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Riga International Coach Terminal (RICT) plays a key role in Latvia’s public transportation network, serving as a key intermodal hub with approximately 400 routes and 2.3 million passengers annually. Despite its central function, RICT suffers from serious operational challenges stemming from limited infrastructure leading to capacity bottlenecks and inefficient resource utilization. The terminal’s constrained urban location further complicates access and maneuverability, affecting both passenger flow and bus operations. This research proposes the implementation of Artificial Intelligence (AI) framework to enhance operational efficiency and optimize platform allocation at RICT. By leveraging data-driven technologies, this framework aims to not only extend the functional life of the terminal but also align Riga’s transport infrastructure with broader European goals for interconnectivity and efficiency enhancement.

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Artificial Intelligence for Enhanced Bus Flow Management at Riga International Coach Terminal

  • 会议论文

  • 发表日期：

    2026年

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  • Vaira Gromule,
  • Juris Pepulis,
  • Irina Yatskiv

摘要

Riga International Coach Terminal (RICT) plays a key role in Latvia’s public transportation network, serving as a key intermodal hub with approximately 400 routes and 2.3 million passengers annually. Despite its central function, RICT suffers from serious operational challenges stemming from limited infrastructure leading to capacity bottlenecks and inefficient resource utilization. The terminal’s constrained urban location further complicates access and maneuverability, affecting both passenger flow and bus operations. This research proposes the implementation of Artificial Intelligence (AI) framework to enhance operational efficiency and optimize platform allocation at RICT. By leveraging data-driven technologies, this framework aims to not only extend the functional life of the terminal but also align Riga’s transport infrastructure with broader European goals for interconnectivity and efficiency enhancement.