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<p>The study investigates public bus transportation data in Macau during normal and Macau Grand Prix seasons. Utilizing real-time data collected from the Transport database, a comparative analysis highlights variations in bus operational metrics such as passenger flow, arrival times, and traffic conditions between standard and event periods. The findings reveal significant spikes in passenger volume and increased traffic congestion associated with the Grand Prix, emphasizing how large-scale events impact public transport dynamics. Through Principal Component Analysis (PCA) and correlation heatmaps, the research illustrates differences in transportation patterns, providing insights essential for enhancing service delivery and operational planning. This dataset aims to serve as a critical resource for future transport policy development and smart city initiatives, advocating for better utilization of data generated by public transport authorities. These insights aim to optimize resource allocation and improve overall urban mobility during major events in the region.</p>

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A Dataset on Public Bus Transportation during Normal and Grand Prix Seasons in the Macao Area

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月26日

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  • Song-Kyoo Kim,
  • Junbo Wang

摘要

The study investigates public bus transportation data in Macau during normal and Macau Grand Prix seasons. Utilizing real-time data collected from the Transport database, a comparative analysis highlights variations in bus operational metrics such as passenger flow, arrival times, and traffic conditions between standard and event periods. The findings reveal significant spikes in passenger volume and increased traffic congestion associated with the Grand Prix, emphasizing how large-scale events impact public transport dynamics. Through Principal Component Analysis (PCA) and correlation heatmaps, the research illustrates differences in transportation patterns, providing insights essential for enhancing service delivery and operational planning. This dataset aims to serve as a critical resource for future transport policy development and smart city initiatives, advocating for better utilization of data generated by public transport authorities. These insights aim to optimize resource allocation and improve overall urban mobility during major events in the region.