Sensor based vehicle detection and classification - a systematic review

被引:0
作者
Singhal, Nikita [1 ]
Prasad, Lalji [1 ]
机构
[1] SAGE Univ, CSE, SIRT, Indore 452012, Madhya Pradesh, India
关键词
vehicle detection; vehicle classification; intelligent transportation system; sensor; machine learning; deep learning; INTELLIGENT TRANSPORT-SYSTEM; PAVEMENT VIBRATION; MAGNETIC SENSOR; IMAGES; LIDAR; VISION; RECOGNITION; ALGORITHM; ENSEMBLE; FUSION;
D O I
10.1504/IJESMS.2022.122731
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页码:38 / 60
页数:23
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