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

Abstract 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 traff...

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Main Authors: Song-Kyoo Kim, Junbo Wang
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-025-05660-y
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author Song-Kyoo Kim
Junbo Wang
author_facet Song-Kyoo Kim
Junbo Wang
author_sort Song-Kyoo Kim
collection DOAJ
description Abstract 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.
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spelling doaj-art-7e1a795b981843f3bd608d98f5e8b13e2025-08-20T03:42:44ZengNature PortfolioScientific Data2052-44632025-07-011211810.1038/s41597-025-05660-yA Dataset on Public Bus Transportation during Normal and Grand Prix Seasons in the Macao AreaSong-Kyoo Kim0Junbo Wang1Faculty of Applied Sciences, Macao Polytechnic UniversityFaculty of Applied Sciences, Macao Polytechnic UniversityAbstract 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.https://doi.org/10.1038/s41597-025-05660-y
spellingShingle Song-Kyoo Kim
Junbo Wang
A Dataset on Public Bus Transportation during Normal and Grand Prix Seasons in the Macao Area
Scientific Data
title A Dataset on Public Bus Transportation during Normal and Grand Prix Seasons in the Macao Area
title_full A Dataset on Public Bus Transportation during Normal and Grand Prix Seasons in the Macao Area
title_fullStr A Dataset on Public Bus Transportation during Normal and Grand Prix Seasons in the Macao Area
title_full_unstemmed A Dataset on Public Bus Transportation during Normal and Grand Prix Seasons in the Macao Area
title_short A Dataset on Public Bus Transportation during Normal and Grand Prix Seasons in the Macao Area
title_sort dataset on public bus transportation during normal and grand prix seasons in the macao area
url https://doi.org/10.1038/s41597-025-05660-y
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