Developing an Object and Event Detection and Recognition Module for Autonomous Vehicles Using Simulators

Souvik Mandal; Venkat Nikhil Tatavarthy; Gourinath Banda

doi:10.1007/978-981-33-6912-2_48

Developing an Object and Event Detection and Recognition Module for Autonomous Vehicles Using Simulators

Souvik Mandal^*, Venkat Nikhil Tatavarthy, Gourinath Banda

^*Kontaktforfatter

IIT Indore

Publikation: Kapitel i bog/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › peer review

Abstract

An autonomous vehicle is capable of operating safely by sensing its environment with little or no human involvement. In this paper, we develop an Object and Event Detection and Recognition (OEDR) system, using supervised machine learning and computer vision techniques, which is an important environment perceiving unit for the autonomous vehicle. To achieve this, we have used the IPG-CarMaker simulator to exploit the advantages of a simulator. In the due course of developing our system, we have encountered a few potential limitations a simulation may raise such as training dataset diversity and camera noise, and found their possible solutions.

Originalsprog	Engelsk
Titel	Soft Computing and Signal Processing
Forlag	Springer
Publikationsdato	2021
Sider	537–548
ISBN (Trykt)	978-981-33-6911-5
ISBN (Elektronisk)	978-981-33-6912-2
DOI	https://doi.org/10.1007/978-981-33-6912-2_48
Status	Udgivet - 2021
Udgivet eksternt	Ja
Begivenhed	ICSCSP 2020 : 3rd International Conference on Soft Computing and Signal Processing - Hyderabad, Indien Varighed: 19. jun. 2020 → 20. jun. 2020

Konference

Konference	ICSCSP 2020 : 3rd International Conference on Soft Computing and Signal Processing
Land/Område	Indien
By	Hyderabad
Periode	19/06/2020 → 20/06/2020

Dokumenter og links

10.1007/978-981-33-6912-2_48

Citationsformater

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title = "Developing an Object and Event Detection and Recognition Module for Autonomous Vehicles Using Simulators",

abstract = "An autonomous vehicle is capable of operating safely by sensing its environment with little or no human involvement. In this paper, we develop an Object and Event Detection and Recognition (OEDR) system, using supervised machine learning and computer vision techniques, which is an important environment perceiving unit for the autonomous vehicle. To achieve this, we have used the IPG-CarMaker simulator to exploit the advantages of a simulator. In the due course of developing our system, we have encountered a few potential limitations a simulation may raise such as training dataset diversity and camera noise, and found their possible solutions.",

author = "Souvik Mandal and Tatavarthy, {Venkat Nikhil} and Gourinath Banda",

year = "2021",

doi = "10.1007/978-981-33-6912-2_48",

language = "English",

isbn = "978-981-33-6911-5",

pages = "537–548",

booktitle = "Soft Computing and Signal Processing",

publisher = "Springer",

address = "Germany",

note = "ICSCSP 2020 : 3rd International Conference on Soft Computing and Signal Processing ; Conference date: 19-06-2020 Through 20-06-2020",

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Mandal, S, Tatavarthy, VN & Banda, G 2021, Developing an Object and Event Detection and Recognition Module for Autonomous Vehicles Using Simulators. i Soft Computing and Signal Processing. Springer, s. 537–548, ICSCSP 2020 : 3rd International Conference on Soft Computing and Signal Processing, Hyderabad, Indien, 19/06/2020. https://doi.org/10.1007/978-981-33-6912-2_48

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AU - Tatavarthy, Venkat Nikhil

AU - Banda, Gourinath

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Y1 - 2021

N2 - An autonomous vehicle is capable of operating safely by sensing its environment with little or no human involvement. In this paper, we develop an Object and Event Detection and Recognition (OEDR) system, using supervised machine learning and computer vision techniques, which is an important environment perceiving unit for the autonomous vehicle. To achieve this, we have used the IPG-CarMaker simulator to exploit the advantages of a simulator. In the due course of developing our system, we have encountered a few potential limitations a simulation may raise such as training dataset diversity and camera noise, and found their possible solutions.

AB - An autonomous vehicle is capable of operating safely by sensing its environment with little or no human involvement. In this paper, we develop an Object and Event Detection and Recognition (OEDR) system, using supervised machine learning and computer vision techniques, which is an important environment perceiving unit for the autonomous vehicle. To achieve this, we have used the IPG-CarMaker simulator to exploit the advantages of a simulator. In the due course of developing our system, we have encountered a few potential limitations a simulation may raise such as training dataset diversity and camera noise, and found their possible solutions.

U2 - 10.1007/978-981-33-6912-2_48

DO - 10.1007/978-981-33-6912-2_48

M3 - Article in proceedings

SN - 978-981-33-6911-5

SP - 537

EP - 548

BT - Soft Computing and Signal Processing

PB - Springer

T2 - ICSCSP 2020 : 3rd International Conference on Soft Computing and Signal Processing

Y2 - 19 June 2020 through 20 June 2020

ER -

Developing an Object and Event Detection and Recognition Module for Autonomous Vehicles Using Simulators

Abstract

Konference

Dokumenter og links

Fingeraftryk

Citationsformater