/

Publication series

Name	Proceedings of AAAI Conference on Artificial Intelligence
Publisher	AAAI
Number	48
Volume	40
ISSN (Print)	2159-5399
ISSN (Electronic)	2374-3468

Conference

Conference	The 40th Annual AAAI Conference on Artificial Intelligence
Abbreviated title	AAAI-26
Country/Territory	Singapore
Period	20/01/26 → 27/01/26
Internet address	https://aaai.org/conference/aaai/aaai-26/

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10.1609/aaai.v40i48.42343Licence: Unspecified

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Doria, F., Percassi, F., Maratea, M., & Vallati, M. (2026). Traffic Signal Plans Explorer: A General Framework for Visualising Traffic Evolution. In S. Koenig, C. Jenkins, & M. E. Taylor (Eds.), The Fortieth AAAI Conference on Artificial Intelligence: Thirty-Eighth Conference on Innovative Applications of Artificial Intelligence, Sixteenth Symposium on Educational Advances in Artificial Intelligence (48 ed., Vol. 40, pp. 41571-41573). (Proceedings of AAAI Conference on Artificial Intelligence; Vol. 40, No. 48). AAAI press. https://doi.org/10.1609/aaai.v40i48.42343

Doria, Francesco ; Percassi, Francesco ; Maratea, Marco et al. / Traffic Signal Plans Explorer : A General Framework for Visualising Traffic Evolution. The Fortieth AAAI Conference on Artificial Intelligence: Thirty-Eighth Conference on Innovative Applications of Artificial Intelligence, Sixteenth Symposium on Educational Advances in Artificial Intelligence. editor / Sven Koenig ; Chad Jenkins ; Matthew E. Taylor. Vol. 40 48. ed. AAAI press, 2026. pp. 41571-41573 (Proceedings of AAAI Conference on Artificial Intelligence; 48).

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title = "Traffic Signal Plans Explorer: A General Framework for Visualising Traffic Evolution",

abstract = "We present the Traffic Signal Plans Explorer, a framework for visualising and exploring traffic signal plans generated via PDDL+ planning. Designed to support both traffic experts and non-specialists, the tool offers a web-based interface for high-level network analysis and a SUMO-based adapter for detailed simulation. Users can inspect junction settings and link dynamics, and simulate plan execution step by step. The system bridges planning technology with practical traffic control, enhancing the transparency and usability of automatically generated solutions.",

keywords = "Traffic Signals, Traffic Evolution",

author = "Francesco Doria and Francesco Percassi and Marco Maratea and Mauro Vallati",

note = "Publisher Copyright: {\textcopyright} 2026, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; The 40th Annual AAAI Conference on Artificial Intelligence, AAAI-26 ; Conference date: 20-01-2026 Through 27-01-2026",

year = "2026",

month = mar,

day = "14",

doi = "10.1609/aaai.v40i48.42343",

language = "English",

isbn = "1577359062",

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publisher = "AAAI press",

number = "48",

pages = "41571--41573",

editor = "Sven Koenig and Chad Jenkins and Taylor, \{Matthew E.\}",

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Doria, F, Percassi, F, Maratea, M & Vallati, M 2026, Traffic Signal Plans Explorer: A General Framework for Visualising Traffic Evolution. in S Koenig, C Jenkins & ME Taylor (eds), The Fortieth AAAI Conference on Artificial Intelligence: Thirty-Eighth Conference on Innovative Applications of Artificial Intelligence, Sixteenth Symposium on Educational Advances in Artificial Intelligence. 48 edn, vol. 40, Proceedings of AAAI Conference on Artificial Intelligence, no. 48, vol. 40, AAAI press, pp. 41571-41573, The 40th Annual AAAI Conference on Artificial Intelligence, Singapore, 20/01/26. https://doi.org/10.1609/aaai.v40i48.42343

Traffic Signal Plans Explorer: A General Framework for Visualising Traffic Evolution. / Doria, Francesco; Percassi, Francesco; Maratea, Marco et al.
The Fortieth AAAI Conference on Artificial Intelligence: Thirty-Eighth Conference on Innovative Applications of Artificial Intelligence, Sixteenth Symposium on Educational Advances in Artificial Intelligence. ed. / Sven Koenig; Chad Jenkins; Matthew E. Taylor. Vol. 40 48. ed. AAAI press, 2026. p. 41571-41573 (Proceedings of AAAI Conference on Artificial Intelligence; Vol. 40, No. 48).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Doria, Francesco

AU - Percassi, Francesco

AU - Maratea, Marco

AU - Vallati, Mauro

PY - 2026/3/14

Y1 - 2026/3/14

N2 - We present the Traffic Signal Plans Explorer, a framework for visualising and exploring traffic signal plans generated via PDDL+ planning. Designed to support both traffic experts and non-specialists, the tool offers a web-based interface for high-level network analysis and a SUMO-based adapter for detailed simulation. Users can inspect junction settings and link dynamics, and simulate plan execution step by step. The system bridges planning technology with practical traffic control, enhancing the transparency and usability of automatically generated solutions.

AB - We present the Traffic Signal Plans Explorer, a framework for visualising and exploring traffic signal plans generated via PDDL+ planning. Designed to support both traffic experts and non-specialists, the tool offers a web-based interface for high-level network analysis and a SUMO-based adapter for detailed simulation. Users can inspect junction settings and link dynamics, and simulate plan execution step by step. The system bridges planning technology with practical traffic control, enhancing the transparency and usability of automatically generated solutions.

KW - Traffic Signals

KW - Traffic Evolution

UR - https://www.scopus.com/pages/publications/105034251740

UR - https://ojs.aaai.org/index.php/AAAI/issue/view/732

U2 - 10.1609/aaai.v40i48.42343

DO - 10.1609/aaai.v40i48.42343

M3 - Conference contribution

SN - 1577359062

VL - 40

T3 - Proceedings of AAAI Conference on Artificial Intelligence

SP - 41571

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BT - The Fortieth AAAI Conference on Artificial Intelligence

A2 - Koenig, Sven

A2 - Jenkins, Chad

A2 - Taylor, Matthew E.

PB - AAAI press

Y2 - 20 January 2026 through 27 January 2026

ER -

Doria F, Percassi F, Maratea M, Vallati M. Traffic Signal Plans Explorer: A General Framework for Visualising Traffic Evolution. In Koenig S, Jenkins C, Taylor ME, editors, The Fortieth AAAI Conference on Artificial Intelligence: Thirty-Eighth Conference on Innovative Applications of Artificial Intelligence, Sixteenth Symposium on Educational Advances in Artificial Intelligence. 48 ed. Vol. 40. AAAI press. 2026. p. 41571-41573. (Proceedings of AAAI Conference on Artificial Intelligence; 48). doi: 10.1609/aaai.v40i48.42343

Traffic Signal Plans Explorer: A General Framework for Visualising Traffic Evolution

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