No abstract

Rapidly developing location acquisition technologies have provided us with big GPS trajectory data, which offers a new means of understanding people's daily behaviors as well as urban dynamics. With such data, predicting human mobility at the city level will be of great significance for transportation scheduling, urban regulation, and emergency management. In particular, most urban human behaviors are related to a small number of important regions, referred to as Regions-of-Interest (ROIs). Therefore, in this study, a deep ROI-based modeling approach is proposed for effectively predicting urban human mobility. Urban ROIs are first discovered from historical trajectory data, and urban human mobility is designated using two types of ROI labels (ISROI and WHICHROI). Then, urban mobility prediction is modeled as a sequence classification problem for each type of label. Finally, a deep-learning architecture built with recurrent neural networks is designed as an effective sequence classifier. Experimental results demonstrate that the superior performance of our proposed approach to the baseline models and several real-world practices show the applicability of our approach to real-world urban computing problems.

No abstract

The airdropping of multi-parafoil systems is of great significance to earthquake relief and military material transportation. In order to achieve the coordinated motion of multiple parafoils, a formation guidance strategy based on a virtual structure is proposed, which enables the formation of multiple parafoils to follow the planned trajectory and land at the target precisely. Firstly, since the main movement mode of a parafoil is turning and gliding, a multiphase homing trajectory for the reference point is planned, which mainly consists of a turning and gliding phase. Then, the trajectories of all the points on the virtual structure are generated by superimposing the relative positions of the virtual structure on the planned trajectory. Based on Lyapunov stability theory, a guidance strategy is designed to guide all parafoils to track the corresponding points on the virtual structure and complete the desired formation task. The simulation results show that the guidance strategy based on a virtual structure can effectively guide multiple parafoils to achieve coordinated formation movement. Parafoils dropped from different positions and heading angles can gradually gather together and form a formation, track the planned trajectories, land at the target point precisely and align up against the wind.