• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.5
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• pp.1055-1067
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• 1994

This paper is presented to perform linear dynamic analysis of bridges due to vehicle moving on bridges. The road surface roughness and bridge/vehicle interaction are also considered. The bridge and vehicle are modeled as 3-D bridge and vehicle model, respectively. The road surface roughness of the roadway and bridge decks are generated from power spectral density(PSD) function for good road. The PSD function proposed by C.J. Dodds and J.D. Robson is used to describe the road surface roughness for good road condition. The vehicles are modeled as two nonlinear vehicle model with 7-D.O.F of truck and 12-D.O.F of tractor-trailer and the equations of motion of the vehicles are derived using Lagrange's equation. The main girder and concrete deck are modeled as beam and shell element, respectively and rigid link is used between main girder and concrete deck. The equations of motion of the vehicles are solved by Newmark ${\beta}$ method and the equations of the motion of the bridges are solved by mode-superposition procedures. The validity of the proposed procedure is demonstrated by comparing the results with the experimental data reported by the AASHO Road Test. The comparison shows that the agreement between experiment and theory is quite satisfactory.

• Journal of IKEEE
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• v.28 no.1
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• pp.6-13
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• 2024

This paper proposes an approach to detect abnormal data in automotive controller area network (CAN) using an unsupervised learning model, i.e. autoencoder and Gaussian kernel density estimation function. The proposed autoencoder model is trained with only message ID of CAN data frames. Afterwards, by employing the Gaussian kernel density estimation function, it effectively detects abnormal data based on the trained model characterized by the optimally determined number of frames and a loss threshold. It was verified and evaluated using four types of attack data, i.e. DoS attacks, gear spoofing attacks, RPM spoofing attacks, and fuzzy attacks. Compared with conventional unsupervised learning-based models, it has achieved over 99% detection performance across all evaluation metrics.

• Proceedings of the KIPE Conference
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• 2016.11a
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• pp.125-126
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• 2016

본 논문에서는 자율주행차량의 ISG시스템에서 비상발전용 양방향 DC-DC 컨버터 개발을 위한 최적화 연구 결과를 발표한다. 자율주행차량의 주 전력시스템이 차단되었을 때 차량을 제어하는 시스템에 전력공급이 가능한 비상발전시스템은 현재 개발되지 않은 상태이다. 자율주행차량의 비상발전시스템의 최대 전력은 약 3kW이며 main battery 전압은 48V, sub battery 전압은 12V이다. 본 연구에서는 차량의 연비를 고려한 고전력 밀도와 배터리 수명을 고려한 전류 리플 최소화를 목표로 한다. 이를 위해 차동모드 커플더 인덕터를 가진 4상 인터리브드 방식으로 설계하였고, 최대 98.22%의 효율이 예상된다.

• Journal of Advanced Navigation Technology
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• v.23 no.6
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• pp.548-553
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• 2019

Along with advanced vehicle to vehicle (V2V) communication technologies, platooning is regarded as one of the most promising form of autonomous driving solutions in order to increase road capacity. In this paper, we propose a novel V2V transmission scheme for safety message dissemination in platooning. The proposed scheme enhances the efficiency of channel access and multi-vehicle orthogonal frequency division multiple access (OFDMA) transmission by taking advantage of triggered uplink access technique and null data packet feedback report protocol introduced in the sixth generation WLAN standard, IEEE 802.11ax. The simulation results prove that the proposed scheme outperforms the conventional IEEE 802.11 transmission scheme throughout all measured vehicle density range.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.794-797
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• 2015

As the interest in VANET is increased, a study on the beacon message transmission between vehicles is actively being made. IEEE 802.11p/1609.4 standard is based on a multichannel system consisting of multiple service channels (SCH) and a control channel (CCH). Multiple SCHs are defined for nonsafety data transfer, while the CCH is used to broadcast safety messages called beacons and control messages (i.e., service advertisement messages). However, most messages broadcast in the only one CCH belong to safety application that must be contested in dense vehicular network. This paper suggests safety message transfer algorithm in dense vehicular congestion. The proposed algorithm is that the priority of safety messages is decided by decision tree and messages are stored in proper queues according to their priorities. Then, safety messages with higher priorities are sent in turn by CCH in the assigned time. The proposed algorithm decreases the beacon transmission delay and increase on the probability of a successful beacon reception in an IEEE 802.11p/1609.4-based network.

