Urban Traffic Analysis through an UAV

Salvo, Giuseppe; Caruso, Luigi; Scordo, Alessandro

doi:10.1016/j.sbspro.2014.01.143

Cited by 114 publications

(43 citation statements)

References 8 publications

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“…It has been used in various fields, both for military and civilian purposes. As a traffic data collection tool, UAV was used in research conducted by Barmpounakis et al [25], Coifman et al [26], and Salvo et al [27]. The use of UAVs in traffic surveys has the advantage of providing cost-effective "eye in the sky" solutions [25].…”

Section: The Challenges For Traffic Conflict Studies In Indonesiamentioning

confidence: 99%

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A brief review: traffic conflict techniques and the challenges of the studies in Indonesia

Kusumastutie

Rusmandani

2019

MATEC Web Conf.

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For the past 50 years, Traffic Conflict Technique (TCT) has been growing rapidly as Surrogate Safety Measure (SSM). Unfortunately, the study of TCT as a road safety analysis tool in Indonesia is still limited. This article aims to describe the developments of TCT, regarding to the use of manual observation, automated video analysis and simulations with the Surrogate Safety Assessment Model (SSAM). This article also aims to identify the challenges of TCT implementation in improving road safety in Indonesia. Thus, it is expected to inspire researchers in Indonesia to develop TCT, for example by using Unmanned Aerial Vehicle (UAV) and microsimulation in TCT studies.

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Section: The Challenges For Traffic Conflict Studies In Indonesiamentioning

confidence: 99%

“…The use of UAVs in traffic surveys has the advantage of providing cost-effective "eye in the sky" solutions [25]. In addition, UAV also has no effect on driver behavior [27].…”

Section: The Challenges For Traffic Conflict Studies In Indonesiamentioning

confidence: 99%

A brief review: traffic conflict techniques and the challenges of the studies in Indonesia

Kusumastutie

Rusmandani

2019

MATEC Web Conf.

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“…However, the precision of the crowd information depends on environmental factors such as clear sky index, ambient luminescence, shadowing, etc. These images are employed to automatically analyze crowd count [88], [99], crowd density [89], visual surveillance [100], and urban traffic analysis [101].…”

Section: ) Social Network Datamentioning

confidence: 99%

Advances in Crowd Analysis for Urban Applications Through Urban Event Detection

Kaiser

Lwin

Mahmud

et al. 2018

IEEE Trans. Intell. Transport. Syst.

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Abstract-The recent expansion of pervasive computing technology has contributed with novel means to pursue human activities in urban space. The urban dynamics unveiled by these means generate an enormous amount of data. These data are mainly endowed by portable and radio-frequency devices, transportation systems, video surveillance, satellites, unmanned aerial vehicles, and social networking services. This has opened a new avenue of opportunities, to understand and predict urban dynamics in detail, and plan various real-time services and applications in response to that. Over the last decade, certain aspects of the crowd, e.g. mobility, sentimental, size estimation and behavioral, have been analyzed in detail and the outcomes have been reported. This article mainly conducted an extensive survey on various data sources used for different urban applications, the state-of-the-art on urban data generation techniques and associated processing methods in order to demonstrate their merits and capabilities. Then, a possible crowd event detection framework is discussed which fuses data from all the available pervasive technology sources. In addition, available open-access crowd datasets for urban event detection are provided along with relevant Application Programming Interfaces, and finally, some open challenges and promising research directions are outlined.Index Terms-Urban sensing, pervasive technology, crowd mobility and management, information fusion, decision support system, benchmark datasets.

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“…Zhang et al [10] devised a real-time traffic incident detection system based on video recording from a UAV. Salvo et al [11] extracted kinematic data of traffic in urban environments utilizing a UAV system.…”

Section: Introductionmentioning

confidence: 99%

Using Small Unmanned Aerial Vehicle in 3D Modeling of Highways with Tree-Covered Roadsides to Estimate Sight Distance

et al. 2019

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The safe and efficient operation of highways largely depends on the adequate provision of sight distance. Small unmanned aerial vehicles (UAVs) can be utilized to efficiently complete data acquisition very soon after identifying an issue when searching for potential highway safety risks. A double grid flight is proposed to obtain an adequate three-dimensional (3D) recreation of the road environment, ensuring an unbiased sight distance output. Then, a dense cloud point is derived through a Structure from Motion Multi-View Stereo process. The point cloud is classified to produce both a terrain model, characterized by its resolution, and a 3D-object model, characterized by the maximum edge length of the entities. The resulting road environment model is utilized to calculate sight distance in a geographic information system. The results enabled the detection of accident-prone locations caused by sight distance limitations. Moreover, the impact of the 3D modeling parameters on the results was assessed.

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Urban Traffic Analysis through an UAV

Cited by 114 publications

References 8 publications

A brief review: traffic conflict techniques and the challenges of the studies in Indonesia

A brief review: traffic conflict techniques and the challenges of the studies in Indonesia

Advances in Crowd Analysis for Urban Applications Through Urban Event Detection

Using Small Unmanned Aerial Vehicle in 3D Modeling of Highways with Tree-Covered Roadsides to Estimate Sight Distance

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