• Wind and Structures
• /
• v.37 no.1
• /
• pp.25-38
• /
• 2023

Due to the complexity and difficulty in meeting the multiphase flow complexity, similarity, and multiscale characteristics, the mechanism of snow drift is so complicated that the snow deposition prediction is still inaccurate and needs to be far improved. Meanwhile, the validation of prediction methods is also limited due to a lack of field-measured data about snow deposition. To this end, a field measurement activity about snow deposition around a cube with time was carried out, and the snow accumulation process was measured under blowing snow conditions in northwest China. The maximum snow depth, snow profile, and variation in snow depth around the cube were discussed and analyzed. The measured results indicated three stages of snow accumulation around the cube. First, snow is deposited in windward, lateral and leeward regions, and then the snow depth in windward and lateral regions increases. Secondly, when the snow in the windward region reaches its maximum, the downwash flow erodes the snow against the front wall. Meanwhile, snow range and depth in lateral regions have a significant increase. Thirdly, a narrow road in the leeward region is formed with the increase in snow range and depth, which results in higher wind speed and reforming snow deposition there. The field measurement study in this paper not only furthers understanding of the snow accumulation process instead of final deposition under complex conditions but also provides an important benchmark for validating prediction methods.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.27 no.2
• /
• pp.50-57
• /
• 2023

Autonomous driving technologies have been gradually improved for road traffic owing to the development of artificial intelligence. Since the truck platooning is beneficial in terms of the associated transporting expenses, the Connected-Automated Vehicle technology is rapidly evolving. The structural performance is, however, rarely investigated to capture the effect of truck platooning on civil infrastructures.In this study, the dynamic behavior of bridges under truck platooning was investigated, and the amplification factor of responses was estimated considering several parameters associated with the driving conditions. Artificial intelligence techniques were used to estimate the maximum response of the mid span of a bridge as the platooning vehicles passing, and the importance of the parameters was evaluated. The most suitable algorithm was selected by evaluating the consistency of the estimated displacement.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.6D
• /
• pp.961-968
• /
• 2006

Curbs and L-type gutters installed at the edge of a road are very important structures to protect pedestrians from traffic accidents and to restraint slip of cars due to rain. However, existing construction method where great parts of the construction progress are done by human power has many problems in workability, quality and cost etc. In this paper, a new construction method for improvement in workability and quality for curbs and L-type gutters is developed. In order to investigate the structural safety and quality of curbs and gutters installed by the new method, tensile and lateral load tests are performed on curbs installed by existing and new methods and uniaxial compression tests are also performed on concrete samples of gutters constructed by existing and new methods. The test results show that the alignment of curbs and the strength of gutter concrete are very much improved by applying the new method. The tensile and lateral load capacities of the curbs installed by the new method are 10.7 and 2.5 times higher than those of curbs by existing method, respectively.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.3D
• /
• pp.363-371
• /
• 2009

The purpose of this study is to verify the safety issue of the tinted vehicle based on the field study as well as the issue of the capacity reduction from the tinted vehicle. Through this study, an innovative experimental method to verify the issues was developed using RTK GPS receivers, and a data collection was conducted using the developed experimental method. Using the collected data, the effects of the ahead vehicle with the windows tinted on the traffic condition such as headways and acceleration noise were analyzed to test that the ahead vehicle with windows tinted too darkly affects the increasing vehicle maneuver as following the degree of tinting. This study was conducted as a frontier study and more studies, for example, full scale analyses considering various road and vehicle conditions need to be conducted in the future.

• Journal of Trauma and Injury
• /
• v.36 no.4
• /
• pp.385-392
• /
• 2023

Purpose: This study investigated the epidemiology, management, outcomes, and postoperative disabilities of degloving soft tissue injuries (DSTIs) treated at a tertiary care center in northern India. Methods: A prospective study of patients with DSTIs was conducted over 15 months. The type of degloving injury, the mechanism of injury, and any associated injuries were analyzed using the World Health Organization Disability Assessment Schedule (WHODAS) 2.0 along with the management, outcomes, and disabilities at a 3-month follow-up. Results: Among 75 patients with DSTIs, the average age was 27.5 years, 80.0% were male, and 76.0% had been injured in traffic accidents. The majority (93.3%) were open degloving injuries. Lower limbs were affected most often (62.7%), followed by upper limbs (32.0%). Fractures were the most commonly associated injuries (72.0%). Most patients required more than two procedures, including secondary debridement (41.3%), split skin grafting (80.0%), flap coverage (12.0%), or vacuum-assisted closure (24.0%), while five patients underwent conservative management for closed degloving injuries. Postoperative complications included surgical site infections (14.7%) and skin necrosis (10.7%). Two patients died due to septic shock and multiple organ dysfunction syndrome. The mean length of hospital stay was 11.5±8.1 days, with injuries affecting the lower limbs and perineum requiring longer hospital stays. The mean WHODAS 2.0 disability score at 3 months was 19. Most patients had mild disabilities. Time away from work depended largely upon the site and severity of the injury. Approximately 75% of patients resumed their previous job or study, 14% changed their job, and 8% stopped working completely due to residual disability. Conclusions: DSTIs are common injuries in trauma and management is challenging. Although open DSTI are clinically evident at secondary survey, closed degloving injuries may be missed in the primary survey, necessitating a high index of suspicion, thorough clinical examination, and protocol-based management. Primary preventive strategies (e.g., road safety protocols, preplacement training, and proper protective equipment in industries) are also needed to reduce the incidence of these injuries.

