Unmanned Aerial Vehicle-Based Traffic Analysis: A Case Study for Shockwave Identification and Flow Parameters Estimation at Signalized Intersections

Abstract

Owing to their dynamic and multidisciplinary characteristics, Unmanned Aerial Vehicles (UAVs), or drones, have become increasingly popular. However, the civil applications of this technology, particularly for traffic data collection and analysis, still need to be thoroughly explored. For this purpose, the authors previously proposed a detailed methodological framework for the automated UAV video processing in order to extract multi-vehicle trajectories at a particular road segment. In this paper, however, the main emphasis is on the comprehensive analysis of vehicle trajectories extracted via a UAV-based video processing framework. An analytical methodology is presented for: (i) the automatic identification of flow states and shockwaves based on processed UAV trajectories, and (ii) the subsequent extraction of various traffic parameters and performance indicators in order to study flow conditions at a signalized intersection. The experimental data to analyze traffic flow conditions was obtained in the city of Sint-Truiden, Belgium. The generation of simplified trajectories, shockwaves, and fundamental diagrams help in analyzing the interrupted-flow conditions at a signalized four-legged intersection using UAV-acquired data. The analysis conducted on such data may serve as a benchmark for the actual traffic-specific applications of the UAV-acquired data. The results reflect the value of flexibility and bird-eye view provided by UAV videos; thereby depicting the overall applicability of the UAV-based traffic analysis system. The future research will mainly focus on further extensions of UAV-based traffic applications.

Tutorial on UAVs: A Blue Sky View onWireless Communication

“…detection [10,29], ii) tracking [110] and iii) analysis of the collected information (e.g. the flow density and dynamics) [55]. In addition, UAVs can be deployed on demand in a fast and dynamic way.…”

Applications of unmanned aerial vehicle (UAV) in road safety, traffic and highway infrastructure management: Recent advances and challenges

“…They have analysed this based on manually observing the UAVs videos. Khan et al (2018a) extended their work presented in Khan et al (2017) in relation to further processing of acquired vehicle trajectories from UAV data. Vehicle trajectories are processed in relation to obtaining critical points in the trajectory to classify them under various flow regimes i.e.…”

Advanced framework for microscopic and lane‐level macroscopic traffic parameters estimation from UAV video

“…The most recent studies in UAV‐based traffic surveillance focus on vehicle detection [14–16, 28–34], vehicle tracking [12, 18, 28–30, 32, 34–36], traffic pattern recognition [13, 37], and traffic parameters estimation [3, 10, 17, 19–21, 23–26, 38]. Vehicle detection and vehicle tracking are usually the initialisation process for traffic pattern recognition and traffic parameter estimation.…”

“…Thus, developing vehicle detectors and trackers with high efficiency, accuracy, and robustness is very important for advanced traffic surveillance tasks. While traditional vehicle detection in UAV videos tended to use background modelling or conventional machine learning with handcrafted features [14, 28–32], more and more studies started to design or implement deep learning based vehicle detectors for UAV surveillance due to the high accuracy of deep neural networks in image classification and localisation [25, 33, 35, 37, 38]. Vehicle detection itself is able to determine traffic parameters like density without the need for motion analysis or vehicle tracking.…”