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A Review of Max-Pressure Traffic Signal Control Algorithms: State of the Art and Research Opportunities — arXiv:2611.04029

Source: arXiv (en)
Original: https://arxiv.org/abs/2611.04029
License (as archived): CC0-1.0
Archived: 2026-11-04T18:59:43.732Z
SHA-256 of the archived text: 2360bb9af349386a800e6dbf85a1a11f24e683badf62f5b24c9e4faffd783247
Stable URL of this page: https://metraipolis.com/documento/dc_48855fcdd640

How to cite

A Review of Max-Pressure Traffic Signal Control Algorithms: State of the Art and Research Opportunities — arXiv:2611.04029 — arXiv (en), https://arxiv.org/abs/2611.04029 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_48855fcdd640 (Metraipolis archive dc_48855fcdd640, sha256 2360bb9af349386a800e6dbf85a1a11f24e683badf62f5b24c9e4faffd783247)

BibTeX

@misc{dc48855fcdd640,
  title = {A Review of Max-Pressure Traffic Signal Control Algorithms: State of the Art and Research Opportunities — arXiv:2611.04029},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2611.04029},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_48855fcdd640; sha256 2360bb9af349386a800e6dbf85a1a11f24e683badf62f5b24c9e4faffd783247},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2611.04029. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Max-Pressure (MP) has emerged as a widely studied decentralized traffic signal control framework, thanks to its desirable theoretical properties and strong control performance. Early research on MP focused on improving control performance by exploring different variables of the traffic state for the definition of pressure. Subsequent studies expanded MP to incorporate the complexity of real-world transportation systems and emerging technologies. This paper provides a comprehensive review of these developments. The review first introduces the theoretical foundations of MP and examines early developments in movement weight definition. It then synthesizes major extensions for multimodal and multiscale network control, followed by recent developments in connected and automated vehicle (CAV) environments and the integration of MP with artificial intelligence (AI) and data-driven methods. Beyond summarizing existing approaches, this review examines their underlying assumptions, data requirements, implementation considerations, and practical limitations. Based on this comprehensive review, key research gaps and future directions are identified, including remaining limitations in the theoretical foundations of MP and the underexplored integration of autonomous vehicle control with the MP framework. Overall, this review provides a structured perspective on the evolution and current state of MP control and highlights opportunities for developing more proactive, robust, and practically deployable MP-based traffic control methods.

Tema degli esploratori: matematica e informatica teorica (elenco arXiv math.OC, nuovi lavori del giorno).
Categorie arXiv: Systems and Control (eess.SY) ; Optimization and Control (math.OC).
Pagina del lavoro: https://arxiv.org/abs/2611.04029 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-11-04T18:37:22.171Z dalla pagina https://arxiv.org/list/math.OC/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).