Obtaining real-time transportation survey data using artificial intelligence techniques

Manual traffic surveys are very time-consuming and labor-intensive to complete. Intelligent surveys can reduce human operators performing manual surveys and the time and expense required to collect data. Due to the rapid growth of technology and the trend toward smart cities administered by various...

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Bibliographic Details
Main Authors: Abdali, Mohanad J., Abdulwahid, Hayder A., Alwan, Kareem H.
Format: Conference Proceeding
Language:English
Subjects:
Artificial intelligence
Counting
Data collection
Digital cameras
Human performance
Machine learning
Real time
Traffic surveillance
Traffic surveys
Transportation systems
Online Access:Get full text
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Summary:Manual traffic surveys are very time-consuming and labor-intensive to complete. Intelligent surveys can reduce human operators performing manual surveys and the time and expense required to collect data. Due to the rapid growth of technology and the trend toward smart cities administered by various intelligent systems, including the transportation system, intelligent surveys are more vital than ever. Using deep learning, this research develops a new method for intelligent surveys of real-time transport data. And developed a system to determine the types and count of vehicles traversing a particular road segment by utilizing a comprehensive database of video surveillance data collected with high-resolution digital cameras. In addition, an application has been developed to present the current traffic status to drivers in real-time. In general, the results demonstrated that the proposed approach functions as intended and under various settings without being considerably affected by the weather and achieving 98 percent accuracy in vehicle counting and classification.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0212188