Computer vision-based model for detecting turning lane features on Florida’s public roadways from aerial images

Richard Boadu Antwi; Samuel Takyi; Michael Kimollo; Alican Karaer; Eren Erman Ozguven; Ren Moses; Maxim A. Dulebenets; Thobias Sando

doi:10.1080/03081060.2024.2386614

Computer vision-based model for detecting turning lane features on Florida’s public roadways from aerial images

Richard Boadu Antwi
, Samuel Takyi
, Michael Kimollo
, Alican Karaer
, Eren Erman Ozguven
, Ren Moses
, Maxim A. Dulebenets
, Thobias Sando

School of Engineering

University of North Florida

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	1113-1144
Number of pages	32
Journal	Transportation Planning and Technology
Volume	48
Issue number	5
DOIs	https://doi.org/10.1080/03081060.2024.2386614
State	Published - Aug 8 2024

ASJC Scopus Subject Areas

Geography, Planning and Development
Transportation

Keywords

Turning lanes
deep learning
machine learning (ML)
pavement markings
roadway characteristic index (RCI)
roadway geometry features

Access to Document

10.1080/03081060.2024.2386614

Cite this

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title = "Computer vision-based model for detecting turning lane features on Florida{\textquoteright}s public roadways from aerial images",

keywords = "Turning lanes, deep learning, machine learning (ML), pavement markings, roadway characteristic index (RCI), roadway geometry features",

author = "Antwi, \{Richard Boadu\} and Samuel Takyi and Michael Kimollo and Alican Karaer and Ozguven, \{Eren Erman\} and Ren Moses and Dulebenets, \{Maxim A.\} and Thobias Sando",

note = "Antwi, R. B., Takyi, S., Kimollo, M., Karaer, A., Ozguven, E. E., Moses, R., … Sando, T. (2024). Computer vision-based model for detecting turning lane features on Florida{\textquoteright}s public roadways from aerial images. Transportation Planning and Technology, 1–32. https://doi.org/10.1080/03081060.2024.2386614",

year = "2024",

month = aug,

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doi = "10.1080/03081060.2024.2386614",

language = "English",

volume = "48",

pages = "1113--1144",

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T1 - Computer vision-based model for detecting turning lane features on Florida’s public roadways from aerial images

AU - Antwi, Richard Boadu

AU - Takyi, Samuel

AU - Kimollo, Michael

AU - Karaer, Alican

AU - Ozguven, Eren Erman

AU - Moses, Ren

AU - Dulebenets, Maxim A.

AU - Sando, Thobias

N1 - Antwi, R. B., Takyi, S., Kimollo, M., Karaer, A., Ozguven, E. E., Moses, R., … Sando, T. (2024). Computer vision-based model for detecting turning lane features on Florida’s public roadways from aerial images. Transportation Planning and Technology, 1–32. https://doi.org/10.1080/03081060.2024.2386614

PY - 2024/8/8

Y1 - 2024/8/8

KW - Turning lanes

KW - deep learning

KW - machine learning (ML)

KW - pavement markings

KW - roadway characteristic index (RCI)

KW - roadway geometry features

UR - https://www.scopus.com/pages/publications/85200994985

UR - https://www.scopus.com/pages/publications/85200994985#tab=citedBy

U2 - 10.1080/03081060.2024.2386614

DO - 10.1080/03081060.2024.2386614

M3 - Article

AN - SCOPUS:85200994985

SN - 0308-1060

VL - 48

SP - 1113

EP - 1144

JO - Transportation Planning and Technology

JF - Transportation Planning and Technology

IS - 5

ER -

Computer vision-based model for detecting turning lane features on Florida’s public roadways from aerial images

ASJC Scopus Subject Areas

Keywords

Access to Document

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Cite this