• International Journal of Highway Engineering
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• v.17 no.4
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• pp.89-98
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• 2015

PURPOSES : This study evaluated the feasibility of implementing protected-permissive left-turn (PPLT) signals at three-leg signalized intersections. METHODS: A three-leg signalized intersection with permissive left-turn was first selected. A VISSIM simulation model was constructed using data collected from the test site. The VISSIM network was calibrated by adjusting related parameter values in order to minimize the difference between the simulated and surveyed critical gap. The calibrated network was validated by the number of waiting left-turning vehicles per cycle. Finally, the mobility and safety measures were extracted from simulation runs in which permissive, protected left turns as well as PPLTs were realized based on diverse traffic volume scenarios. RESULTS : The mobility-related measures of effectiveness (MOEs) of the case with PPLT outperformed the other two left-turn treatment scenarios. In particular, the average waiting time per cycle for the left-turn vehicles in the case with PPLT was reduced by 30 s. The safety-related MOEs of the case with PPLT were somewhat higher than those in the case with protected left-turns and much higher than those in the case with permissive left-turns. CONCLUSIONS : Based on the mobility- and safety-related MOEs generated from the VISSIM simulation runs, the use of PPLT seems to be feasible at three-leg signalized intersections where the left-turn is permissive and a pedestrian signal exists at the conflicting approach. However, in order to use the PPLT in earnest, it is necessary to revise the road traffic act, traffic signs, and related manuals.

• Atmosphere
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• v.27 no.4
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• pp.483-498
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• 2017

Sky view factor can quantify the influence of complex obstructions. This study aims to evaluate the best available SVF method that represents an urban thermal condition with land cover in complex city of Korea and also to quantify a correlation between SVF and mean air temperature; the results are as follows. First, three SVF methods comparison result shows that urban thermal study should consider forest canopy induced effects because the forest canopy test (on/off) on SVF reveals significant difference range (0.8, between maximum value and minimum value) in comparison with the range (0.1~0.3) of SVFs (Fisheye, SOLWEIG and 3DPC) difference. The significance is bigger as a forest cover proportion become larger. Second, R-square between SVF methods and urban local mean air temperature seems more reliable at night than a day. And as the value of SVF increased, it showed a positive slope in summer day and a negative slope in winter night. In the SVF calculation method, Fisheye SVF, which is the observed value, is close to the 3DPC SVF, but the grid-based SWG SVF is higher in correlation with the temperature. However, both urban climate monitoring and model/analysis study need more development because of the different between SVF and mean air temperature correlation results in the summer night period, which imply other major factors such as cooling air by the forest canopy, warming air by anthropogenic heat emitted from fuel oil combustion and so forth.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.11
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• pp.6898-6905
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• 2014

A stress ribbon bridge is a PSC structure that behaves as a reverse arch structure due to post-tensioned thin deck of the catenary type. In foreign countries, the stress ribbon bridge is recognized as the minimum destruction of nature and beautiful bridge, and has many construction examples as pedestrian and car bridges. On the other hand, there have been few studies in Korea. In this study, the FE Analysis model was established for different construction stages considering the nonlinear and time-dependent behaviors. The FE model was verified by a comparison with the numerical results and the behavior was analyzed for the different construction stages.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.651-658
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• 2015

Recently, lots of research works have been actively focused on the self-driving car. In order to implement the self-driving car, lots of fusion techniques should be merged and, specially, it is noted that a vehicle-attached camera can provide several useful functionalities such as traffic lights recognition, pedestrian detection, stop-line recognition including simple driving records. Accordingly, as one of the efficient tools for the self-driving car implementation, this paper proposes a mathematical model for estimating effectively the road distance with a vehicle-attached black box camera. The proposed model can be effectively used for estimating the road distance by using the height of black box camera or the widths of the referenced road line and the observed road line. Through several simulations, it is shown that the proposed model is effective in estimating the road distance.

