• Journal of Korea Spatial Information System Society
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• v.9 no.1
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• pp.79-90
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• 2007

In this paper we proposed and implemented an incident detection model which combines fuzzy algorithm and traffic pattern in order to enhance the efficiency of incident detection for the highways with lamps. Most of the existing algorithms dealt with highways without lamps and can not be used for detecting incidents in the highways with lamps. The data used for model building are traffic volume, occupancy, and speed data. They have been collected by a loop sensor at 5 minutes interval at a point in the Internal Circular Highway of Seoul for the period of 3 months. In this model, the three parameters collected by sensor were fuzzified and combined with the daily traffic pattern of the link. The test of efficiency of the propsed model was performed by comparing the result of proposed model with traditional APID algorithm and fuzzy algorithm without the pattern data respectively. The result showed significant amount of improvement in reducing the false incident detection rate by 18%.

• International Journal of Highway Engineering
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• v.11 no.2
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• pp.17-25
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• 2009

The goal of this study is to develop Logistic regression model by accident location(entry section, exit section, inside intersection and pedestrian crossing section). Based on the accident data of Chungbuk Provincial Police Agency(2004$\sim$2005) and the field survey data, the geometric elements, environmental factor and others related to traffic accidents were analyzed. Developed models are all analyzed to be statistically significant(chi-square p=0.000, Nagelkerke $R^2$=0.363$\sim$0.819). The models show that the common factors of accidents are the traffic volume(ADT), distant of crossing and exclusive left turn lane, and the specific factors are the minor traffic volume(inside intersection model) and U-turn of main road(pedestrian crossing model). Hosmer & Loineshow tests are evaluated to be statistically significant(p$\geqq$0.05) except the entry section model. The correct classification rates are also analyzed to be very predictable(more than 73.9% to all models).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.11 no.4
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• pp.55-66
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• 1991

Presented is a study on the realistic determination of design loads and design criteria for bridge structures. The current bridge design code does not consider realistically the uncertainties inherent in loads and resistances and thus the level of safety varies greatly among the bridge spans. The resonable bridge design loads and design criteria which exhibit uniform reliability among various bridge spans are therefore derived in the present paper. The proposed design loads are determined from the analysis of numerous data obtained from actual traffic survey and the design criteria are based on the advanced concept of load and resistance factor format. The live load factors take into account resonably the effects of traffic volume increase. The proposed design loads and design criteria show uniform safety level for various bridge spans and reasonably consider the effects of traffic volume increase. The present study provides useful and valuable data for new version of our bridge design code.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.107-116
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• 2005

The information on travel time in providing the information of traffic to drivers is one of the most important data to control a traffic congestion efficiently. Especially, this information is the major element of route choice of drivers, and based on the premise that it has the high degree of confidence in real situation. This study developed a vehicle arrival time prediction algorithm called as "VAT-DV" for 6 corridors in total 6.1Km of "Nam-san area trffic information system" in order to give an information of congestion to drivers using VMS, ARS, and WEB. The spatial scope of this study is 2.5km~3km sections of each corridor, but there are various situations of traffic flow in a short period because they have signalized intersections in a departure point and an arrival point of each corridor, so they have almost characteristics of interrupted and uninterrupted traffic flow. The algorithm uses the information on a demand volume and a queue length. The demand volume is estimated from density of each points based on the Greenburg model, and the queue length is from the density and speed of each point. In order to settle the variation of the unit time, the result of this algorithm is strategically regulated by importing the AVI(Automatic Vehicle Identification), one of the number plate matching methods. In this study, the AVI travel time information is composed by Hybrid Model in order to use it as the basic parameter to make one travel time in a day using ILD to classify the characteristics of the traffic flow along the queue length. According to the result of this study, in congestion situation, this algorithm has about more than 84% degree of accuracy. Specially, the result of providing the information of "Nam-san area traffic information system" shows that 72.6% of drivers are available.

• International Journal of Highway Engineering
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• v.18 no.6
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• pp.153-160
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• 2016

OBJECTIVES : The objective of this study is to develop a traffic accident model of a roundabout based on the type of land use. METHODS : The traffic accident data from 2010 to 2014 were collected from the "traffic accident analysis system (TAAS)" data set of the Road Traffic Authority. A multiple linear regression model was utilized in this study to analyze the accidents based on the type of land use. Variables such as geometry and traffic volume were used to develop the accident models based on the type of land use. RESULTS : The main results are as follows. First, the null hypothesis that the type of land use does not affect the number of accidents is rejected. Second, four accident models based on the type of land use have been developed, which are statistically significant (high $R^2$ values). Finally, the total entering and circulating volumes, area of the central island, number of speed breakers, mean number of entry lanes, diameter of the inscribed circle, mean width of the entry lane, area of the roundabout, bus stops, and number of circulatory roadways are analyzed to see how they affect the accident for each type of land use. CONCLUSIONS : The development of the accident models based on the type of land use has revealed that the accident factors at a roundabout are different for each case. Thus, more speed breakers in commercial areas and an inscribed circle of proper diameter in commercial and residential areas are determined to be important for reducing the number of accidents. Additionally, expanding the width of the entry lanes, decreasing the area of the roundabouts in residential areas, and reducing the conflict factors such as bus stops in green spaces are determined to be important.

