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Dergiler / Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi / 2026 / Cilt: 24 Sayı: 1

Cep Telefonu Kullanılarak Araç Hızı ile Çukur Tespiti Arasındaki İlişkinin Araştırılması

Investigating The Relationship Between Vehicle Speed and Pothole Detection by Using Mobile Phone

Ömer Kaya(ERZURUM TEKNİK ÜNİVERSİTESİ)0000-0003-1037-5546
Muhammed Yasin Çodur(ERZURUM TEKNİK ÜNİVERSİTESİ)0000-0001-7647-2424
Sayfa
228–241
Yayın Tarihi
2024-02-27
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Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Son olarak videodan elde edilen görsellerden elde edilen algılama sonuçları, modellerde aşırı uyumun olmadığını göstermiştir.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Yol kaplamalarının zaman, iklim koşulları ve inşaat hatalarından dolayı bozulduğu bilinmektedir.
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Temel Bulgular & Veri:Ancak bu sistemde araç hızının çukur tespiti üzerindeki etkisi bilinmemektedir.
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Sonuç & Katkı:Son olarak videodan elde edilen görsellerden elde edilen algılama sonuçları, modellerde aşırı uyumun olmadığını göstermiştir.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Yol Hasarı · Çukur · Otomatik Algılama

Özet

Yol kaplamalarının zaman, iklim koşulları ve inşaat hatalarından dolayı bozulduğu bilinmektedir. Bu hasarlar dikkate alındığında yol güvenliğini ve konforunu azaltan en önemli yol kusurlarından biri çukurlardır. Özellikle çukurun genişliği ve derinliği arttıkça sürüş güvenliğini de tehlikeye atmaktadır. Özellikle şehir içi yollarda bu çukurların konumları birçok bölgede manuel olarak belirlenmektedir. Bu süreç çukurların bakım ve onarımında gecikmelere neden olmaktadır. Bu amaçla yazarlar, yol ağında meydana gelen çukurları otomatik olarak tespit etmek için birden fazla aşamadan oluşan araç içi entegre bir sistem planlıyorlar. Bu sistemin ilk aşaması, yüksek doğrulukta nesne algılama yöntemleri ile çukurların belirlenmesidir. Ancak bu sistemde araç hızının çukur tespiti üzerindeki etkisi bilinmemektedir. Bu karmaşık durumu çözmek için aynı yol ve çukur üzerinde farklı araç hızlarında gerçek zamanlı video kayıtları yapılmıştır. Daha sonra YOLOv7 ve YOLOv8 tek aşamalı detektör ile bu videolar üzerinden çukur tespit işlemi gerçekleştirilmiştir. Elde edilen sonuçlar incelendiğinde araç hızı ile çukur tespiti arasında kesin bir ilişki tespit edilememiştir. Bu durum kamera açısı, görüntü kalitesi, güneş ışığı durumu gibi çeşitli parametrelere göre değişiklik gösterebilmektedir. Ayrıca her iki model performans kriterlerine göre karşılaştırıldığında YOLOv7'nin mAP0.5, hassasiyet, geri çağırma ve F1 skoru değerlerinde YOLOv8'e kısmi üstünlüğü bulunmaktadır. Bu kriterlerin 1'e yakın olması anlamlıdır. Son olarak videodan elde edilen görsellerden elde edilen algılama sonuçları, modellerde aşırı uyumun olmadığını göstermiştir.

Abstract

It is known that road pavements are damaged due to time, climatic conditions and construction errors. Considering these damages, the most important road defect that reduces road safety and comfort is potholes. Especially as the width and depth of the pothole increases, driving safety is also endangered. In addition, the locations of these potholes, especially on urban roads, are determined manually in many regions. This process causes delays in the maintenance and repair of the potholes. To this end, the authors plan an in-vehicle integrated system consisting of multiple stages to automatically detect potholes occurring in the road network. The main purpose of the planned system is to identify potholes with high accuracy. However, the effect of vehicle speed on pothole detection in this system is unknown. In order to solve this complex situation, real-time video recordings were made on the same road and pothole at different vehicle speeds. Then, the pothole detection process was realized through these videos with the single-stage detector YOLOv7 vs YOLOv8. When the results obtained were examined, exact relationship could not be determined between vehicle speed and pothole detection. This situation may vary according to various parameters such as camera angle, image quality, sunlight condition. In addition, when both models are compared according to the performance criteria, YOLOv7 has a partial superiority over YOLOv8 in mAP0.5, precision, recall and F1 score values. It is especially significant that these criteria are close to 1. Finally, the perception results obtained from the images obtained from the video showed that there was no overfitting in the models.

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Bu Makaleye Atıf Yap

Kaya, Ö., Çodur, M. Y. (2024). Cep Telefonu Kullanılarak Araç Hızı ile Çukur Tespiti Arasındaki İlişkinin Araştırılması. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, Cilt: 24 Sayı: 1, 228–241. https://doi.org/10.35414/akufemubid.1328778

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