Unmanned Aerial System Automation Using Artificial Intelligence Tools
This project will conduct an exploratory analysis of artificial intelligence (AI) tools to aid with the automation of Unmanned Aerial Systems (UAS) use case activities across transportation with a focus on potential applications for transportation system benefits. This is an area of great potential for innovation through the use of advanced technologies in a synergistic manner. The project will focus on representative use cases where AI can enable advanced data processing and decision-making, such as: infrastructure inspection (e.g., rail track condition monitoring, construction progress tracking); operations and safety (e.g., traffic monitoring for incidents and special events); and UAS operating conditions monitoring (e.g., wildlife detection, vegetation health assessment). These use cases represent areas where AI-driven computer vision, predictive analytics, and anomaly detection can significantly improve efficiency, safety, and sustainability. Additionally, the project will explore how AI-enabled UAS operations can contribute to energy benefits and cost savings by optimizing inspection schedules, reducing fuel-intensive manual operations, and supporting compliance with regulatory standards. In the context of the above-described use cases, the research team will conduct the following activities: (1) identify commercial AI-enabled tools currently available for purchase or license and assess their capabilities for UAS data integration; (2) evaluate how these tools can be modified or expanded to meet the specific needs of transportation related monitoring applications; and (3) develop prototype workflows demonstrating AI-enabled automation for UAS operations.
Language
- English
Project
- Status: Active
- Funding: $70,000.00
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Contract Numbers:
69A3552348329
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
1111 Rellis Parkway
Bryan, Texas United States 77807 -
Project Managers:
Ocon, Monica
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Performing Organizations:
Texas A&M Transportation Institute
Texas A&M University System
3135 TAMU
College Station, TX United States 77843-3135 -
Principal Investigators:
Shukla, Harshit
Kraus, Edgar
Primes, Markus
- Start Date: 20260301
- Expected Completion Date: 20261231
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers
- Source Data: 03-05-TTI
Subject/Index Terms
- TRT Terms: Artificial intelligence; Autonomous vehicles; Case studies; Drones; Inspection; Monitoring; Operations
- Subject Areas: Aviation; Data and Information Technology; Maintenance and Preservation; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment;
Filing Info
- Accession Number: 01981634
- Record Type: Research project
- Source Agency: Center for Advancing Research in Transportation Emissions, Energy, and Health (CARTEEH)
- Contract Numbers: 69A3552348329
- Files: UTC, RIP
- Created Date: Mar 3 2026 4:49PM