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萨尔瓦多城市交通网络 (SUNT):一个具有里程碑意义的时空数据集,用于公共交通
Marcos V Ferreira1, Matheus Souza2, Tatiane N Rios1,3
1Federal University of Bahia, Institute of Computing, Salvador, Brazil.
Scientific data
|July 30, 2025
概括
本研究介绍了SUNT数据集,这是来自巴西萨尔瓦多的城市公共交通数据的大规模收集. 它使人们能够更好地了解交通模式,从而实现高效的城市流动性和环境效益.
科学领域:
- 城市规划与交通科学 城市规划与交通科学
- 数据科学和大数据分析
背景情况:
- 高效的公共交通对于城市发展至关重要,它影响了流动性,成本,拥堵和环境可持续性.
- 了解乘客和运输模式是优化城市交通系统的关键.
研究的目的:
- 引入SUNT数据集,这是一个新的,全面的,公开可用的城市数据集.
- 促进公共交通管理和城市流动性建模方面的研究.
主要方法:
- 收集大约70万个人的每日乘客数据.
- 整合公共交通数据,包括约2,000辆车辆,约400条线路和约3,000个站点/站点.
- 数据收集时间超过一年 (2024年3月至2025年3月),采用高频 (分分钟) 采集.
主要成果:
- SUNT数据集是该领域最大和最全面的开放式城市数据集之一.
- 它涵盖多种公共交通方式:常规公共汽车,地铁和公共汽车快速运输 (BRT).
- 提供关于巴西主要城市乘客流和车辆运行的细节数据.
结论:
- SUNT数据集为旨在改善城市公共交通的研究人员和政策制定者提供了宝贵的资源.
- 促进城市流动,交通模式和减少环境影响的先进建模.
- 支持在大型城市中心开发更高效,更可持续的公共交通系统.
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