Kim Song-Kyoo, Wang Junbo
Faculty of Applied Sciences, Macao Polytechnic University, R. de Luis Gonzaga Gomes, Macau, China.
Sci Data. 2025 Jul 26;12(1):1306. doi: 10.1038/s41597-025-05660-y.
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.
该研究调查了澳门在正常时期和澳门格兰披治大赛车期间的公共巴士运输数据。利用从交通数据库收集的实时数据,一项比较分析突出了标准时期和赛事期间巴士运营指标(如客流量、到达时间和交通状况)的差异。研究结果显示,与大赛车相关的客流量显著飙升,交通拥堵加剧,凸显了大型活动对公共交通动态的影响。通过主成分分析(PCA)和相关热图,该研究展示了交通模式的差异,为加强服务提供和运营规划提供了至关重要的见解。该数据集旨在成为未来交通政策制定和智慧城市倡议的关键资源,倡导更好地利用公共交通当局生成的数据。这些见解旨在优化资源分配,并在该地区的重大活动期间改善整体城市流动性。