Tracking and Simulating Pedestrian Movements at Intersections Using Unmanned Aerial Vehicles

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Bibliographische Detailangaben
Veröffentlicht in:	Remote Sensing vol. 11, no. 8 (Feb 2019), p. n/a
1. Verfasser:	Zhu, Jiasong
Weitere Verfasser:	Chen, Siyuan, Tu, Wei, Sun, Ke
Veröffentlicht:	MDPI AG
Schlagworte:	France China International conferences Pedestrians Artificial neural networks Roads & highways Unmanned aerial vehicles Tracking Distance learning Traffic congestion Traffic conflicts Pedestrian traffic flow Computer simulation Pattern recognition Vehicles Bicycling Global positioning systems > GPS Traffic flow Pedestrian safety Social organization Traffic signals Traffic accidents & safety Target recognition Neural networks Moving targets Maximum likelihood estimation Methods Transit time Algorithms Movement Informatics Traffic control Urban transportation Internet of Things Traffic intersections Laboratories
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