Abstract
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.
Highlights
With rapid economic development, the use of automobiles has greatly increased in developing countries, especially in China, India, and Vietnam, where vehicles are replacing bicycles as the dominant transportation mode [1,2]
In a recent traffic safety report released by the World Health Organization (WHO), road collisions are the world’s leading cause of preventable death; over 1.25 million people die annually on the roads because of traffic collisions [3]
Considering the interactions of pedestrians, cyclists, and vehicles, this study aims to track and simulate pedestrian movements at complex traffic intersections using advanced computer vision algorithms
Summary
The use of automobiles has greatly increased in developing countries, especially in China, India, and Vietnam, where vehicles are replacing bicycles as the dominant transportation mode [1,2]. Considering the interactions of pedestrians, cyclists, and vehicles, this study aims to track and simulate pedestrian movements at complex traffic intersections using advanced computer vision algorithms. These algorithms will provide microscopic simulations of traffic intersections to optimize traffic organization and promote pedestrian safety. Liu et al [42] explored various interactions of pedestrians on crosswalks by considering the collision avoidance behaviors of pedestrians moving backward and the follow-up behaviors of leading pedestrians, and established a microscopic model to incorporate the interactions between pedestrians and surrounding pedestrians These studies provided valuable insights into microscopic pedestrian traffic simulation. This study employs a UAV to automatically identify and track moving objects, including pedestrians, cyclists, and vehicles at complex traffic intersections, and to simulate the pedestrian movements.
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