• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.5 no.1 s.9
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• pp.1-12
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• 2006

In order to estimate a dynamic origin and destination demand between on and off-ramps in the freeways, a traffic flow theory can be used to calculate a link distribution proportion of traffics moving between them. We have developed a dynamic traffic estimation model based on the three-phase traffic theory (Kerner, 2004), which explains the complexity of traffic phenomena based on phase transitions among free-flow, synchronized flow and moving jam phases, and on their complex nonlinear spatiotemporal features. The developed model explains and estimates traffic congestion in terms of speed breakdown, phase transition and queue propagation. We have estimated the link, on and off-ramp volumes at every time interval by using traffic data collected from vehicle detection systems in Korea freeway sections. The analyzed results show that the developed model describes traffic flows adequately.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.1017-1023
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• 2017

Duration induced by freeway crashes has a critical influence on traffic congestion. In general, crash duration composes detection and verification, response, and clearance time. Of these, the crash clearance time determined by a crash clearance team has attracted considerable attention in the freeway congestion management since the interest of the first two time stages faded away with increasing ubiquitous mobile phone users. The objective of this study is to identify the critical factors that affect freeway crash clearance time using a Cox's proportional hazard model. In total, 6,870 crash duration data collected from 30 major Korean freeways in 2013 were used. As a result, it was found that crashes during the night, with trailer or larger size truck, and in tunnel section contribute to increasing clearance time. Crashes associated with fatality, completed damage of crashed vehicle (s), and vehicles' fire or rollover after crash also lead to increasing clearance time. Additionally, an increase in the number of vehicles involved resulted in longer clearance time. On the other hand, crashes in the vicinity of tollgate, by passenger car, during spring, on flat section, and of car-facility type had longer clearance time. On the basis of the results, this paper suggested some strategic plans and mitigation measures to reduce crash clearance time on Korean freeway systems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.34-44
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• 2016

This study was initiated to evaluate the performance of methodologies to estimate the space mean speed(SMS) using the time mean speed(TMS) which was collected from the vehicle detection system(VDS) in expressways. To this end, the methodologies presented in prior studies were firstly summarized. It is very hard to achieve exact SMSs and TMSs due to mechanical and communication errors in the field. Thus, a microscopic traffic simulation model was utilized to evaluated the performance. As a result, the harmonic mean and volume-distance weighted harmonic mean were close to the SMS in the case in which the TMSs of individual vehicles were used. However, when the 30-second-interval aggregated TMS were used, the volume-distance weighted harmonic mean was outstanding. In this study, a radar detector was installed in the Joongbu expressway to collect the SMS. The trajectory of individual vehicles collected from the detector were used to calculate the SMS, which was compared with the estimates using other methodologies selected in this study. As a result, the volume-distance weighted mean was turned out to be close to the SMS. However, as the congestion becomes severe. the deviation between the two speed becomes bigger.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.47-59
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• 2000

The purpose of this study is to develop travel-time estimation model using neural networks and prediction model using neural networks and kalman-filtering technique. The data used in this study are travel speed collected from inductive loop vehicle detection systems(VDS) and travel time collected from the toll collection system (TCS) between Seoul and Osan toll Plaza on the Seoul-Pusan Expressway. Two models, one for travel-time estimation and the other for travel-time Prediction were developed. Application cases of each model were divided into two cases, so-called, a single-region and a multiple-region. because of the different characteristics of travel behavior shown on each region. For the evaluation of the travel time estimation and Prediction models, two Parameters. i.e. mode and mean were compared using five-minute interval data sets. The test results show that mode was superior to mean in representing the relationship between speed and travel time. It is, however shown that mean value gives better results in case of insufficient data. It should be noted that the estimation and the Prediction of travel times based on the VDS data have been improved by using neural networks, because the waiting time at exit toll gates can be included for the estimation of travel time based on the VDS data by considering differences between VDS and TCS travel time Patterns in the models. In conclusion, the results show that the developed models decrease estimation and prediction errors. As a result of comparing the developed model with the existing model using the observed data, the equality coefficients of the developed model was average 88% and the existing model was average 68%. Thus, the developed model was improved minimum 17% and maximum 23% rather then existing model .

