Corridor-wide Surveillance Using Unmanned Aircraft Systems Phase III: Exploration of the Implementation of Using Unmanned Aircraft Systems for Freeway Incident Detection and Management
In the last two phases of the project, the collaborative UPRM and USF research team (the research team hereafter) designed traffic data collection experiments on freeways with unmanned aerial systems (UAV with RGB and thermal cameras). The parameters of experiments included the height and speed of the drones, camera angles, congestion and non-congested traffic conditions, etc. The research team developed a learning-based object detection algorithm and evaluated the performance of the algorithm for RGB and thermal videos with different parameter settings and identified the settings with consistent high performance. In addition, the research team developed automated incident detection algorithms by identifying abnormal traffic characteristics. In Phase III of this project, the research team will focus on the validation of the algorithms developed in the previous phases and implementation matters of Phase II. Two main tasks of the research include: (1) validate object detection algorithm and automated incident detection algorithm developed in previous phases; (2) explore the integration of UAS with traffic management center. For the first task, researchers from UPRM will focus on incident detection with CCTV video. Traffic data during the incident will be collected with drones and shared with researchers from USF. Researchers from USF will focus on applying the incident detection algorithm for the data collected during the incident. Results from both analyses will be compared and insights from the comparison will be drawn. The same procedure will be applied to analyzing traffic data from the Tampa area. For the second task, researchers from UPRM and USF will work closely with Puerto Rico DTPW and Metric Engineering, and Florida DOT District 7. By understanding the barriers and challenges of implementing emerging technologies in automatic incident detection, the research team will work on implementation recommendations. (See also Phase I NICR Project 4-3: Corridor-Wide Surveillance Using Unmanned Aircraft Systems, Phase II Part A NICR Project 4-4.1 Corridor-Wide Surveillance Using Unmanned Aircraft Systems Phase II: Freeway Incident Detection using Unmanned Aircraft Systems Part A, and Phase II Part B NICR Project 4-4.1 Corridor-Wide Surveillance Using Unmanned Aircraft Systems Phase II: Freeway Incident Detection using Unmanned Aircraft Systems Part B)
Language
- English
Project
- Status: Active
- Funding: $159738
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Contract Numbers:
69A3551947136
79075-00-A
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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:
National Institute for Congestion Reduction
University of South Florida
Tampa, FL United States 33620 -
Project Managers:
Zhang, Yu
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Performing Organizations:
National Institute for Congestion Reduction
University of South Florida
Tampa, FL United States 33620University of Puerto Rico at Mayagüez
Department of Civil Engineering and Surveying
PO Box 9000
Mayagüez PR 00681-9000, PR United States 00681-9000 -
Principal Investigators:
Zhang, Yu
Cruzado Velez, Ivette
Kourtellis, Achilleas
Figueroa Medina, Alberto
- Start Date: 20220601
- Expected Completion Date: 20230630
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Automatic incident detection; Drones; Image processing; Traffic incidents
- Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management;
Filing Info
- Accession Number: 01853953
- Record Type: Research project
- Source Agency: National Institute for Congestion Reduction
- Contract Numbers: 69A3551947136, 79075-00-A
- Files: UTC, RIP
- Created Date: Aug 7 2022 9:50AM