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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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Lei Zhou, Weiye Xiao, Chen Wang, Haoran Wang
Pág. 143 - 161
Human mobility datasets, such as traffic flow data, reveal the connections between urban spaces. A novel framework is proposed to explore the spatial association between urban commercial and residential spaces via consumption travel flows in Shanghai. A ...
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Yupei Shu, Xu Chen and Xuan Di
This paper aims to use location-based social media data to infer the impact of the Russia?Ukraine war on human mobility. We examine the impact of the Russia?Ukraine war on changes in human mobility in terms of the spatial range of check-in locations usin...
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Lama Ayad, Hocine Imine, Claudio Lantieri and Francesca De Crescenzio
Cyclists are at a higher risk of being involved in accidents. To this end, a safer environment for cyclists should be pursued so that they can feel safe while riding their bicycles. Focusing on safety risks that cyclists may face is the main key to prese...
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Vincent Obry-Legros, Geneviève Boisjoly
Pág. 67 - 96
While the influence of land use and transport networks on travel behavior is known, few studies have jointly examined the effects of home and work location characteristics when modelling travel behavior. In this study, a two-step approach is proposed to ...
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Ngoc An Nguyen, Joerg Schweizer, Federico Rupi, Sofia Palese and Leonardo Posati
The present study contributes to narrowing down the research gap in modeling individual door-to-door trips in a superblock scenario and in evaluating the respective impacts in terms of travel times, modal shifts, traffic performance, and environmental be...
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Haiqiang Yang and Zihan Li
The objective imbalance between the taxi supply and demand exists in various areas of the city. Accurately predicting this imbalance helps taxi companies with dispatching, thereby increasing their profits and meeting the travel needs of residents. The ap...
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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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Jiusheng Du, Chengyang Meng and Xingwang Liu
This study utilizes taxi trajectory data to uncover urban residents? travel patterns, offering critical insights into the spatial and temporal dynamics of urban mobility. A fusion clustering algorithm is introduced, enhancing the clustering accuracy of t...
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R. J. Roosien, M. N. A. Lim, S. M. Petermeijer and W. F. Lammen
To reduce the carbon footprint of transport, policymakers are simultaneously stimulating cleaner vehicles and more sustainable mobility choices, such as a shift to rail for short-haul flights within Europe. The purpose of this study is to determine the c...
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