Kim, Beomseong;Choi, Baehoon;An, Jhonghyun;Hwang, Jaeho;Kim, Euntai
Journal of the Korean Institute of Intelligent Systems
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v.24
no.4
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pp.392-397
/
2014
Recently, there are many researches on active safety system of intelligent vehicle. To reduce the probability of collision caused by driver's inattention and mistakes, the active safety system gives warning or controls the vehicle toward avoiding collision. For the purpose, it is necessary to recognize and analyze circumstances around. In this paper, we will treat the problem about collision risk assessment. In general, it is difficult to calculate the collision risk before it happens. To consider the uncertainty of the situation, Monte Carlo simulation can be employed. However it takes long computation time and is not suitable for practice. In this paper, we apply neural networks to solve this problem. It efficiently computes the unseen data by training the results of Monte Carlo simulation. Furthermore, we propose the features affects the performance of the assessment. The proposed algorithm is verified by applications in various crash scenarios.
Journal of Korean Society of Coastal and Ocean Engineers
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v.18
no.4
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pp.269-282
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2006
We numerically studied tsunami propagation characteristics through Korean Straits based on nonlinear shallow water equation, a robust wave driver of the near field tsunamis. Tsunamis are presumed to be generated by the earthquake in Tsuhima-Koto fault line. The magnitude of earthquake is chosen to be 7.5 on Richter scale, which corresponds to most plausible one around Korean peninsula. It turns out that it takes only 60 minutes for leading waves to cross Korean straits, which supports recently raised concerns at warning system might be malfunctioned due to the lack of evacuation time. We also numerically obtained the probability of tsunami inundation of various levels, usually referred as tsunami hazard, along southern coastal area of Korean Peninsula based on simple seismological and Kajiura (1963)'s hydrodynamic model due to tsunami-generative earthquake in Tsuhima-Koto fault line. Using observed data at Akita and Fukaura during Okushiri tsunami in 1993, we verified probabilistic model of tsunami height proposed in this study. We believe this inundation probability of various levels to give valuable information for the amendment of current building code of coastal disaster prevention system to tame tsunami attack.
The aim of this study is to analyze the effects of DVR(Driving Video Recorder) operation on decreasing the number of traffic accidents, the cost of traffic accident claim, and the behavioral change in drivers' driving. The data for this research are obtained from taxi drivers in Busan. For this, Structural Equation Model and two-way ANOVA are employed for empirical analysis. Overall results of this study show that the number of traffic accidents of 4 taxi corporations in Busan has decreased by average 32.7 percent after using DVRs. In addition, as to the cost of taxi accident claims, it is expected that the DVR operation has a considerable effect on economic benefits of taxi corporations. Moreover, this study could make clear the difference in behaviors between DVR users and non-users, and discriminate the positive and negative impacts of the DVR operation on the drivers' driving behavior. The study quantitatively examined the indirect impact of 'attitude', 'subject norm' and 'behavioral control' factors on planned 'behavior', and the direct impact of 'behavioral control' factor on the planned 'behavior'. This study suggests that they should add the video recoding function of DVRs when operation recorder(blackbox for the car) is obligatorily set up on cars for business by traffic security law.
This study has analyzed the factors that influence the safety consciousness of elderly drivers. To achieve this, 307 elderly who drives commercial and non-commercial in Daejeon, Sejong, Chungnam and Chungbuk area were selected as study subjects. For the data analysis, PASW Statistics 18.0 was used. The main results of this study are as follows. The level of safety consciousness of commercial and non-commercial drivers were 6.49 and 6.93 respectively showing that drivers of non-commercial were significantly higher. Second, the factors that influence the safety consciousness were shown to be significantly different for each group. The factors that influence the safety consciousness of commercial drivers were shown in the order of safety-seeking motivation, economic status, daily driving hours, sensation-seeking disposition. The factors that influence the safety consciousness of non-commercial drivers were shown in the order of safety-seeking motivation, health status, whether or not the accident was experienced, sensation-seeking disposition. Based on these results, several ways were suggested to improve the safety consciousness of elderly drivers and prevent the traffic accidents.
