A Domain-specific Heuristic for PDDL+-based Traffic Signal Optimisation
Francesco Doria, Francesco Percassi, Marco Maratea, Mauro Vallati
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.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Builds on1
Related papers
- Temporal Planning with Intermediate Conditions and EffectsAlessandro Valentini, Andrea Micheli, Alessandro CimattiAAAI 2020 · 27 citations
- HDDL: An Extension to PDDL for Expressing Hierarchical Planning ProblemsDaniel Höller, Gregor Behnke, Pascal Bercher, Susanne Biundo et al.AAAI 2020 · 111 citations
- Two Constraint Compilation Methods for Lifted PlanningPeriklis Mantenoglou, Luigi Bonassi, Enrico Scala, Pedro Zuidberg Dos MartiresAAAI 2026
- Homomorphisms of Lifted Planning Tasks: The Case for Delete-Free Relaxation HeuristicsRostislav Horcík, Daniel Fiser, Álvaro TorralbaAAAI 2022 · 6 citations
- SayCanPay: Heuristic Planning with Large Language Models Using Learnable Domain KnowledgeRishi Hazra, Pedro Zuidberg Dos Martires, Luc De RaedtAAAI 2024 · 74 citations
