{
  "abstract": "Fine-grained adaptive signal control requires a performance evaluator that is causally faithful and fast enough for phase-level rolling decisions. Simulation-in-the-loop optimization pays for fidelity with replication cost, while fast analytical evaluators based on store-and-forward or exponential queueing assumptions discard the stochastic structure of inter-arrival and service times or the coupling between intersections. We develop a finite-capacity queueing network evaluator in which each signalized link is a PH/PH/1/K queue with a state-dependent service rate, arrival and service-time variability is inherited from rolling-window moment fitting, and link interactions are resolved by a fixed-point decomposition in which finite-capacity blocking caps delivered throughput; the node solve is proved exact, with complete proofs of convergence, sensitivity, and cost bounds. Discrete-event checks confirm the node solution across variability regimes from near-deterministic to strongly bursty, where matched-mean exponential approximations deviate by up to 33%, network mean queues over 24 links are predicted within 12.7 vehicles, and a network evaluation completes in about 0.26 s. Embedded as the fitness kernel of a warm-started rolling hybrid metaheuristic, the evaluator reduces network vehicle-hours by 13.9% relative to uniform fixed timing and 12.4% versus a cycle-based max-pressure baseline on a nine-intersection network, making phase-level rolling optimization computationally feasible with an explicit causal chain from settings to performance.",
  "abstract_shown": true,
  "affiliations": [
    "National Engineering Laboratory of Integrated Transportation Big Data Application Technology, National United Engineering Laboratory of Integrated and Intelligent Transportation, School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, China"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Dan Tu"
    },
    {
      "affs": [
        0
      ],
      "name": "Rong Liang"
    },
    {
      "affs": [
        0
      ],
      "name": "Caiwen Luo"
    },
    {
      "affs": [
        0
      ],
      "name": "Yi Wang"
    },
    {
      "affs": [
        0
      ],
      "name": "Zhihong Yao",
      "orcid": "0000-0001-6946-2367"
    },
    {
      "affs": [
        0
      ],
      "name": "Yangsheng Jiang",
      "orcid": "0000-0003-4137-0721"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/e39sbw7s4h0pz.bib",
  "cited_by": 0,
  "doi": "10.3390/math14203755",
  "fulltext_url": null,
  "id": "e39sbw7s4h0pz",
  "issns": [
    "2227-7390"
  ],
  "landing_url": "https://www.mdpi.com/2227-7390/14/20/3755",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2207|Traffic control and management"
    ]
  ],
  "openalex": "W7222542454",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-16",
  "publisher": "MDPI AG",
  "ris": "https://research.draconitic.com/paper/e39sbw7s4h0pz.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:29Z",
      "native_id": "10.3390/math14203755",
      "source": "crossref",
      "url": "https://www.mdpi.com/2227-7390/14/20/3755"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "issn:2227-7390",
      "subfield": "general"
    }
  ],
  "title": "State-Dependent Phase-Type Queueing Networks for Urban Traffic Signal Control",
  "title_text": "State-Dependent Phase-Type Queueing Networks for Urban Traffic Signal Control",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:29Z",
  "url": "https://research.draconitic.com/paper/e39sbw7s4h0pz",
  "venue": "Mathematics",
  "versions": []
}