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.
Highlights
The aim of this paper is to examine the use of Unmanned aerial vehicles (UAVs) as a tool for microscopic traffic data collection and The analysis
Several applications regarding microscopic traffic data analysis can be carried out is of great importance, since many conflicts occur in this type of intersections [43,44]
Accurate and high detailed naturalistic microscopic traffic data are essential for re5
Summary
Several applications can be implemented by using the acquired dataset in terms of traffic safety, road capacity, and level of service analysis [1,2,3,4]. As the traffic conditions get more complex, the level of detail and the quality of the collected information is getting higher. The forthcoming applications of intelligent transport systems on vehicles and infrastructure mean that existing road layouts need to be examined across a wider range of scenarios [5]. As new technologies are applied to transport systems, accurate calibration and validation approaches of microscopic traffic flow models are essential. A dataset of accurate and high detailed microscopic traffic data can improve the reliability of models and allow a sufficient traffic analysis
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