• International Journal of Highway Engineering
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• v.20 no.2
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• pp.75-85
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• 2018

PURPOSES : This study aimed to analyze traffic accidents at circular intersections, and discuss accident reduction strategies based on land use and vehicle type. METHODS : Traffic accident data from 2010 to 2014 were collected from the "traffic accident analysis system" (TAAS) data set of the Road Traffic Authority. To develop the accident rate model, a multiple linear regression model was used. Explanatory variables such as geometry and traffic volume were used to develop the models. RESULTS : The main results of the study are as follows. First, it was found that the null hypotheses that land use and vehicle type do not affect the accident rate should be rejected. Second, 16 accident rate models, which are statistically significant (with high $R^2$ values), were developed. Finally, the area of the central island, number of speed humps, entry lane width, circulatory roadway width, bus stops, and pedestrian crossings were analyzed to determine their effect on accidents according to the type of land use and vehicle. CONCLUSIONS : Through the developed accident rate models, it was revealed that the accident factors at circular intersections changed depending on land use and vehicle type. Thus, selecting the appropriate location of bus stops for trucks, widening entry lanes for cars, and installing splitter islands and optimal lighting for motorcycles were determined to be important for reducing the accident rate. Additionally, the evaluation showed that commercial and mixed land use had a weaker effect on accidents than residential land use.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.187-192
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• 2008

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human Jollowing by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. This paper describes appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• Journal of Korean Society of Transportation
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• v.28 no.5
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• pp.155-162
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• 2010

Elderly pedestrians account for more than 30% of all deaths in traffic accident and the number of elderly-related traffic accidents are increasing every year. Considering Korea's quickly aging society, drastic measures must henceforth be taken. Taking notice of the elderly living in and moving around the provinces, this research focused on analyzing the characteristics of elderly pedistrians' traffic accidents on provincial roads and developing an Equivalent Property Damage Only (EPDO) model. The authors collected 720 traffic accident data points from the police agency and developed the EPDO model, weighted differently by light injury, severe injury, and death using Multiple Regression Analysis. As a result, the speed of vehicles is the most influential variable in EPDO, and the shape of the road is significant as well. Therefore, various policies should be established like improving the environmental factors of provincial roads, like expanding speed-reduction treatments and signage, and setting up detours around areas of high elderly concentration.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2179-2184
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• 2007

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. This paper described appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.25-31
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• 2021

Moving toward an aged society, traffic accidents involving elderly drivers have also attracted broader public attention. A rapid increase of senior involvement in crashes calls for developing appropriate crash-severity prediction models specific to senior drivers. In that regard, this study leverages machine learning (ML) algorithms so as to predict the severity of vehicle-pedestrian collisions induced by elderly drivers. Specifically, four ML algorithms (i.e., Logistic model, K-nearest Neighbor (KNN), Random Forest (RF), and Support Vector Machine (SVM)) have been developed and compared. Our results show that Logistic model and SVM have outperformed their rivals in terms of the overall prediction accuracy, while precision measure exhibits in favor of RF. We also clarify that driver education and technology development would be effective countermeasures against severity risks of senior driver-induced collisions. These allow us to support informed decision making for policymakers to enhance public safety.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.61-68
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• 2024

Despite the continuous efforts to mitigate pedestrian accidents at crosswalks, the problem persist. Vulnerable groups, including the elderly and disabled individuals are at a risk of being involved in traffic incidents. This paper proposes the implementation of object detection algorithm using the YOLO v5 model specifically for pedestrians using assistive devices like wheelchairs and crutches. For this research, data was collected and utilized through image crawling, Roboflow, and Mobility Aids datasets, which comprise of wheelchair users, crutch users, and pedestrians. Data augmentation techniques were applied to improve the model's generalization performance. Additionally, ensemble techniques were utilized to mitigate type 2 errors, resulting in 96% recall rate. This demonstrates that employing ensemble methods with a single YOLO model to target transportation-disadvantaged individuals can yield accurate detection performance without overlooking crucial objects.