• Proceedings of the KOR-KST Conference
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• 2007.02a
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• pp.306-314
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• 2007

This paper is to develop a model for evaluation of highway alignment design considering the driver's behavior in order to enhance the highway safety. Under the conditions, this research included a new evaluation criteria development and an analysis on how to change evaluation criteria according to roadway alignments, to evaluate safety. The vehicle spacing and speed deviation are suggested as new evaluation index The evaluation criteria model can be used to compare the anticipated safety performance of two or more geometric alternatives for a proposed highway improvement.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.145-157
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• 2004

Microscopic freeway simulation models project the uncertain values of performance measures for subject traffic conditions by explaining drivers' driving behavior with lane changing and car-following models. However, the existing lane changing models are limited to gap acceptance oriented passive behavior of drivers and not able to capture more-or-less aggressive driving behavior(e.g. cut-in lane changing) ordinarily obseved in field. This paper suggests the definition of cut-inlane changing and presents its characteristics based on the findings from two different freeway on- and off-ramp sections. In addition, this paper proposes a new lane changing model capable of handling both passive and active drivers' driving behavior for better performance of simulations. The proposed lane changing model was tested with Hanyang Simulatin (HYTSIM), a microscopic freeway simulation program developed for this study. The HYTSIM simulation results reflecting the performance of the proposed lane changing model were compared against the field data. The test results showed that the distribution of gaps collected when vehicles change lanes were statistically identical to the field data at 95% confidence level.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.414-419
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• 1994

In recent years, there has been an increasing intest in control of active automotive suspension systems with a goal of improving the ride comfort and safety. Many approaches for these purposes have used linearized models of the suspension's dynamics, allowing the use of linear control theory. However, the linearized model does not well descriibe the actual system behavior which is inherently nonlinear. The object of this study is to develop a neuro controlled active suspension for the ride quality improvement. After obtaining active control law using optimal control theory, we use the artificial neural network to train the neuro controller to learn the relation of road input and control force. Form the numerical results, we found that back propagation learning does show good pattern matching and vertical acceleration of the driver's seat and sprung mass.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.384-389
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• 2008

In this paper, we propose a UML modeling of ATO on-board software. An automatic train operation (ATO) system is a real-time control system, which operates a train without a manual operation by a driver. For the safe and comfortable service, real-time embedded software for ATO on-board equipment should have both of high performance and reliability. UML-based object-oriented modeling technique is introduced and used widely to design software that satisfies this requirement. We used Rhapsody, which is a modeling tool for real-time embedded software, to model the construction and the behavior of ATO on-board equipment. As a result, ATO on-board software which performs the profile calculation and the real-time speed control is designed and implemented. The brief modeling result including behavioral characteristics and the simulation results are presented.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1717-1725
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• 2008

In this paper, the HILS system is proposed for the AWS ECU of the bi-modal tram. Using the HILS of the AWS ECU, the behavior of the vehicle can be predicted and the reliability of the AWS system also can be verified. The hardware part of the HILS system includes the ECUs, hydraulic systems, steering linkages and sensors of the bi-modal tram. The software part of the HILS system contains the virtual vehicle model and sensor emulation. Driver input conditions, such as vehicle velocity and front steering angle, are provided to the ECUs by the software. The driving simulation of the bi-modal tram is carried out by the HILS. Also, the reliability of the AWS system, including the ECUs and hydraulic systems, is verified.

• International Journal of Aerospace System Engineering
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• v.3 no.2
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• pp.22-25
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• 2016

This dissertation tried to analyze passenger behaviors after an accident with the possibilities of a variety of accidents open reflecting the phases of the times of increasing interests in safety of passengers as the use of means of transportation such as cars and airplanes is increasing. Because a lot of data on head-on collisions, broadside collisions and reverse side collisions have been gathered through lots of experiments and interpretations, I chose to study a relatively unfamiliar subject, dropping collision. For example, I tried to study passenger behaviors in seating position after a dropping collision in preparation for falling accidents due to recent frequently-occurring sinkholes, driver's carelessness or mechanical problems. I used MADYMO, passenger behavior interpretation program, and experimented with 2 meters high Drop Test device which I made in person to increase the reliability of the results. On the basis of these, I compared the real experiments with interpretations.

• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.103-108
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• 2004

The motivation of this study comes from the problem recognition that the headway of passing vehicle in signalized intersections can not be merely determined by departing sequence. Traffic speed and headway data of passing vehicles in signalized intersection have been obtained by using magnetic detectors(NC 97) and detecting program, and the data was analyzed. Without special treatment, the model established on passing behavior of vehicles was meaningless from statistical view point. Hence, special treatments such as filtering (upper 85% offensive driver driven vehicle's) and log scaling of data were carried on. With this new data, meaningful model (where coefficient of determination is 0.91) was established. This model explained the fact that vehicle headway in signalized intersection is affected by speed and headway of previous vehicle and speed of itself.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.7-19
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• 2011

Using 2006 metropolitan household travel survey data, this study analyzes trip behaviors based on a concept of trip chains using both trip purpose and number of trip linkages. For the analysis, trip chains are classified into two groups depending on including commute trips. Each group is further classified into a single linkage (i.e., Origin-Destination trips without any intermediate stop-by) and multiple linkages (Origin-Destination trip with at least one intermediate stop-by). The analysis is conducted using the two-step Nested Logit Model. Computational results identifying the characteristics of single and multiple linkages show that the young, male and office employee drivers tend to have more multiple linkages than single linkages in their trips. In contrast, it is shown that a driver whose monthly income is less than 3,000,000 Korean Won with a longer commute time more likely to make a trip chain with single linkages (p<0.0001).

• Journal of Korean Society of Transportation
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• v.29 no.5
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• pp.107-120
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• 2011

Traffic signal is one of the major factors that affect the amount of vehicle emissions on urban highway. The amount of vehicle emissions in urban area is highly affected by the vehicle's cruising speeds heavily influenced by the traffic signal lighting conditions. It was attempted in this study to trace the changing patterns of the vehicle emissions by collecting the emission data from a set of simulation studies and by categorizing vehicle cruising conditions into four different groups: idling, acceleration, deceleration, and running at a constant speed. Authors propose a simple emission model prepared based on Kinematic theory. The validation test results showed that the amount of the emission estimated by the proposed model was relatively satisfactory compared to the one of the existing model employing the average speed data only as the determinant.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.101-113
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• 2008

VMS are installed in many Korean highways in oder to give drivers informations such as travel time to destination, congestion and Incident situation. However, some guidelines for install VMS are restricted in only geometric factors although human factors considering driver behavior are very important to affect the VMS installation. Therefore, this paper are focusing on developing and verifying the discriminant model for VMS installation considering human factors. As a result, following outputs are obtained ; (1) developing the discriminant model using human factors of driving simulation experiments in oder to predict driver reading VMS messages safely detour highway. (2) proving that driving experiences in highway, personal driving history, vehicle speed orderly affects VMS installation (3) verifying predictability of developed model by comparing the real values with predicted values. (4) suggesting that VMS should be installed off 3.2Km from the I.C. of rural highway.