five

Related works.

收藏
Figshare2025-09-16 更新2026-04-28 收录
下载链接:
https://figshare.com/articles/dataset/Related_works_/30139501
下载链接
链接失效反馈
官方服务:
资源简介:
Public transportation is essential for smart city development, especially in rapidly growing urban areas. In Riyadh, Saudi Arabia, the implementation of the metro system is expected to significantly impact the city’s transportation dynamics. This study uses Call Detail Records (CDRs) to analyze human mobility patterns and predict metro usage in 2024. This study also developed a methodology to categorize Traffic Analysis Zones (TAZs) and create metro zones, aiding in the visualization of the city’s population distribution and expected flow around the upcoming metro stations. Demographic data, including information on females and non-Saudis, was incorporated to predict metro usage more accurately. This approach identified areas with higher anticipated metro demand for the metro and potential feeder bus routes to support transportation efficiency. The insights gained from this analysis contribute to optimizing the metro system and addressing the needs of target populations, such as women and non-Saudi residents. This study demonstrates how mobile phone data can enhance transport planning in emerging urban environments.
创建时间:
2025-09-16
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作