Pedestrian and Vehicle Detection in Autonomous Vehicle Perception Systems—A Review

Autonomous Vehicles (AVs) have the potential to solve many traffic problems, such as accidents, congestion and pollution. However, there are still challenges to overcome, for instance, AVs need to accurately perceive their environment to safely navigate in busy urban scenarios. The aim of this paper...

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Autores principales:	Luiz G. Galvao, Maysam Abbod, Tatiana Kalganova, Vasile Palade, Md Nazmul Huda
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	autonomous vehicle vehicle detection pedestrian detection generic object detection deep learning traditional technique Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/1e21657bc99641acad01eba3ddf51a29
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spelling	oai:doaj.org-article:1e21657bc99641acad01eba3ddf51a292021-11-11T19:13:47ZPedestrian and Vehicle Detection in Autonomous Vehicle Perception Systems—A Review10.3390/s212172671424-8220https://doaj.org/article/1e21657bc99641acad01eba3ddf51a292021-10-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7267https://doaj.org/toc/1424-8220Autonomous Vehicles (AVs) have the potential to solve many traffic problems, such as accidents, congestion and pollution. However, there are still challenges to overcome, for instance, AVs need to accurately perceive their environment to safely navigate in busy urban scenarios. The aim of this paper is to review recent articles on computer vision techniques that can be used to build an AV perception system. AV perception systems need to accurately detect non-static objects and predict their behaviour, as well as to detect static objects and recognise the information they are providing. This paper, in particular, focuses on the computer vision techniques used to detect pedestrians and vehicles. There have been many papers and reviews on pedestrians and vehicles detection so far. However, most of the past papers only reviewed pedestrian or vehicle detection separately. This review aims to present an overview of the AV systems in general, and then review and investigate several detection computer vision techniques for pedestrians and vehicles. The review concludes that both traditional and Deep Learning (DL) techniques have been used for pedestrian and vehicle detection; however, DL techniques have shown the best results. Although good detection results have been achieved for pedestrians and vehicles, the current algorithms still struggle to detect small, occluded, and truncated objects. In addition, there is limited research on how to improve detection performance in difficult light and weather conditions. Most of the algorithms have been tested on well-recognised datasets such as Caltech and KITTI; however, these datasets have their own limitations. Therefore, this paper recommends that future works should be implemented on more new challenging datasets, such as PIE and BDD100K.Luiz G. GalvaoMaysam AbbodTatiana KalganovaVasile PaladeMd Nazmul HudaMDPI AGarticleautonomous vehiclevehicle detectionpedestrian detectiongeneric object detectiondeep learningtraditional techniqueChemical technologyTP1-1185ENSensors, Vol 21, Iss 7267, p 7267 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	autonomous vehicle vehicle detection pedestrian detection generic object detection deep learning traditional technique Chemical technology TP1-1185
spellingShingle	autonomous vehicle vehicle detection pedestrian detection generic object detection deep learning traditional technique Chemical technology TP1-1185 Luiz G. Galvao Maysam Abbod Tatiana Kalganova Vasile Palade Md Nazmul Huda Pedestrian and Vehicle Detection in Autonomous Vehicle Perception Systems—A Review
description	Autonomous Vehicles (AVs) have the potential to solve many traffic problems, such as accidents, congestion and pollution. However, there are still challenges to overcome, for instance, AVs need to accurately perceive their environment to safely navigate in busy urban scenarios. The aim of this paper is to review recent articles on computer vision techniques that can be used to build an AV perception system. AV perception systems need to accurately detect non-static objects and predict their behaviour, as well as to detect static objects and recognise the information they are providing. This paper, in particular, focuses on the computer vision techniques used to detect pedestrians and vehicles. There have been many papers and reviews on pedestrians and vehicles detection so far. However, most of the past papers only reviewed pedestrian or vehicle detection separately. This review aims to present an overview of the AV systems in general, and then review and investigate several detection computer vision techniques for pedestrians and vehicles. The review concludes that both traditional and Deep Learning (DL) techniques have been used for pedestrian and vehicle detection; however, DL techniques have shown the best results. Although good detection results have been achieved for pedestrians and vehicles, the current algorithms still struggle to detect small, occluded, and truncated objects. In addition, there is limited research on how to improve detection performance in difficult light and weather conditions. Most of the algorithms have been tested on well-recognised datasets such as Caltech and KITTI; however, these datasets have their own limitations. Therefore, this paper recommends that future works should be implemented on more new challenging datasets, such as PIE and BDD100K.
format	article
author	Luiz G. Galvao Maysam Abbod Tatiana Kalganova Vasile Palade Md Nazmul Huda
author_facet	Luiz G. Galvao Maysam Abbod Tatiana Kalganova Vasile Palade Md Nazmul Huda
author_sort	Luiz G. Galvao
title	Pedestrian and Vehicle Detection in Autonomous Vehicle Perception Systems—A Review
title_short	Pedestrian and Vehicle Detection in Autonomous Vehicle Perception Systems—A Review
title_full	Pedestrian and Vehicle Detection in Autonomous Vehicle Perception Systems—A Review
title_fullStr	Pedestrian and Vehicle Detection in Autonomous Vehicle Perception Systems—A Review
title_full_unstemmed	Pedestrian and Vehicle Detection in Autonomous Vehicle Perception Systems—A Review
title_sort	pedestrian and vehicle detection in autonomous vehicle perception systems—a review
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/1e21657bc99641acad01eba3ddf51a29
work_keys_str_mv	AT luizggalvao pedestrianandvehicledetectioninautonomousvehicleperceptionsystemsareview AT maysamabbod pedestrianandvehicledetectioninautonomousvehicleperceptionsystemsareview AT tatianakalganova pedestrianandvehicledetectioninautonomousvehicleperceptionsystemsareview AT vasilepalade pedestrianandvehicledetectioninautonomousvehicleperceptionsystemsareview AT mdnazmulhuda pedestrianandvehicledetectioninautonomousvehicleperceptionsystemsareview
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Pedestrian and Vehicle Detection in Autonomous Vehicle Perception Systems—A Review

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