Park, Jinho;Lim, Joonbeom;Joo, Sungkab;Lee, Soobeom
International Journal of Highway Engineering
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v.17
no.2
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pp.107-122
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2015
PURPOSES : The use of virtual driving tests to determine actual road driving behavior is increasing. However, the results indicate a gap between real and virtual driving under same road conditions road based on ergonomic factors, such as anxiety and speed. In the future, the use of virtual driving tests is expected to increase. For this reason, the purpose of this study is to analyze the gap between real and virtual driving on same road conditions and to use a calibration formula to allow for higher reliability of virtual driving tests. METHODS : An intelligent driving recorder was used to capture real driving. A driving simulator was used to record virtual driving. Additionally, a virtual driving map was made with the UC-Win/Road software. We gathered data including geometric structure information, driving information, driver information, and road operation information for real driving and virtual driving on the same road conditions. In this study we investigated a range of gaps, driving speeds, and lateral positions, and introduced a calibration formula to the virtual record to achieve the same record as the real driving situation by applying the effects of the main causes of discrepancy between the two (driving speed and lateral position) using a linear regression model. RESULTS: In the virtual driving test, driving speed and lateral position were determined to be higher and bigger than in the real Driving test, respectively. Additionally, the virtual driving test reduces the concentration, anxiety, and reality when compared to the real driving test. The formula includes four variables to produce the calibration: tangent driving speed, curve driving speed, tangent lateral position, and curve lateral position. However, the tangent lateral position was excluded because it was not statistically significant. CONCLUSIONS: The results of analyzing the formula from MPB (mean prediction bias), MAD (mean absolute deviation) is after applying the formula to the virtual driving test, similar to the real driving test so that the formula works. Because this study was conducted on a national, two-way road, the road speed limit was 80 km/h, and the lane width was 3.0-3.5 m. It works in the same condition road restrictively.
Purpose: The aim of the present study is to evaluate the effect of repetitive distraction and compression on new bone formation during distraction period. Materials and methods: Sixteen healthy rabbits, weighing about 2.5kg, were used in this experiment. A unilateral mandibular osteotomy was performed in the left mandible and the distractor(Track 1 $plus^{(R)}$, Gebruder Martin $GmbH^{(R)}$, Germany) was fixed with four screws (Cross driver screw $TI^{(R)}$, Gebruder Martin $GmbH^{(R)}$, Germany). After 4 days, the mandibles were distracted at a rate of 0.6mm/day for 10 days to obtain the amount of 6mm distraction in the control group(n=4). In the experimental group A(n=6), they were distracted at a rate of 1.2mm/day for 5 days and then compression of 0.6mm length and distraction of 0.6mm per 12 hours were carried out as counter direction for 5 days, relatively. In the experimental group B(n=6), distraction of 1.2mm length and compression of 0.6mm length per 12 hours were repeated for 10 days to obtain the amount of 6mm distraction finally. The experimental animals were sacrificed at 2 and 4 weeks after surgery and block specimens were obtained. With histologic and histomorphometric analysis, we observed the histologic changes of the cells and bone formation after H-E and Masson- Trichrome staining and then, measured Bone Deposition Rate with TOMORO $ScopeEye^{TM}$ ver. 3.5(Olympus, Japan), Results: Histologically, new bone formation was examined in all experimental groups and the control. But, the ability of bone formation of the experimental group A was somewhat better than any other groups. On the histomorphometric analysis, Bone Deposition Rate was higher in the experimental group A$(50.67{\pm}4.36%)$ than in the control group$(45.94{\pm}3.97%)$ and in the experimental group B$(42.68{\pm}5.70%)$. These data showed significant differences statistically(p<0.05). Conclusion: These results show that the distraction osteogenesis using repetitive compression and distraction force in the early consolidation period may be effective for new bone formation.
The Journal of The Korea Institute of Intelligent Transport Systems
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v.18
no.6
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pp.110-123
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2019
Traffic data is the most basic element necessary for transportation planning and traffic system operation. Recently, a method of estimating traffic flow characteristics using distance to a leading vehicle measured by an ADAS camera has been attempted. This study investigated the feasibility of the ADAS vehicle reflecting the distance error of image-based vehicle identification technology as a means to estimate the traffic flow through the normalized root mean square error (NRMSE) based on the number of lanes, traffic demand, penetration rate of probe vehicle, and time-space estimation area by employing the microscopic simulation model, VISSIM. As a result, the estimate of low density traffic flow (i.e., LOS A, LOS B) is unreliable due to the limitation of the maximum identification distance of ADAS camera. Although the reliability of the estimates can be improved if multiple lanes, high traffic demands, and high penetration rates are implemented, artificially raising the penetration rates is unrealistic. Their reliability can be improved by extending the time dimension of the estimation area as well, but the most influential one is the driving behavior of the ADAS vehicle. In conclusion, although it is not possible to accurately estimate the traffic flow with the ADAS camera, its applicability will be expanded by improving its performance and functions.