• Journal of Navigation and Port Research
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• v.42 no.4
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• pp.277-282
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• 2018

Recently, the Vessel Traffic Service (VTS) coverage has expanded to include coastal areas following the increased attention on vessel traffic safety. However, it has increased the workload on the VTS operators. In some cases, when the traffic volume increases sharply during the rush hour, the VTS operator may not be aware of the risks. Therefore, in this paper, we proposed a new method to recognize ship movement anomalies automatically to support the VTS operator's decision-making. The proposed method generated traffic pattern model without any category information using the unsupervised learning algorithm.. The anomaly score can be calculated by classification and comparison of the trained model. Finally, we reviewed the experimental results using a ship-handling simulator and the actual trajectory data to verify the feasibility of the proposed method.

• International Journal of High-Rise Buildings
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• v.3 no.2
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• pp.155-165
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• 2014

This study measured and compared the variation of ventilation rate and fan energy consumption according to various control strategies after installing wireless sensor-based pilot ventilation system in order to verify the applicability of demand-controlled ventilation (DCV) strategy that was efficient ventilation control strategy for underground parking lot. The underground parking lot pilot ventilation system controlled the ventilation rate by directly or indirectly tracking the traffic load in real-time after sensing data, using vehicle detection sensors and carbon monoxide (CO) and carbon dioxide ($CO_2$) sensor. The ventilation system has operated for 9 hours per a day. It responded real-time data every 10 minutes, providing ventilation rate in conformance with the input traffic load or contaminant level at that time. A ventilation rate of pilot ventilation system can be controlled at 8 levels. The reason is that a ventilation unit consists of 8 high-speed nozzle jet fans. This study proposed vehicle detection sensor based demand-controlled ventilation (VDS-DCV) strategy that would accurately trace direct traffic load and CO sensor based demand-controlled ventilation (CO-DCV) strategy that would indirectly estimate traffic load through the concentration of contaminants. In order to apply DCV strategy based on real-time traffic load, the minimum required ventilation rate per a single vehicle was applied. It was derived through the design ventilation rate and total parking capacity in the underground parking lot. This is because current ventilation standard established per unit floor area or unit volume of the space made it difficult to apply DCV strategy according to the real-time variation of traffic load. According to the results in this study, two DCV strategies in the underground parking lot are considered to be a good alternative approach that satisfies both energy saving and healthy indoor environment in comparison with the conventional control strategies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.101-116
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• 2017

This Study estimates the actual night traffic using the smart card data used by most of the public transportation users, and compares it with the current night bus routes by KT Telecom based on the night time call volume. In order to compare the current night bus and night trips evaluated by smart card data, we presented indicators related to the degree of matching, and estimated the volume of service currently provided. The unique approach of the study is that we chose subway station instead of bus stop for the unit of the study. Bus stops has their complexity in a way that stops with same name could belong to different administrative area depending on its direction. For this reason, we decided to use subway station and defined its adjacent administrative district as the scope of influence. Since night bus is the primary means of transportation during the late night, it is anticipated that they will be able to provide better service by calculating the actual traffic and selecting the routes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4268-4290
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• 2015

Future mobile communications face enormous challenges as traditional voice services are replaced with increasing mobile multimedia and data services. To address the vast data traffic volume and the requirement of user Quality of Experience (QoE) in the next generation mobile networks, it is imperative to develop efficient content distribution technique, aiming at significantly reducing redundant data transmissions and improving content delivery performance. On the other hand, in recent years cloud computing as a promising new content-centric paradigm is exploited to fulfil the multimedia requirements by provisioning data and computing resources on demand. In this paper, we propose a cooperative caching framework which implements State based Content Distribution (SCD) algorithm for future mobile networks. In our proposed framework, cloud service providers deploy a plurality of cloudlets in the network forming a Distributed Cloud Service Network (DCSN), and pre-allocate content services in local cloudlets to avoid redundant content transmissions. We use content popularity and content state which is determined by content requests, editorial updates and new arrivals to formulate a content distribution optimization model. Data contents are deployed in local cloudlets according to the optimal solution to achieve the lowest average content delivery latency. We use simulation experiments to validate the effectiveness of our proposed framework. Numerical results show that the proposed framework can significantly improve content cache hit rate, reduce content delivery latency and outbound traffic volume in comparison with known existing caching strategies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.3
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• pp.90-99
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• 2020

The "Low Emission Zone" (LEZ) system restricts entry of vehicles with high air pollutants into city centers. Implementation of the system improves air environment around the world. Since 2012, operating restrictions have been applied to all of Seoul's metropolitan areas and some other metropolitan areas in the state. Beginning in December 2019, entry of 5th class vehicles to the central green transport zone of Seoul has been restricted. In this study we examine the status of operational restrictions in this zone, and predict the amount of traffic reduction expected when numbers of target vehicles are expanded in the future, we use data for each vehicle's emission grade: by region and 'Origin-Destination Traffic Volume'. After estimating the amount of traffic entering Seoul's 25 autonomous districts, by emission class, we propose a target region that may have a significant effect if target areas for automobile operation restrictions expand in the future.