PDDL+ Models for Deployable yet Effective Traffic Signal Optimisation


  • Anas El Kouaiti University of Brescia, Italy
  • Francesco Percassi University of Huddersfield, UK
  • Alessandro Saetti University of Brescia, Italy
  • Thomas Leo McCluskey University of Huddersfield, UK
  • Mauro Vallati University of Huddersfield, UK




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 strategies remain, as existing approaches tend not 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.




How to Cite

El Kouaiti, A., Percassi, F., Saetti, A., McCluskey, T. L., & Vallati, M. (2024). PDDL+ Models for Deployable yet Effective Traffic Signal Optimisation. Proceedings of the International Conference on Automated Planning and Scheduling, 34(1), 168-177. https://doi.org/10.1609/icaps.v34i1.31473