Automatic observing is the most efficient system for sky surveys that image many targets over large areas of the sky. Such a system requires the integrating control software that systematically manages astronomical instruments that are not connected to each other. In February of 2017, we installed a wide-field 10 inch telescope for Supernovae survey on the McDonald 30 inch telescope as a piggyback system. However, during the observations, information such as target coordinates could not be exchanged with the telescope mount. The reason is the program that controls the telescope control system (TCS) and the program that controls the imager operate on independent PCs. KAOS30 is an integrated observing software developed to improve this environment. The software is composed of four packages that are the Telescope Control Package (TCP), the Data Acquisition Package (DAP), the Auto Focus Package (AFP), and the Script Mode Package (SMP). The TCP communicates to the TCS and also communicates weather information. SMP supports automatic observing in a script mode, which improves the efficiency of the survey. KAOS30 was developed based on Visual C ++ and runs on the Windows operating system. It also supports the ASCOM driver platform for various manufacturers. The instruments that support ASCOM can be installed without modification of the program code. KAOS30 can be applied as software for many different telescopes in future projects.
In recent decades, microscopic simulation models have become powerful tools to analyze traffic flow on highways and to assist the investigation of level of service. The existing microscopic simulation models simulate an individual vehicle's speed based on a constant free-flow speed dominantly specified by users and driver's behavior models reflecting vehicle interactions, such as car following and lane changing. They set a single free-flow speed for a single vehicle on a given link and neglect to consider the effects of highway design elements to it in their internal simulation. Due to this, the existing models are limitted to provide with identical simulation results on both curved and tangent sections of highways. This paper presents a model developed to estimate the change of free-flow speeds based on highway design elements. Nine neural network models were trained based on the field data collected from seven different freeway curve sections and three different locations at each section to capture the percent changes of free-flow speeds: 100 m upstream of the point of curve (PC) and the middle of the curve. The model employing seven highway design elements as its input variables was selected as the best : radius of curve, length of curve, superelevation, the number of lanes, grade variations, and the approaching free-flow speed on 100 m upstream of PC. Tests showed that the free-flow speeds estimated by the proposed model were statistically identical to the ones from the field at 95% confidence level at each three different locations described above. The root mean square errors at the starting and the middle of curve section were 6.68 and 10.06, and the R-squares at these points were 0.77 and 0.65, respectively. It was concluded from the study that the proposed model would be one of the potential tools introducing the effects of highway design elements to free-flow speeds in simulation.
The Journal of The Korea Institute of Intelligent Transport Systems
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v.9
no.5
/
pp.38-48
/
2010
Adverse weather (e.g. strong winds, snow and ice) will probably appear as a more serious and frequent threat to road traffic than in clear climate. Another consequence of climate change with a natural disastrous on road traffic is respond to traffic accident more the large and high-rise bridge zone, tunnel zone, inclined plane zone and de-icing zone than any other zone, which in turn calls for continuous adaption of monitoring procedures. Accident mitigating measures against this accident category may consist of intense winter maintenance, the use of road weather information systems for data collection and early warnings, road surveillance and traffic control. While hazard from reduced road friction due to snow and ice may be eliminated by snow removal and de-icing measures, the effect of strong winds on road traffic are not easily avoided. The purpose of the study described here, was to design of amber information the relationship between traffic safety, weather, user information on road weather and driving conditions in local-scale Geographic. The most applications are the optimization of the amber information definition, improvements to road surveillance, road weather monitoring and improved accuracy of user information delivery. Also, statistics on wind gust, surface condition, vehicle category and other relevant parameters for wind induced accidents provide basis for traffic control, early warning policies and driver education for improved road safety at bad weather-exposed locations.
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