Road Hazard Assessment Using Pothole and Traffic Data in South Korea

Yang, Choong Heon; Kim, Jin Guk; Shin, Sung Pil

doi:10.1155/2021/5901203

Cited by 8 publications

(6 citation statements)

References 12 publications

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“…In Korea, no criteria exist for evaluating pothole risk, but a few studies have been conducted. Chung-Hyun et al [34] attached an acceleration sensor to a vehicle. They presented a risk index divided into four stages: Caution, Alert, Warning, and Danger, according to the Z-axis acceleration value generated when passing through the pothole.…”

Section: Risk Assessment Methodsmentioning

confidence: 99%

Image-Based Pothole Detection Using Multi-Scale Feature Network and Risk Assessment

Heo

Choi

Kim³

et al. 2023

Electronics

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Potholes on road surfaces pose a serious hazard to vehicles and passengers due to the difficulty detecting them and the short response time. Therefore, many government agencies are applying various pothole-detection algorithms for road maintenance. However, current methods based on object detection are unclear in terms of real-time detection when using low-spec hardware systems. In this study, the SPFPN-YOLOv4 tiny was developed by combining spatial pyramid pooling and feature pyramid network with CSPDarknet53-tiny. A total of 2665 datasets were obtained via data augmentation, such as gamma regulation, horizontal flip, and scaling to compensate for the lack of data, and were divided into training, validation, and test of 70%, 20%, and 10% ratios, respectively. As a result of the comparison of YOLOv2, YOLOv3, YOLOv4 tiny, and SPFPN-YOLOv4 tiny, the SPFPN-YOLOv4 tiny showed approximately 2–5% performance improvement in the mean average precision (intersection over union = 0.5). In addition, the risk assessment based on the proposed SPFPN-YOLOv4 tiny was calculated by comparing the tire contact patch size with pothole size by applying the pinhole camera and distance estimation equation. In conclusion, we developed an end-to-end algorithm that can detect potholes and classify the risks in real-time using 2D pothole images.

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Section: Risk Assessment Methodsmentioning

confidence: 99%

Image-Based Pothole Detection Using Multi-Scale Feature Network and Risk Assessment

Heo

Choi

Kim³

et al. 2023

Electronics

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“…The AP is calculated using the difference-average precision metric, the area under the precision-recall curve. The equations for precision and recall are shown in Equations ( 4) and (5).…”

Section: Evaluation Metrics and Experimental Detailsmentioning

confidence: 99%

“…Pavement damage due to road aging, traffic volume, construction materials, and weather [1,2] is an important cause of driving safety [3][4][5]. Therefore, pavement damage detection is beneficial for drivers' lives' safety.…”

Section: Introductionmentioning

confidence: 99%

Automatic Recognition of Road Damage Based on Lightweight Attentional Convolutional Neural Network

Han

Lee

Seo

2022

Sensors

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An efficient road damage detection system can reduce the risk of road defects to motorists and road maintenance costs to traffic management authorities, for which a lightweight end-to-end road damage detection network is proposed in this paper, aiming at fast and automatic accurate identification and classification of multiple types of road damage. The proposed technique consists of a backbone network based on a combination of lightweight feature detection modules constituted with a multi-scale feature fusion network, which is more beneficial for target identification and classification at different distances and angles than other studies. An embedded lightweight attention module was also developed that can enhance feature information by assigning weights to multi-scale convolutional kernels to improve detection accuracy with fewer parameters. The proposed model generally has higher performance and fewer parameters than other representative models. According to our practice tests, it can identify many types of road damage based on the images captured by vehicle cameras and meet the real-time detection required when piggybacking on mobile systems.

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“…While South Korea boasts a modern urban fabric, it still contends with persistent road pavement issues that deeply affect its populace. Chief among the culprits are potholes, wear-induced fissures, inadequate drainage, and an uptick in vehicular movement due to urban growth [4,5]. Together, these issues present both monetary and societal challenges rooted in infrastructure wear, congestion, and road safety [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…Chief among the culprits are potholes, wear-induced fissures, inadequate drainage, and an uptick in vehicular movement due to urban growth [4,5]. Together, these issues present both monetary and societal challenges rooted in infrastructure wear, congestion, and road safety [4,5].…”

Section: Introductionmentioning

confidence: 99%

From Hive to Highway: Waste Honeycombs as a Sustainable Modifier for Asphalt Binder Formulations in South Korea

Nciri,

Kim

2023

Materials

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Navigating the crossroads of sustainable infrastructure and innovative waste management, this research unveils the potential of waste honeycombs (WHCs)—an overlooked byproduct of apiculture—as a potent modifier for asphalt binder formulations. This endeavor addresses the dual challenge of enhancing road pavement sustainability and mitigating environmental degradation. A meticulous methodology evaluated the impact of varying WHC concentrations (5, 10, and 15 wt.%) on the asphalt binder, examining its attributes pre- and post-aging. Employing an array of analytical tools—thin-layer chromatography-flame ionization detection (TLC-FID); Fourier transform-infrared spectroscopy (FT-IR); scanning electron microscopy (SEM); thermogravimetric analysis (TGA); and a suite of conventional tests such as penetration, softening point, viscosity, ductility, dynamic shear rheometer (DSR), and multiple stress-creep recovery (MSCR)—provided a comprehensive insight into the binder’s behavior. TLC-FID analyses revealed that WHC, with its 92 wt.% resin content, altered the SARA profile across distinct aging conditions, notably reducing asphaltene content, a factor linked to binder stiffness. The colloidal instability index (IC) further attested to this, pointing to a more thermodynamically stable system with WHC’s inclusion. Meanwhile, FT-IR confirmed a physical interaction between WHC and asphalt without introducing new chemical entities. SEM observations highlighted the superior miscibility of WHC with asphalt, evidenced by a unique microtexture. With marked precision, TGA assessments unveiled a bolstering of asphalt’s inherent thermal resilience consequent to a minor WHC integration. From the conventional tests, shifts in penetration, softening point, and viscosity were observed, with reduced viscosity, indicating improved workability. Lastly, while rutting potential was sensitive to WHC concentrations, fatigue resistance notably heightened with minor to moderate WHC inclusions. In essence, this pioneering study advocates for WHC’s integration into asphalt formulations, offering enhanced road performance coupled with sustainable waste utilization. The findings underscore the synergy between environmental stewardship and infrastructural advancement.

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Road Hazard Assessment Using Pothole and Traffic Data in South Korea

Cited by 8 publications

References 12 publications

Image-Based Pothole Detection Using Multi-Scale Feature Network and Risk Assessment

Image-Based Pothole Detection Using Multi-Scale Feature Network and Risk Assessment

Automatic Recognition of Road Damage Based on Lightweight Attentional Convolutional Neural Network

From Hive to Highway: Waste Honeycombs as a Sustainable Modifier for Asphalt Binder Formulations in South Korea

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