Transport Geography, GIS and GPS
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Transportation and Future Mobility".
Deadline for manuscript submissions: closed (15 April 2022) | Viewed by 7379
Special Issue Editor
Interests: intelligent mobility; trajectory representation learning; taxi trajectory data compression and visualization; time and space trajectory mining and analysis; modeling of human movement behavior; intelligent unmanned system
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the proliferation of GPS devices and wireless communication technologies in daily life, recent years have witnessed an increasing number of GPS-equipped vehicles, reporting their real-time moving locations to data centers continuously. On the other hand, due to convenience and speed, vehicles have become one of the most common transportation methods to move around the city. As a result, trajectory data that record where and when people move are now being gathered and readily available on a large scale, providing us a time-evolving view to understand how city transport takes place from a data-driven perspective. Nonetheless, a considerable gap still exists between data collection and consequent extraction of actionable insights when building smart cities. Such a gap poses fundamental challenges to how we can achieve such insights. To narrow this gap, advanced mathematical techniques are necessary. Such methods have particular technical challenges to overcome, which include algorithm effectiveness, computation speed, energy efficiency, user privacy, server security, and overall system scalability. This Special Issue aims to present state-of-the-art research achievements in addressing the above mentioned challenges in converting pervasive observation data to actionable insights, especially in the context of moving vehicles.
Prof. Dr. Chao Chen
Guest Editor
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