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.3
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• pp.457-468
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• 2018

To improve understanding of the physico-chemical characteristics of aerosols in the national park and comparing the air pollution between national park and the urban area nearby national park, the aerosol characterization study was conducted in Bukhansan National Park, Seoul, from July through September 2017. Semi-continuous measurements of $PM_{2.5}$ using PILS (Particle Into Liquid System) coupled with IC (Ion Chromatography) and TOC (Total Organic Carbon) analyzer allowed quantification of concentrations of major ionic species($Cl^-$, $SO_4{^{2-}}$, $NO_3{^-}$, $Na^+$, $NH_4{^+}$, $K^+$, $Mg{^{2+}}$ and $Ca{^{2+}}$) and water soluble organic carbon (WSOC) with 30-minute time resolution. The total mass concentration of $PM_{2.5}$ was measured by T640 (Teledyne) with 5-minute time resolution. The black carbon (BC) and ozone were measured with a minute time resolution. The timeline of aerosol chemical compositions reveals a strong influence from urban area (Seoul) at the site in Bukhansan National Park. Inorganic aerosol composition was observed to be dominated by ammoniated sulfate at most times with ranging from $0.1{\sim}32.6{\mu}g/m^3$ (6.5~76.1% of total mass of $PM_{2.5}$). The concentration of ammonium nitrate, a potential indicator of the presence of local source, ranged from below detection limits to $20{\mu}g/m^3$ and was observed to be highest during times of maximum local urban (Seoul) impact. The total mass of $PM_{2.5}$ in Bukhansan National Park was observed to be 10~23% lower than the total mass of $PM_{2.5}$ in urban area (Gireum-dong and Bulgwang-dong, Seoul). In general, ozone concentration in Bukhansan National Park was observed to be similar or higher than urban sites in Seoul, suggesting additional biogenic VOCs with $NO_x$ from vehicle emission were to be precursors for ozone formation in Bukhansan National Park.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.5
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• pp.595-602
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• 2017

In Korea, much research and development have occurred to enhance the technological competitiveness of tuna purse seining fisheries. Due to these efforts, fishing efficiency has been improved with the development of radar, sonar and global positioning systems for fish detection and revisions to the hull forms of tuna purse seiners. However, for skiff boats, net boats and speed boats, which are auxiliary working boats mounted on tuna purse seiners, technology has lagged behind relative to the modernization of the main vessel. In this study, the hull of an existing propeller-based net boat with steel wire net to protect tuna was changed to the hull of a water jet propulsion vehicle to reduce resistance and improve maneuverability. As a result, a prototype of a water jet propulsion option was produced according to the aluminum structure strength standards specified by the Ministry of Oceans and Fisheries, and safety was confirmed by performing a drop test. Moreover, through a sea trial test, an existing net boat was shown to have a speed of 12.0knots and a towing force of 2,545 kgf at 2,500 RPM. The prototype had a speed of 26.7 knots and a towing force of 2,011 kgf at 3,200 RPM, which satisfied the towing capacity standards of auxiliary working boats mounted on tuna purse seiners.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.211-221
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• 2019

The death toll for every 10,000 cars registered in Korea is 1.4, which is still the lowest among OECD members, and the need for rescue and response systems is emerging. In response, the company is developing a vehicle ICT-based emergency rescue system (e-Call) that can handle accidents such as rapid and accurate life saving by automatically sending accident detection and related information to the central center in the event of a traffic accident. However, ordinary citizens are negative about the installation and cost of e-Call services. To solve these problems, various introduction and operation methods of e-Call were proposed for activation of terminal distribution. In addition, the effect of introducing e-Call was analyzed by predicting the penetration rate of e-Call terminals. Analysis shows that 463 to 926 deaths and 3,335 to 6,66.9 billion won will be saved in 10 years after the introduction of e-Call terminals.

