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International Journal of Intelligent Transportation Systems Research

Erschienen in:

11.05.2022

Automated Truck Taxonomy Classification Using Deep Convolutional Neural Networks

verfasst von: Abdullah Almutairi, Pan He, Anand Rangarajan, Sanjay Ranka

Erschienen in: International Journal of Intelligent Transportation Systems Research | Ausgabe 2/2022

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Abstract

Trucks are the key transporters of freight. The types of commodities and goods mainly determine the right trailer for carrying them. Furthermore, finding the commodities’ flow is an important task for transportation agencies in better planning freight infrastructure investments and initiating near-term traffic throughput improvements. In this paper, we propose a fine-grained deep learning based truck classification system that can detect and classify the trucks, tractors, and trailers following the Federal Highway Administration’s (FHWA) vehicle schema. We created a large, fine-grained labeled dataset of vehicle images collected from state highways. Experimental results show the high accuracy of our system and visualize the salient features of the trucks that influence classification.

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Titel: Automated Truck Taxonomy Classification Using Deep Convolutional Neural Networks
verfasst von: Abdullah Almutairi
Pan He
Anand Rangarajan
Sanjay Ranka
Publikationsdatum: 11.05.2022
Verlag: Springer US
Erschienen in: International Journal of Intelligent Transportation Systems Research / Ausgabe 2/2022
Print ISSN: 1348-8503
Elektronische ISSN: 1868-8659
DOI: https://doi.org/10.1007/s13177-022-00306-4

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