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Sebastián Vallejos, Luis Berdun, Marcelo Armentano, Silvia Schiaffino and Daniela Godoy
Data captured by mobile devices enable us, among other things, learn the places where users go, identify their home and workplace, the places they usually visit (e.g., supermarket, gym, etc.), the different paths they take to move from one place to anoth...
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Hui Zhang, Yu Cui, Yanjun Liu, Jianmin Jia, Baiying Shi and Xiaohua Yu
Dockless bike-sharing (DBS) is a green and flexible travel mode, which has been considered as an effective way to address the first-and-last mile problem. A two-level process is developed to identify the integrated DBS?metro trips. Then, DBS trip data, m...
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Yafei Xi, Quanhua Hou, Yaqiong Duan, Kexin Lei, Yan Wu and Qianyu Cheng
Exploring the correlation of the built environment with metro ridership is vital for fostering sustainable urban growth. Although the research conducted in the past has explored how ridership is nonlinearly influenced by the built environment, less resea...
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Maja Ahac, Sa?a Ahac, Igor Majstorovic and ?eljko Stepan
This paper aims to contribute to the process of evaluating urban rail infrastructure projects through the presentation of the methodology and the results of a preliminary feasibility study concerning the revitalization, development, and (re)integration o...
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Zhenzhong Yin and Bin Zhang
Providing accurate and real-time bus travel time information is crucial for both passengers and public transportation managers. However, in the traditional bus travel time prediction model, due to the lack of consideration of the influence of different b...
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