{
  "abstract": "This study proposes an efficient and computationally light route based map matching method for GPS track data on urban expressway networks. The key idea is to exploit a symbolic structure of named lines and named junctions that link level map matching leaves unused. We represent each candidate route as a sequence of line and junction names, take the set of such sequences as a route codebook, and formulate map matching as scored alignment of a probe trajectory against members of the codebook. Probes become token sequences via a mesh quantizer, a precomputed grid mapping each coordinate to a line or junction token, and the decoder returns a member of the codebook by construction. The codebook is indexed by a DAFSA $\\times$ Levenshtein automaton, a fuzzy lookup technique from approximate string matching and speech recognition; the per query decoding cost is orders of magnitude lower than a brute force scan. We evaluate the method on a deformed replica of the Tokyo Metropolitan Expressway topology. The method recovers the exact route at moderate GPS noise and continues to identify the line and junction sequence under heavy noise; a sensitivity analysis maps the mesh resolution operating range. Real probe evaluation, channel model calibration, and a head to head HMM comparison are left to a forthcoming version.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2607.22543",
  "author_total": 2,
  "authors": [
    {
      "name": "Takara Sakai"
    },
    {
      "name": "Hiroyuki Hasada"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5y7qhqmy2mzxx.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2607.22543",
  "fulltext_url": null,
  "id": "5y7qhqmy2mzxx",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2607.22543",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.IR"
    ],
    [
      "arxiv",
      "cs.NI"
    ],
    [
      "arxiv",
      "math.OC"
    ],
    [
      "openalex",
      "1711|Data Management and Algorithms"
    ]
  ],
  "openalex": "W7171562398",
  "pdf_url": "https://arxiv.org/pdf/2607.22543",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-03",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/5y7qhqmy2mzxx.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:36Z",
      "native_id": "2607.22543",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2607.22543"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.OC",
      "subfield": "optimisation-control"
    }
  ],
  "title": "Route Based Map Matching via a Structured Codebook and Token Sequence Decoding",
  "title_text": "Route Based Map Matching via a Structured Codebook and Token Sequence Decoding",
  "type": "preprint",
  "updated_at": "2026-10-30T12:18:36Z",
  "url": "https://research.draconitic.com/paper/5y7qhqmy2mzxx",
  "venue": "arXiv",
  "versions": []
}