Automatic Traffic Safety Analysis using Unmanned Aerial Vehicle Technology at Unsignalized Intersections in Heterogeneous Traffic

A generalized, reliable unmanned aerial vehicle (UAV) system for visual tracking and detection of road vehicles from aerial videography would outperform traditional traffic monitoring systems, providing extensive coverage and optimal study area perspectives. The combination of UAV technology for data collection and advanced video processing tools for visual tracking would assist traffic engineers in a detailed spatial and temporal utilization analysis with accurate traffic characteristics. Initially, traffic conflicts were determined by post encroachment time from visual data at unsignalized intersection. But a new concept (known as “required post encroachment time”) has been proposed to differentiate between critical and non-critical conflicts among road users. Finally, by extracting the information of vehicle trajectories, we have also developed a “collision probability evaluation model” to determine the severity level of critical conflicts in heterogeneous traffic conditions. Our numerical results show the high precision of our suggested model with regard to risk recognition when evaluating the collision probability at the study intersection. This research utilizes vehicle trajectories to evaluate driving risk at intersections through automatic traffic safety analysis.

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Publication Details

Journal
Transportation Research Record Journal of the Transportation Research Board
Published
2024-08-09
DOI
https://doi.org/10.1177/03611981241266838
Citations
4
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
Field-Weighted Citation Impact
0.81
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article

Automatic Traffic Safety Analysis using Unmanned Aerial Vehicle Technology at Unsignalized Intersections in Heterogeneous Traffic

K. Ramachandra Rao, Niladri Chatterjee, Debashis Sarkar
4 citations
Transportation Research Record Journal of the Transportation Research Board
Autonomous Vehicle Technology and Safety
0.81
article

Automatic Traffic Safety Analysis using Unmanned Aerial Vehicle Technology at Unsignalized Intersections in Heterogeneous Traffic

K. Ramachandra Rao, Niladri Chatterjee, Debashis Sarkar
article en
4 citations

Abstract

A generalized, reliable unmanned aerial vehicle (UAV) system for visual tracking and detection of road vehicles from aerial videography would outperform traditional traffic monitoring systems, providing extensive coverage and optimal study area perspectives. The combination of UAV technology for data collection and advanced video processing tools for visual tracking would assist traffic engineers in a detailed spatial and temporal utilization analysis with accurate traffic characteristics. Initially, traffic conflicts were determined by post encroachment time from visual data at unsignalized intersection. But a new concept (known as “required post encroachment time”) has been proposed to differentiate between critical and non-critical conflicts among road users. Finally, by extracting the information of vehicle trajectories, we have also developed a “collision probability evaluation model” to determine the severity level of critical conflicts in heterogeneous traffic conditions. Our numerical results show the high precision of our suggested model with regard to risk recognition when evaluating the collision probability at the study intersection. This research utilizes vehicle trajectories to evaluate driving risk at intersections through automatic traffic safety analysis.

Transportation Research Record Journal of the Transportation Research BoardVol. 2679(2)
Indian Institute of Technology Delhi (IN)
Sustainable cities and communities
Openalex Percentile: Top 29%
Autonomous Vehicle Technology and Safety
0.81
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Automatic Traffic Safety Analysis using Unmanned Aerial Vehicle Technology at Unsignalized Intersections in Heterogeneous Traffic — K. Ramachandra Rao, Niladri Chatterjee, et al. · Transportation Research Record Journal of the Transportation Research Board (2024) | TGRS Research Map | TGRS