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<p>This paper presents a scalable methodology for real-time transfer synchronization in urban bus networks, using online stochastic optimization (<span>OSO</span>). The approach integrates three key components. First, an offline arc-flow model captures all control tactics—<i>hold</i>, <i>speedup</i>, and <i>skip-stop</i>—for a main line and its feeder connections, using a graph-based representation over a fixed control horizon. Second, the Regret (<span>R</span>) algorithm operates in real time within an <span>OSO </span>framework, leveraging the offline model to evaluate multiple stochastic scenarios and to select robust control tactics. Third, a network-wide simulator (<span>NWS</span>) integrates the full <span>OSO </span>framework and re-optimizes decisions dynamically at each bus departure from any stop, allowing the coordination of multiple interconnected lines. The <span>NWS</span> is applied to the transit network of Laval, Canada, using historical vehicle positions and smart card validations to replicate real-time stochastic conditions. Results show significant improvements in both passenger travel and transfer times across a variety of network structures, highlighting the scalability and applicability of real-time transfer synchronization for urban multi-line transit networks.</p>

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Network-wide transfer synchronization strategies in a public bus system with real-time AVL and smart card data

  • 期刊论文

  • 发表日期：

    2026年3月18日

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  • Laura Kolcheva,
  • Antoine Legrain,
  • Martin Trépanier

摘要

This paper presents a scalable methodology for real-time transfer synchronization in urban bus networks, using online stochastic optimization (OSO). The approach integrates three key components. First, an offline arc-flow model captures all control tactics—hold, speedup, and skip-stop—for a main line and its feeder connections, using a graph-based representation over a fixed control horizon. Second, the Regret (R) algorithm operates in real time within an OSO framework, leveraging the offline model to evaluate multiple stochastic scenarios and to select robust control tactics. Third, a network-wide simulator (NWS) integrates the full OSO framework and re-optimizes decisions dynamically at each bus departure from any stop, allowing the coordination of multiple interconnected lines. The NWS is applied to the transit network of Laval, Canada, using historical vehicle positions and smart card validations to replicate real-time stochastic conditions. Results show significant improvements in both passenger travel and transfer times across a variety of network structures, highlighting the scalability and applicability of real-time transfer synchronization for urban multi-line transit networks.