Title: Sensor based vehicle detection and classification - a systematic review

Authors: Nikita Singhal; Lalji Prasad

Addresses: CSE, SIRT, SAGE University, Indore, MP, 452012, India ' CSE, SIRT, SAGE University, Indore, MP, 452012, India

Abstract: Traffic management has become a major problem in every country due to day by day increase of vehicles on road. With this enhancement, sometimes it becomes difficult to keep track of vehicles for the purpose of traffic monitoring and law enforcement. We need an intelligent transportation system (ITS) which will help in traffic management. In this study, we presented a review of the smart transportation system that focuses on vehicle detection and classification (VDC) that is generally used in applications like congestion prediction, future road infrastructure requirement prediction, automated parking, and security enforcement. We have reviewed more than 130 papers that are published between 2010 and 2021 and found that various sensor technologies, machine learning, computer vision and deep learning techniques have been applied for the detection and classification of vehicles by many researchers. This study will provide useful directions to the researchers in selecting appropriate technologies for VDC.

Keywords: vehicle detection; vehicle classification; intelligent transportation system; sensor; machine learning; deep learning.

DOI: 10.1504/IJESMS.2022.122731

International Journal of Engineering Systems Modelling and Simulation, 2022 Vol.13 No.1, pp.38 - 60

Received: 15 Jun 2021
Accepted: 13 Jul 2021
Published online: 09 May 2022 *

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