• Smart Structures and Systems
• /
• v.32 no.3
• /
• pp.153-166
• /
• 2023

Health monitoring of civil infrastructures, in particular, old bridges that are still in service, has become more than necessary, given the risk that a possible degradation or failure of these infrastructures can induce on the safety of users in addition to the resulting commercial and economic impact. Bridge integrity assessment has attracted significant research efforts over the past forty years with the aim of developing new damage identification methods applicable to real structures. The bridge of Ouled Mimoun (Tlemcen, Algeria) is one of the oldest railway structure in the country. It was built in 1889. This bridge, which is too low with respect to the level of the road, has suffered multiple shocks from various machines that caused considerable damage to its central part. The present work aims to analyze the stability of this bridge by identifying damages and evaluating the damage rate in different parts of the structure on the basis of a finite element model. The applied method is based on an inverse analysis of the normal stress responses that were calculated from the corresponding recorded strains, during the passage of a real train, by means of a set of strain gauges placed on certain elements of the bridge. The results obtained from the inverse analysis made it possible to successfully locate areas that were really damaged and to estimate the damage rate. These results were also used to detect an excessive rigidity in certain elements due to the presence of plates, which were neglected in the numerical reference model. In the case of the continuous bridge monitoring, this developed method will be a very powerful tool as a smart health monitoring system, allowing engineers to take in time decisions in the event of bridge damage.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.17 no.1
• /
• pp.67-75
• /
• 2024

Crosswalks play an important role for the safe movement of pedestrians in a complex urban environment. However, for the visually impaired, crosswalks can be a big risk factor. Although assistive tools such as braille blocks and acoustic traffic lights exist for safe walking, poor management can sometimes act as a hindrance to safety. This paper proposes a method to improve accuracy in a deep learning-based real-time crosswalk detection model that can be used in applications for pedestrian assistance for the disabled at the beginning. The image was binarized by utilizing the characteristic that the white line of the crosswalk image contrasts with the road surface, and through this, the crosswalk could be better recognized and the location of the crosswalk could be more accurately identified by using two models that learned the whole and the middle part of the crosswalk, respectively. In addition, it was intended to increase accuracy by creating a boundary box that recognizes crosswalks in two stages: whole and part. Through this method, additional frames that the detection model did not detect in RGB image learning from the crosswalk image could be detected.

• International Journal of Computer Science & Network Security
• /
• v.24 no.5
• /
• pp.1-10
• /
• 2024

Individuals with visual impairments face numerous challenges in their daily lives, with navigating streets and public spaces being particularly daunting. The inability to identify safe crossing locations and assess the feasibility of crossing significantly restricts their mobility and independence. Globally, an estimated 285 million people suffer from visual impairment, with 39 million categorized as blind and 246 million as visually impaired, according to the World Health Organization. In Saudi Arabia alone, there are approximately 159 thousand blind individuals, as per unofficial statistics. The profound impact of visual impairments on daily activities underscores the urgent need for solutions to improve mobility and enhance safety. This study aims to address this pressing issue by leveraging computer vision and deep learning techniques to enhance object detection capabilities. Two models were trained to detect objects: one focused on street crossing obstacles, and the other aimed to search for objects. The first model was trained on a dataset comprising 5283 images of road obstacles and traffic signals, annotated to create a labeled dataset. Subsequently, it was trained using the YOLOv8 and YOLOv5 models, with YOLOv5 achieving a satisfactory accuracy of 84%. The second model was trained on the COCO dataset using YOLOv5, yielding an impressive accuracy of 94%. By improving object detection capabilities through advanced technology, this research seeks to empower individuals with visual impairments, enhancing their mobility, independence, and overall quality of life.

• Journal of Korean Society of Transportation
• /
• v.30 no.2
• /
• pp.43-52
• /
• 2012

A lane departure warning system (LDWS) is an effective technology-based countermeasure for preventing traffic crashes as it provides warning information to drivers. Understanding the characteristics of perception and satisfaction levels on LDWS is fundamental for deriving better performance and functionality enhancements of the system. The purpose of this study is to evaluate the user satisfaction of LDWS. A survey to collect user perception and user preference data was conducted. Both cross-tabulation analysis and binary logistic regression technique were adopted to identify the factors affecting user satisfaction for LDWS. The results revealed that the accuracy and timeliness of warning information was significant for evaluating the effectiveness of LDWS. In particular, the warning accuracy at a curve segment on the road was the most dominant factor affecting user satisfaction. The outcome of this study would be valuable in evaluating and designing LDWS functionalities.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.6
• /
• pp.222-234
• /
• 2020

Autonomous vehicles are equipped with a wide rage of sensors such as GPS, RADAR, LIDAR, camera, IMU, etc. and are driven by recognizing and judging various transportation systems at intersections in the city. The accident ratio of the intersection of the autonomous vehicles is 88% of all accidents due to the limitation of prediction and judgment of an area outside the sensing distance. Not only research on non-signalized intersection collision avoidance strategies through V2V and V2I is underway, but also research on safe intersection driving in failure situations is underway, but verification and fragments through simple intersection scenarios Only typical V2V failures are presented. In this paper, we analyzed the architecture of the V2V module, analyzed the causal factors for each V2V module, and defined the failure mode. We presented intersection scenarios for various road conditions and traffic volumes. we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to analyze the risk of autonomous vehicle based on the simulation. We presented ASIL, which is the result of risk analysis, proposed a monitoring concept for each component of the V2V module, and presented monitoring coverage.