Automatic Vehicle Identification and Classification Model Using the YOLOv3 Algorithm for a Toll Management System
Vehicle identification and classification are some of the major tasks in the areas of toll management and traffic management, where these smart transportation systems are implemented by integrating various information communication technologies and multiple types of hardware. The currently shifting...
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Veröffentlicht in: | Sustainability 2022-08, Vol.14 (15), p.9163 |
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creator | Rajput, Sudhir Kumar Patni, Jagdish Chandra Alshamrani, Sultan S. Chaudhari, Vaibhav Dumka, Ankur Singh, Rajesh Rashid, Mamoon Gehlot, Anita AlGhamdi, Ahmed Saeed |
description | Vehicle identification and classification are some of the major tasks in the areas of toll management and traffic management, where these smart transportation systems are implemented by integrating various information communication technologies and multiple types of hardware. The currently shifting era toward artificial intelligence has also motivated the implementation of vehicle identification and classification using AI-based techniques, such as machine learning, artificial neural network and deep learning. In this research, we used the deep learning YOLOv3 algorithm and trained it on a custom dataset of vehicles that included different vehicle classes as per the Indian Government’s recommendation to implement the automatic vehicle identification and classification for use in the toll management system deployed at toll plazas. For faster processing of the test videos, the frames were saved at a certain interval and then the saved frames were passed through the algorithm. Apart from toll plazas, we also tested the algorithm for vehicle identification and classification on highways and urban areas. Implementing automatic vehicle identification and classification using traditional techniques is a highly proprietary endeavor. Since YOLOv3 is an open-standard-based algorithm, it paves the way to developing sustainable solutions in the area of smart transportation. |
doi_str_mv | 10.3390/su14159163 |
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The currently shifting era toward artificial intelligence has also motivated the implementation of vehicle identification and classification using AI-based techniques, such as machine learning, artificial neural network and deep learning. In this research, we used the deep learning YOLOv3 algorithm and trained it on a custom dataset of vehicles that included different vehicle classes as per the Indian Government’s recommendation to implement the automatic vehicle identification and classification for use in the toll management system deployed at toll plazas. For faster processing of the test videos, the frames were saved at a certain interval and then the saved frames were passed through the algorithm. Apart from toll plazas, we also tested the algorithm for vehicle identification and classification on highways and urban areas. Implementing automatic vehicle identification and classification using traditional techniques is a highly proprietary endeavor. Since YOLOv3 is an open-standard-based algorithm, it paves the way to developing sustainable solutions in the area of smart transportation.</description><identifier>ISSN: 2071-1050</identifier><identifier>EISSN: 2071-1050</identifier><identifier>DOI: 10.3390/su14159163</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Accuracy ; Algorithms ; Artificial intelligence ; Classification ; Deep learning ; Fees & charges ; Highways ; Identification ; Neural networks ; Roads & highways ; Sensors ; Spread spectrum ; Sustainability ; Toll roads ; Tolls ; Traffic congestion ; Traffic management ; Transportation planning ; Transportation systems ; Urban areas ; Vehicle identification ; Vehicles</subject><ispartof>Sustainability, 2022-08, Vol.14 (15), p.9163</ispartof><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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subjects | Accuracy Algorithms Artificial intelligence Classification Deep learning Fees & charges Highways Identification Neural networks Roads & highways Sensors Spread spectrum Sustainability Toll roads Tolls Traffic congestion Traffic management Transportation planning Transportation systems Urban areas Vehicle identification Vehicles |
title | Automatic Vehicle Identification and Classification Model Using the YOLOv3 Algorithm for a Toll Management System |
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