• 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.

• International Journal of Highway Engineering
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• v.13 no.1
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• pp.49-57
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• 2011

This study deals with the traffic accident of arterial link sections in the case of Cheongju. The purpose of the study is to develop the traffic accident model by the function of arterial links. In pursuing the above, this study gives particular attentions to developing the appropriate models using the accident data of main and minor arterial roads divided by 472 small link sections. The main results analyzed are as follows. First, as the t test on the accident characteristics of main and minor arterial roads shows that there are differences in the number of accident and EPDO(equivalent property damage only) between two roads, the development of models by function is analyzed to be appropriate. Second, it is analyzed that ZINB models are all statistically suitable to the number of accident and EPDO of main arterial roads. Third, the analysis shows that EPDOs of minor arterial roads fit to ZINB, and the number of the accident fit to ZIP model. Finally, the common variables of main arterial roads are evaluated to be the traffic volume and the number of inflection point, and those of minor be the average grade.

• Journal of Korean Society of Transportation
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• v.26 no.6
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• pp.71-80
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• 2008

Typically uncontrolled intersections are characterized by the absence of signal, stop and yield sign, and by very light traffic volume. In this study, a gap acceptance model for such uncontrolled intersections has been modeled. The motivation is to identify the behavior of drivers so that the traffic flow phenomena can be easily understood. For this, actual traffic survey was accomplished at intersections in Suwon and the data have been fed into modeling process. The logit model was used and the results showed that total delay experienced by drivers, turning right movement, age, sex, and the existence of passenger affected gap acceptance. For example, male drivers, with experiencing longer delay and having passenger(s) with them, accepted shorter gaps. These identified characteristics regarding gap acceptance could be used for facility design and/or safety oriented traffic information dissemination near uncontrolled intersections.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.29-42
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• 2012

Recently, traffic congestion has become serious due to increase of private car usages. Carsharing or other innovative public transportation systems were developed to alleviate traffic congestion and carbon emissions. These measures can make the traffic environment more comfortable, and efficient. Cloud Transportation System (CTS) is a recent carsharing model. User can rent an electronic vehicles with various traffic information through the CTS. In this study, a concept, vision and scenarios of CTS are introduced. And, authors analyzed the location of CTS rental stations and estimated CTS demands. Firstly, we analyze the number of the population, employees, students and traffic volume in study areas. Secondly, the frequency and utilization time are examined. Demand for CTS in each traffic zone was estimated. Lastly, the CTS rental station location is determined based on the analyzed data of the study areas. Evaluation standard of the determined location includes accessibility and density of population. And, the number of vehicles and that of parking zone at the rental station are estimated. The result suggests that Haewoondae Square parking lot would be assigned 11 vehicles and 14.23 parking spaces and that Dongbac parking lot be assigned 7.9 vehicles and 10.29 parking spaces. Further study requires additional real-time data for CTS to increase accuracy of the demand estimation. And network design would be developed for redistribution of vehicles.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.109-122
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• 2016

Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.

• Journal of the Korean Society of Safety
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• v.30 no.1
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• pp.104-110
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• 2015

This study deals with the roundabout accidents. The goal of this study is to develop the sideswipe accident models at roundabout. In the pursuing the above, this study gives particular attentions to collecting the data of geometric structure and accidents of 54 roundabouts in Korea and developing the Poisson and negative binomial regression models. The main results are as follows. First, sideswipe accident is analyzed to be the highest frequency that is 39.5% of total accident data. Second, Poisson models which is statistically significant is developed. Finally, traffic volume per approach($X_1$), number of circulatory roadway($X_3$), operation of parking lot($X_4$) and width of circulatory roadway($X_6$) are adopted as the common variables. This study might be expected to give some implications to the accident research on the roundabout.

• Journal of the Korean Society of Safety
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• v.29 no.6
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• pp.151-157
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• 2014

This study deals with the rear-end collision at roundabouts. The purpose of this study is to develop the accident models of rear-end collision in Korea. In pursuing the above, this study gives particular attention to developing the appropriate models using Poisson, negative binomial model, ZAM, multiple linear and nonlinear regression models, and statistical analysis tools. The main results are as follows. First, the Vuong statistics and overdispersion parameters indicate that ZIP is the most appropriate model among count data models. Second, RMSE, MPB, MAD and correlation coefficient tests show that the multiple nonlinear model is the most suitable to the rear-end collision data. Finally, such the independent variables as traffic volume, ratio of heavy vehicle, number of circulatory roadway lane, number of crosswalk and stop line are adopted in the optimal model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.539-547
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• 2012

Increasing the mode transfer volume between public transportation modes has known to be necessary for efficiency improvement of public transportation system operation and it is also found to be important to have relevant transfer point selection with reflection of current travel pattern. This study is in regards to providing a selection guideline for the location of transfer point between public transport modes. This case study has been carried out for Daegu Metropolitan City especially for public transportation users behaviour by analysis of daily usage of transportation card to identify the transfer travel pattern. A cluster analysis was applied to categorize the pattern of transfer stop which induces many users and a discriminant analysis also utilized for grouping the stops by number of transfer trip. This research produces the estimation result of transfer volume for urban railway system no.3 in Daegu City which is currently under construction. In addition, the locations of transfer center has also been proposed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.63-73
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• 2003

COSMOS(Cycle, Offset, Split Model for Seoul), a real-time traffic adaptive signal system. estimates queue lengths on each approach on the basis of arithmetic average spot speeds calculated on loop detectors installed at each of two adjacent lanes. In this paper, A new method, a traffic volume-weighted average method, was studied and compared with the existing arithmetic average method. It was found that the relationship between the ratio of volumes of two lanes and the difference of average speed of each lane has a linear form. With field data, The two methods were applied and the proposed method shows more stable and reasonable queue estimation results.

• International Journal of Highway Engineering
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• v.19 no.2
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• pp.113-126
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• 2017

PURPOSES : This study proposes standards for rural access road pavement section and thickness design considering existing access road construction conditions; the study also proposes a complementary policy that can be used for design convenience. METHODS : Various literature review and case studies had been performed in terms of rural access road section and thickness design, both domestically and internationally, and this was followed by domestic rural access road field surveys. KPRP and KENLAYER were used to analyze the commonalities and predict the remaining life. Data on real cost is used to select an appropriate construction method through economic analysis. RESULTS : The economic efficiency of concrete pavement ($15{\times}15$) was the highest in terms of economic efficiency of performance life and traffic volume. In the case of asphalt pavement, it is considered that the most economical method is to implement micro-surfacing method four times as a preventive maintenance method (once every 10 years and 4.5 years for asphalt concrete pavement and MS construction method, respectively). Repairable asphalt pavement is advantageous for areas where heavy vehicles are expected to pass. In the case of other general areas, it is considered economical to place concrete ($15{\times}15$) pavement. However, as analytical results on its performance life are unavailable, it is to be considered for study in the future. CONCLUSIONS : This study proposed interim design guidelines based on various domestic and international design guidelines and case studies. However, in order to develop the final design criteria applicable to the field, it is necessary to (a) estimate the bearing capacity of the lower level of the pavement at various sites, (b) estimate the daily traffic volume, (c) implement advanced low-cost pavement technologies, and (d) propose maintenance standards and techniques for long-term performance.