Abstract
Optimising traffic signals is crucial for mitigating urban congestion, and automated planning, particularly with PDDL+, has shown promise for real-world deployment due to its flexibility and centralised perspective. While existing PDDL+ models guarantee deployability on current infrastructure, they face significant limitations: reliance on domain-independent heuristics restricts their applicability and scalability, leading to slow solution generation and unclear plan quality. To overcome these challenges and unlock the widespread adoption of planning-based traffic control, we introduce hCAFE, a domain-specific heuristic for PDDL+-based traffic signal optimisation. Unlike prior approaches, hCAFE is designed to work effectively across multiple problem encodings, addressing a key limitation of traditional domain-specific heuristics. We demonstrate its capabilities on real-world data from a region of the UK, showing significant improvements in solution generation time and search space exploration. Our evaluation also compares the strategies generated by hCAFE against historical data from existing traffic control systems and a non-deployable benchmark, confirming the high quality of the resulting plans.
| 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 | 36207-36216 |
| Number of pages | 10 |
| Volume | 40 |
| ISBN (Print) | 1577359062, 9781577359067 |
| DOIs | |
| 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 the AAAI Conference on Artificial Intelligence |
|---|---|
| Publisher | AAAI |
| Number | 43 |
| 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 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
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