Lane type classification & distance measurement system for autonomous vehicle

Name: Lane type classification & distance measurement system for autonomous vehicle
Author: Özen, S., Kaya, Uygar, Semiz, A., Yalçın, M. F., Çelebi, A. T.

İsim	Lane type classification & distance measurement system for autonomous vehicle
Yazar	Özen, S., Kaya, Uygar, Semiz, A., Yalçın, M. F., Çelebi, A. T.
Basım Tarihi:	2023
Basım Yeri	- IEEE
Konu	Custom dataset, Deep learning, Image processing, Lane distance measurement, Lane type classification
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	2-s2.0-85173434745
Kayıt Numarası	fcf9a667-c05f-40ca-bcc6-e836204fa565
Tarih	2023
Örnek Metin	In this paper, lane type classification and lane distance measurement system are proposed for autonomous vehicles. In the proposed system, the perspective transformation method is applied to the image taken from the vehicle camera, so that a bird's-eye view is obtained and the parts with stripes are cropped from the image, and then a multi-class classification model is implemented using neural network-based architectures to determine the stripe type. In addition, with the proposed distance measurement system, the distance of the vehicle to the right and left lanes is calculated during autonomous driving, thus ensuring that the vehicle can drive autonomously on the lane. For this study, our own data set has been created.
DOI	10.1109/SIU59756.2023.10224048

Kaynağa git Özyeğin Üniversitesi

Aramaya Dön

Özyeğin Üniversitesi

Kaynağa git

Lane type classification & distance measurement system for autonomous vehicle

Yazar Özen, S., Kaya, Uygar, Semiz, A., Yalçın, M. F., Çelebi, A. T.

Basım Tarihi 2023

Basım Yeri - IEEE

Konu Custom dataset, Deep learning, Image processing, Lane distance measurement, Lane type classification

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 2-s2.0-85173434745

Kayıt Numarası fcf9a667-c05f-40ca-bcc6-e836204fa565

Tarih 2023

Örnek Metin In this paper, lane type classification and lane distance measurement system are proposed for autonomous vehicles. In the proposed system, the perspective transformation method is applied to the image taken from the vehicle camera, so that a bird's-eye view is obtained and the parts with stripes are cropped from the image, and then a multi-class classification model is implemented using neural network-based architectures to determine the stripe type. In addition, with the proposed distance measurement system, the distance of the vehicle to the right and left lanes is calculated during autonomous driving, thus ensuring that the vehicle can drive autonomously on the lane. For this study, our own data set has been created.

DOI 10.1109/SIU59756.2023.10224048