Deep Learning–Based Detection of Vehicle Axle Type with Images Collected via UAV
Publication: Journal of Transportation Engineering, Part B: Pavements
Volume 150, Issue 3
Abstract
The identification and quantification of vehicle axle type are essential to evaluate the operational status of road traffic. Uncrewed aerial vehicles (UAV) are helpful in obtaining information about vehicles in most road scenes. This paper proposed the collection of road vehicle information using UAVs with a high-resolution camera. The UAV flight scheme for optimal image quality acquisition was studied, and the collected UAV images were processed. An image data set was established with four vehicle types and nine vehicle axle types. Three state-of-the-art object-detection algorithm, namely, CenterNet, you only look once (YOLO)v7, and Detection Transformer (DTER), were used to train the data set, and their prediction performance was compared. YOLOv7 performed the best among the three algorithms with a mean average precision (MAP) of 97.1%. The YOLOv7 object-detection algorithm was combined with the DeepSORT object-tracking algorithm to achieve detection and statistics of vehicle axle type in traffic flow. The findings of this study help to quickly obtain basic information about the vehicles on the road.
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Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported in part by the National Key Research and Development Project of China under Grant No. 2021YFB2600603 and in part by the National Natural Science Foundation of China under Grant No. 52208428.
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Information & Authors
Information
Published In
Journal of Transportation Engineering, Part B: Pavements
Volume 150 • Issue 3 • September 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Sep 27, 2023
Accepted: Mar 11, 2024
Published online: May 22, 2024
Published in print: Sep 1, 2024
Discussion open until: Oct 22, 2024
ASCE Technical Topics:
- Algorithms
- Computer vision and image processing
- Engineering fundamentals
- Equipment and machinery
- Highway and road management
- Highway transportation
- Highways and roads
- Infrastructure
- Mathematics
- Methodology (by type)
- Traffic engineering
- Traffic flow
- Traffic management
- Transportation engineering
- Uncrewed vehicles
- Vehicles
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