A Temporal Planning Framework for Disruption Aware Dynamic Route Optimization in Heterogeneous Railway Systems

[2606.14582] A Temporal Planning Framework for Disruption Aware Dynamic Route Optimization in Heterogeneous Railway Systems Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Artificial Intelligence arXiv:2606.14582 (cs) [Submitted on 12 Jun 2026 ( v1 ), last revised 14 Aug 2026 (this version, v2)] Title: A Temporal Planning Framework for Disruption Aware Dynamic Route Optimization in Heterogeneous Railway Systems Authors: Pollob Chandra Ray , Sabah Binte Noor , Fazlul Hasan Siddiqui View a PDF of the paper titled A Temporal Planning Framework for Disruption Aware Dynamic Route Optimization in Heterogeneous Railway Systems, by Pollob Chandra Ray and 1 other authors View PDF HTML (experimental) Abstract: Efficient route optimization play a vital role in ensuring both safety and punctuality in railway operations. It is very crucial particularly in heterogeneous multi-gauge railway networks with varying train speed, stopping pattern, infrastructure compatibility constraints increase coordination complexity. In single-track systems these challenges are further intensify due to all trains to share the same track and requires frequent track this http URL disruptions events including blocked tracks, blocked trains, engine failure and speed slowdowns introduces additional unpredictability in operations and deviate the timetable. However, existing studies predominantly focuses on high-level timetabling, omitting operational details such as track switching coordination. As a result leaving decision to human operators, increasing safety risks into railway operations. This study proposes a framework based on temporal planning for dynamic route optimization and disruption management in heterogeneous railway systems. The framework formulates railway operations as a temporal planning problem using PDDL 2.1 with explicitly modeling gauge compatibility constraints and diverse disruption scenarios. It generates conflict-free timestamped operational plans specifying both optimized schedules and executable action sequences. To evaluate the proposed framework, we developed a benchmark problem set with 200 instances using up to 1,000 track points and 120 trains. Two state-of-the-art temporal planners and a plan validator were employed to assessed the framework. The experimental results demonstrate that the framework effectively generates temporal operational plans for heterogeneous railway systems and handles multi-gauge constraints, disruptions, and reduces dependence on manual decision making. Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2606.14582 [cs.AI] (or arXiv:2606.14582v2 [cs.AI] for this version) https://doi.org/10.48550/arXiv.2606.14582 Focus to learn more arXiv-issued DOI via DataCite Journal reference: Ray PC, Binte Noor S, Siddiqui FH (2026;), "Dynamic route optimization in disrupted heterogeneous railway systems via temporal planning". Railway Sciences, 2026 Related DOI : https://doi.org/10.1108/RS-06-2026-0047 Focus to learn more DOI(s) linking to related resources Submission history From: Sabah Binte Noor [ view email ] [v1] Fri, 12 Jun 2026 16:00:31 UTC (869 KB) [v2] Fri, 14 Aug 2026 20:51:06 UTC (875 KB) Full-text links: Access Paper: View a PDF of the paper titled A Temporal Planning Framework for Disruption Aware Dynamic Route Optimization in Heterogeneous Railway Systems, by Pollob Chandra Ray and 1 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.AI < prev | next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... 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