State-of-the-art review of unmanned aerial vehicles (UAVs) and artificial intelligence (AI) for traffic and safety analyses: Recent progress, applications, challenges, and opportunities

• Tracks the evolution of traffic analysis with UAV and AI integration. • Compares traditional video monitoring with modern UAV and AI approaches. • Reviews 248+ scholarly articles for comprehensive literature coverage. • Examines UAV roles in traffic operations, safety, and environmental studies. • Highlights challenges and future directions in UAV- and AI-based traffic analysis. This review comprehensively examines the intersection of Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence (AI) in traffic and safety analyses, addressing their transformative impact on traffic monitoring, safety assessment, and environmental studies. By systematically analyzing over 315 scholarly works from 2009 to 2024, this review highlights the evolution from traditional data collection methods to UAV-enabled systems enhanced by advanced AI algorithms. The findings reveal UAVs’ significant contributions to traffic operations monitoring, safety evaluations, and special environmental applications, demonstrating enhanced efficiency in collecting, analyzing, and interpreting high-resolution traffic data. For instance, UAVs have improved traffic flow estimation accuracy by over 20%, enabled detailed safety conflict analysis through surrogate safety measures like Time-to-Collision (TTC), and facilitated data collection protocols optimized for diverse facility types, including intersections and roundabouts. Key challenges, such as data privacy, integration with existing systems, and weather-related limitations, are critically discussed. The review identifies future research directions, emphasizing the potential for autonomous UAV operations, ethical frameworks, and cost-effective scaling. Ultimately, this review underscores UAVs and AI as pivotal technologies reshaping traffic analysis, enabling smarter, safer, and more sustainable transportation systems.

Authors

Institutions

Publication Details

Journal
Transportation Research Interdisciplinary Perspectives
Published
2025-08-31
DOI
https://doi.org/10.1016/j.trip.2025.101591
Citations
4
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
19.97

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

State-of-the-art review of unmanned aerial vehicles (UAVs) and artificial intelligence (AI) for traffic and safety analyses: Recent progress, applications, challenges, and opportunities

Khaled Hamad, Karim Ismail, Lubna Obaid, Rami Issa Al-Ruzouq et al.
4 citations
Transportation Research Interdisciplinary Perspectives
UAV Applications and Optimization
19.97
article

State-of-the-art review of unmanned aerial vehicles (UAVs) and artificial intelligence (AI) for traffic and safety analyses: Recent progress, applications, challenges, and opportunities

Khaled Hamad, Karim Ismail, Lubna Obaid, Rami Issa Al-Ruzouq, Saleh Abu Dabous, Emran Alotaibi
article en
4 citations

Abstract

• Tracks the evolution of traffic analysis with UAV and AI integration. • Compares traditional video monitoring with modern UAV and AI approaches. • Reviews 248+ scholarly articles for comprehensive literature coverage. • Examines UAV roles in traffic operations, safety, and environmental studies. • Highlights challenges and future directions in UAV- and AI-based traffic analysis. This review comprehensively examines the intersection of Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence (AI) in traffic and safety analyses, addressing their transformative impact on traffic monitoring, safety assessment, and environmental studies. By systematically analyzing over 315 scholarly works from 2009 to 2024, this review highlights the evolution from traditional data collection methods to UAV-enabled systems enhanced by advanced AI algorithms. The findings reveal UAVs’ significant contributions to traffic operations monitoring, safety evaluations, and special environmental applications, demonstrating enhanced efficiency in collecting, analyzing, and interpreting high-resolution traffic data. For instance, UAVs have improved traffic flow estimation accuracy by over 20%, enabled detailed safety conflict analysis through surrogate safety measures like Time-to-Collision (TTC), and facilitated data collection protocols optimized for diverse facility types, including intersections and roundabouts. Key challenges, such as data privacy, integration with existing systems, and weather-related limitations, are critically discussed. The review identifies future research directions, emphasizing the potential for autonomous UAV operations, ethical frameworks, and cost-effective scaling. Ultimately, this review underscores UAVs and AI as pivotal technologies reshaping traffic analysis, enabling smarter, safer, and more sustainable transportation systems.

Transportation Research Interdisciplinary PerspectivesVol. 33
Canadian University of Dubai (AE), University of Sharjah (AE), Carleton University (CA)
University of Sharjah
Openalex Percentile: Top 1%
UAV Applications and Optimization
19.97
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.