• Journal of Korea Spatial Information System Society
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• v.4 no.2 s.8
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• pp.55-64
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• 2002

VEfficient generation of road data is one of the most important issues in GIS (Geographic Information System). In this paper, we propose a hybrid approach for automatic generation of road data by combining mobile mapping and image processing techniques. Mobile mapping systems have a form of vehicle equipped with CCD camera, GPS, and INS. They can calculate absolute position of objects that appear in acquired image by photogrammetry, but it is labor-intensive and time-consuming. Automatic road detection methods have been studied also by image processing technology. However, the methods are likely to fail because of obstacles and exceptive conditions in the real world. To overcome the problems, we suggest a hybrid method for automatic road generation, by exploiting both GPS/INS data acquired by mobile mapping system and image processing algorithms. We design an estimator to estimate 3-D coordinates of road line and corresponding location in an image. The estimation process reduces complicated image processing operations that find road line. The missing coordinates of road line due to failure of estimation are obtained by cubic spline interpolation. The interpolation is done piecewise, separated by rapid change such as road intersection. We present experimental results of the suggested estimation and interpolation methods with image sequences acquired by mobile mapping system, and show that the methods are effective in generation of road data.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.537-542
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• 2017

Aggressive driving is a major cause of car accidents. Previous studies have mainly analyzed young driver's aggressive driving tendency, yet they were only done through pure clustering or classification technique of machine learning. However, since elderly people have different driving habits due to their fragile physical conditions, it is necessary to develop a new method such as enhancing the characteristics of driving data to properly analyze aggressive driving of elderly drivers. In this study, acceleration data collected from a smartphone of a driving vehicle is analyzed by a newly proposed ECA(Enhanced Clustering method for Acceleration data) technique, coupled with a conventional clustering technique (K-means Clustering, Expectation-maximization algorithm). ECA selects high-intensity data among the data of the cluster group detected through K-means and EM in all of the subjects' data and models the characteristic data through the scaled value. Using this method, the aggressive driving data of all youth and elderly experiment participants were collected, unlike the pure clustering method. We further found that the K-means clustering has higher detection efficiency than EM method. Also, the results of K-means clustering demonstrate that a young driver has a driving strength 1.29 times higher than that of an elderly driver. In conclusion, the proposed method of our research is able to detect aggressive driving maneuvers from data of the elderly having low operating intensity. The proposed method is able to construct a customized safe driving system for the elderly driver. In the future, it will be possible to detect abnormal driving conditions and to use the collected data for early warning to drivers.

• Journal of Sensor Science and Technology
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• v.7 no.2
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• pp.124-130
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• 1998

High-speed 3D vision systems are essential for autonomous robot or vehicle control applications. In our study, a stereo vision process has been developed. It consists of three steps : extraction of edges in right and left images, matching corresponding edges and calculation of the 3D map. This process is implemented in a VME 150/40 Imaging Technology vision system. It is a modular system composed by a display, an acquisition, a four Mbytes image frame memory, and three computational cards. Programmable accelerator computational modules are running at 40 MHz and are based on TMS320C31 DSP with a $64{\times}32$ bit instruction cache and two $1024{\times}32$ bit internal RAMs. Each is equipped with 512 Kbytes static RAM, 4 Mbytes image memory, 1 Mbytes flash EEPROM and a serial port. Data transfers and communications between modules are provided by three 8 bit global video bus, and three local configurable pipeline 8 bit video bus. The VME bus is dedicated to system management. Tasks between DSPs are distributed as follows: two DSPs are used to edges detection, one for the right image and the other for the left one. The last processor computes the matching process and the 3D calculation. With $512{\times}512$ pixels images, this sensor generates dense 3D maps at a rate of about 1 Hz depending of the scene complexity. Results can surely be improved by using a special suited multiprocessors cards.