• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.1
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• pp.105-114
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• 2016

With approximately 20 million transportation card data entries of the metropolitan districts being generated per day, application of the data to management and policy interventions is becoming an issue of interest. The research herein attempts a model of the possibility of dynamic demand change predictions and its purpose is thereby to construct a Dynamic Passengers Trip Assignment Model. The model and algorithm created are targeted at city rail lines operated by seven different transport facilities with the exclusion of travel by bus, as passenger movements by this mode can be minutely disaggregated through card tagging. The model created has been constructed in continuous time as is fitting to the big data characteristic of transport card data, while passenger path choice behavior is effectively represented using a perception parameter as a function of increasing number of transfers. Running the model on 800 pairs of metropolitan city rail data has proven its capability in determining dynamic demand at any moment in time, in line with the typical advantages expected of a continuous time-based model. Comparison against data measured by the eye of existing rail operating facilities to assess changes in congestion intensity shows that the model closely approximates the values and trends of the existing data with high levels of confidence. Future research efforts should be directed toward continued examination into construction of an integrated bus-city rail system model.

• Journal of Computational Design and Engineering
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• v.1 no.4
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• pp.233-242
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• 2014

A magnetically levitated vehicle (Maglev) system is under commercialization as a new transportation system in Korea. The Maglev is operated by an unmanned automatic control system. Therefore, the plan of train operation should be carefully established and validated in advance. In general, when making a train operation plan, statistically predicted traffic data is used. However, a traffic wave often occurs in real train service, and demand-driven simulation technology is required to review a train operation plan and service quality considering traffic waves. We propose a method and model to simulate Maglev operation considering continuous demand changes. For this purpose, we employed a discrete event model that is suitable for modeling the behavior of railway passenger transportation. We modeled the system hierarchically using discrete event system specification (DEVS) formalism. In addition, through implementation and an experiment using the DEVSim++ simulation environment, we tested the feasibility of the proposed model. Our experimental results also verified that our demand-driven simulation technology can be used for a priori review of train operation plans and strategies.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.230-239
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• 1999

A virtual prototyping seeks to virtual environment where the development of vehicle models can be flecible as well as rapid and the experiments can be executed effectively concerning kinematics, controls, and behavior aspects of the models. This paper explains a virtual environment used for virtual prototyping of a vehicle. Ut has been developed using the dVISE environment thar provides actions, events, sounds, and light features. A vehicle model including detailed informations about a real-size vehicle. A human model is introduced for odjective visual evaluations of the developed, and then results are illustrated in order to demonstrate the applicability of developed models.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.613-616
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• 2012

A multi body simulation (MBS) model is developed for predicting the impact harshness of the vehicle. Impact harshness is the vehicle performance to evaluate the impulsive vibration behavior during driving over an obstacle of the road. Thus, the approach is simulated on the time domain for considering the transient behavior of the vehicle. The validity of vehicle component modeling of bushes, dampers and structure flexibilities is verified. The simulations are compared with the test results in both of vertical and longitudinal directions. In particular, the vertical vibration of the vehicle is significantly affected by the body flexibility. Through the sensitivity analysis, main factors for the impact harshness performance are investigated.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.31-37
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• 2018

Recently, the safety in vehicle also has become a hot topic as self-driving car is developed. In passive safety systems such as airbags and seat belts, the system is being changed into an active system that actively grasps the status and behavior of the passengers including the driver to mitigate the risk. Furthermore, it is expected that it will be possible to provide customized services such as seat deformation, air conditioning operation and D.W.D (Distraction While Driving) warning suitable for the passenger by using occupant information. In this paper, we propose robust vehicle occupant detection algorithm based on RGB-Depth-Thermal camera for obtaining the passengers information. The RGB-Depth-Thermal camera sensor system was configured to be robust against various environment. Also, one of the deep learning algorithms, OpenPose, was used for occupant detection. This algorithm is advantageous not only for RGB image but also for thermal image even using existing learned model. The algorithm will be supplemented to acquire high level information such as passenger attitude detection and face recognition mentioned in the introduction and provide customized active convenience service.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.173-182
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• 2021

