The study aims to evaluate the veracity of the Data from Sky (DFS) tool in processing and analyzing traffic data in heterogeneous and area-based traffic conditions, which are prevalent in most developing countries. The methodology involves a comparative analysis of macroscopic variables, such as Classified Volume Count (CVC) and Space Mean Speeds (SMS), as well as microscopic vehicle trajectories, between the DFS output and manually extracted data.
The results show that the DFS tool performs well in the case of bird's-eye view data, with low errors in CVC and SMS. However, the performance of DFS degrades in angled data collected at different heights, with significant errors observed for certain vehicle classes, particularly Buses and Heavy Commercial Vehicles (HCVs). The errors are influenced by the traffic composition, camera view angle, and the direction of traffic movement (towards or away from the camera). The microscopic vehicle trajectories extracted from DFS are validated against GPS-based trajectories, and the results indicate a strong positive correlation, suggesting the reliability of DFS in capturing individual vehicle movements.
The study provides valuable insights into the applicability and limitations of the DFS tool in heterogeneous and area-based traffic contexts, offering guidance to researchers and practitioners on the appropriate use of this technology for traffic data collection and analysis.
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arxiv.org
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by Yawar Ali (1... at arxiv.org 04-29-2024
https://arxiv.org/pdf/2404.17212.pdfDeeper Inquiries