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Tracking and Simulating Pedestrian Movements at Intersections Using Unmanned Aerial Vehicles

Պահպանված է:
Հրատարակված է:Remote Sensing vol. 11, no. 8 (Feb 2019), p. n/a
Հիմնական հեղինակ: Zhu, Jiasong
Այլ հեղինակներ: Chen, Siyuan, Tu, Wei, Sun, Ke
Հրապարակվել է:
MDPI AG
Խորագրեր:
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
Առցանց հասանելիություն:Citation/Abstract
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Համառոտագրություն:For a city to be livable and walkable is the ultimate goal of future cities. However, conflicts among pedestrians, vehicles, and cyclists at traffic intersections are becoming severe in high-density urban transportation areas, especially in China. Correspondingly, the transit time at intersections is becoming prolonged, and pedestrian safety is becoming endangered. Simulating pedestrian movements at complex traffic intersections is necessary to optimize the traffic organization. We propose an unmanned aerial vehicle (UAV)-based method for tracking and simulating pedestrian movements at intersections. Specifically, high-resolution videos acquired by a UAV are used to recognize and position moving targets, including pedestrians, cyclists, and vehicles, using the convolutional neural network. An improved social force-based motion model is proposed, considering the conflicts among pedestrians, cyclists, and vehicles. In addition, maximum likelihood estimation is performed to calibrate an improved social force model. UAV videos of intersections in Shenzhen are analyzed to demonstrate the performance of the presented approach. The results demonstrate that the proposed social force-based motion model can effectively simulate the movement of pedestrians and cyclists at road intersections. The presented approach provides an alternative method to track and simulate pedestrian movements, thus benefitting the organization of pedestrian flow and traffic signals controlling the intersections.
ISSN:2072-4292
DOI:10.3390/rs11080925
Աղբյուր:Advanced Technologies & Aerospace Database