Enabling Smart Mobility for People and Beyond With Heterogeneous Trajectory Data

被引:0
|
作者
Zhang, Wanyi [1 ]
Meng, Fei [1 ]
Liao, Chengwu [2 ]
Chen, Chao [1 ]
机构
[1] Chongqing Univ, Chongqing 400044, Peoples R China
[2] China Unicom, Chongqing 401120, Peoples R China
关键词
D O I
10.1109/MITP.2024.3428333
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, with the prevalence of new ride services, such as ride-on-demand, human mobility has extended to the cyberphysical world meanwhile leaving behind heterogeneous people-centered trajectories on a large scale. Owing to the unique characteristics of trajectory data (e.g., pervasiveness, heterogeneous, and representativeness), it provides us a comprehensive view to understand human mobility from a data-driven perspective. Thus, it opens up valuable opportunities for developing knowledge-based smart mobility. In this article, we carefully introduce how to utilize trajectory data to enable elaborate smart mobility for a spectrum of people and beyond, aiming at providing a systematic guidance for the further research. Moreover, we point out several open issues and foresee a few new research directions, with hoped-for inspiring sustainable development in this field.
引用
收藏
页码:71 / 78
页数:8
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