Utilizing UAVs Technology on Microscopic Traffic Naturalistic Data Acquirement

Abstract

Research into collecting and measuring reliable, accurate, and naturalistic microscopic traffic data is a fundamental aspect in road network planning scientific literature. The vehicle trajectory is one of the main variables in traffic flow theory that allows to extract information regarding microscopic traffic flow characteristics. Several methods and techniques have been applied regarding the acquisition of vehicle trajectory. The forthcoming applications of intelligent transport systems on vehicles and infrastructure require sufficient and innovative tools to calibrate existing models on more complex situations. Unmanned aerial vehicles (UAVs) are one of the most emerging technologies being used recently in the transportation field to monitor and analyze the traffic flow. The aim of this paper is to examine the use of UAVs as a tool for microscopic traffic data collection and analysis. A comprehensive guiding framework for accurate and cost-effective naturalistic traffic surveys and analysis using UAVs is proposed and presented in detail. Field experiments of acquiring vehicle trajectories on two multilane roundabouts were carried out following the proposed framework. Results of the experiment indicate the usefulness of the UAVs technology on various traffic analysis studies. The results of this study provide a practical guide regarding vehicle trajectory acquirement using UAVs.

An Adaptive Deblurring Vehicle Detection Method for High-Speed Moving Drones: Resistance to Shake

“…Unmanned aerial vehicles (UAVs) are increasingly used in plant protection [1], disaster relief [2], traffic monitoring [3], urban planning [4] and other fields [5][6][7][8][9] owing to their low cost, high flexibility, ease of operation and small size. The detection and classification of vehicles in aerial images is one of the important applications for drones, which is applied to the intelligent traffic system for traffic flow estimation and vehicle identification gradually, which is an application trend in the future.…”