In this paper, we analyzed driver's and passenger's motions that cause driver's distraction, and recognized 10 driver's behaviors related to mobile phones. First, distraction-inducing behaviors were classified into environments and factors, and related recent papers were analyzed. Based on the analyzed papers, 10 driver's behaviors related to cell phones, which are the main causes of distraction, were recognized. The experiment was conducted based on about 100,000 image data. Features were extracted through SURF and tested with three models (CNN, ResNet-101, and improved ResNet-101). The improved ResNet-101 model reduced training and validation errors by 8.2 times and 44.6 times compared to CNN, and the average precision and f1-score were maintained at a high level of 0.98. In addition, using CAM (class activation maps), it was reviewed whether the deep learning model used the cell phone object and location as the decisive cause when judging the driver's distraction behavior.

• Tribology and Lubricants
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• v.18 no.6
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• pp.384-388
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• 2002

The adequate design of a passenger car braking system, which is directly related to the safety of a car, is very important since the safety is an essential design parameter of a car to keep men and car from the damage. The thermal behaviors of the ventilated disk has been investigated based on the air cooling effects during repeat braking operations. In this study, the thermal behavior of ventilated disk brake system was investigated by numerical method. The 3-Dimensional unsteady model was simulated by using a general purpose software package “FLUENT” to obtain the temperature distributions of disk and pad. The model includes the more realistic braking method, which repeats braking and release. The effects of aspect ratio of ventilated hole on the heat dissipation was investigated.

• IE interfaces
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• v.17 no.1
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• pp.22-32
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• 2004

The most complicated and difficult area in the simulation of evacuation process is the area of human behavior. However, it is generally very difficult to understand and quantify human behaviors since the factors involved vary significantly according to the types of accidents and the environment. The walking speed of passenger is especially affected by dynamic effect and list due to damage and ship motion in wave. There are various methods to get the useful data for evacuation simulation. The onboard experimental approach is one of the strongest method. This paper discusses the onboard experimental results of human mobility of passengers in evacuation from ship. To realize ship trim and heel due to maritime casuality, the passage model for experiment is made. The experiment was carried out at dynamic and static condition respectively using the ship with passage model. The result was evaluated and it will be reflected in evacuation simulation tool.

• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.57-66
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• 2003

Because the Logit model easily calculates probabilities for choice alternatives and estimates parameters for explanatory variables, it is widely used as a traffic mode choice model. However, this model includes an assumption which is independently and identically distributed to the error component distribution of the mode choice utility function. This paper is a study on the estimation of the Heteroscedastic Logit Model. which mitigates this assumption. The purpose of this paper is to estimate a Logit model that more accurately reflects the mode choice behavior of passengers by resolving the homoscedasticity of the model choice utility error component. In order to do this, we introduced a scale factor that is directly related to the error component distribution of the model. This scale factor was defined so as to take into account the heteroscedasticity in the difference in travel time between using public transport and driving a car, and was used to estimate the travel time parameter. The results of the Logit Model estimation developed in this study show that Heteroscedastic Logit Models can realistically reflect the mode choice behavior of passengers, even if the difference in travel time between public and private transport remains the same as passenger travel time increases, by identifying the difference in mode choice probability of passengers for public transportation.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.183-192
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• 2012

This study analyzes the travel behavior for short-term demand forecasting model of KTX. This research suggests the following. First, the outlier criteria is considered to appropriate twice the standard deviation of the traffic. Second, the result of a homogeneity test using ANOVA analysis has been divided into weekdays(Mon Thu and weekends(Fri Sun). Third, a cluster analysis for O/D pairs using trip frequency, traffic averages and th distance between stations was performed.