• Journal of the Korean Society for Railway
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• v.14 no.6
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• pp.526-534
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• 2011

In this study, proposed is the methodology to determine the upper limit for stiffness of rail pad for the ballasted and concrete track in high-speed railway in the viewpoint of running safety, considering the dynamic characteristics of train and track and the operation environment. For the track irregularity, one of the most important input parameters for traintrack interaction analysis, the reference vertical track irregularity PSDs(power spectral densities) for the ballasted and concrete track in a wide range of frequencies were proposed based on those presented in France and Germany and that obtained from the measured data at Kyeong-Bu 1st phase high-speed railway line. Using these reference PSD models, the input data for the vertical track irregularity data were regenerated by random generation process, and then, the wheel load reduction rates according to the stiffness of the rail pads have been calculated by the train-track interaction analysis technique. Finally, by comparing the wheel load reduction rates calculated with the derailment criteria prescribed in the Korean standards for railway vehicle safety criteria, the upper limits for the stiffness of rail pad have been proposed.

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.91-102
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• 2003

There are two goals in this paper. The one is development of existing CA(Cellular Automata) model to explain more realistic deceleration process to stop. The other is the application of the updated CA model to forecasting simulation to predict short term link travel time that takes a key rule in finding the shortest path of route guidance system of ITS. Car following theory of CA models don't makes not response to leading vehicle's velocity but gap or distance between leading vehicles and following vehicles. So a following vehicle running at free flow speed must meet steeply sudden deceleration to avoid back collision within unrealistic braking distance. To tackle above unrealistic deceleration rule, “Slow-to-stop” rule is integrated into NaSch model. For application to interrupted traffic flow, this paper applies “Slow-to-stop” rule to both normal traffic light and random traffic light. And vehicle packet method is used to simulate a large-scale network on the desktop. Generally, time series data analysis methods such as neural network, ARIMA, and Kalman filtering are used for short term link travel time prediction that is crucial to find an optimal dynamic shortest path. But those methods have time-lag problems and are hard to capture traffic flow mechanism such as spill over and spill back etc. To address above problems. the CA model built in this study is used for forecasting simulation to predict short term link travel time in Kangnam district network And it's turned out that short term prediction simulation method generates novel results, taking a crack of time lag problems and considering interrupted traffic flow mechanism.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.4
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• pp.53-58
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• 2012

The roadside unit (RSU) collects vehicle information from vehicles in the intelligent transportation system (ITS). The vehicle density on the road within the communication range of a RSU is a time varying parameter. The higher the vehicle density, the more vehicle information can be collected. Therefore, the probability of packet collision will be raised. In this paper, an adaptive transmission scheme is proposed to improve the probability of packet reception rate by changing the data rate and transmission period according to the vehicle density. The performance of IEEE 802.11p MAC protocol that is a standard for vehicular communications is evaulated in terms of the vehicle density with the ns-2,33 simulator.

• Resources Recycling
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• v.26 no.2
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• pp.66-70
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• 2017

The purpose of this research was to estimate density changes of sea sand by washing. To examine water content test, field density test, particle density test and measuring of dump regarding extracted sea sand and selling one. Measured result of mean particle density of barge and dump were $2.666g/cm^3$, $2.651g/cm^3$, respectively. Also, measured result of field density for each sea sand was $1.716g/cm^3$, $1.331g/cm^3$ on average. Converted to the volume of 1ton of each sea sand, $0.583m^3$, $0.751m^3$, respectively. Occurring to volume change approximately 28.8% on average. The mean field densities of measuring of sea sand that dump and barge were $1.398g/cm^3$ and $1.716g/cm^3$ respectively. This values indicated $0.715m^3$ and $0.583m^3$ each, when converted to the volume of sea sand 1ton. It was found that the average of 22.6% volume change occurred between the amount of sea sand and the sales volume.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.83-91
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• 2011

This paper discusses models for estimating dynamic travel times based on probability theory. The dynamic travel time models proposed in the paper are formulated assuming that the travel time of a vehicle depends on the distribution of the traffic stream condition with respect to the location along a road when the subject vehicle enters the starting point of a travel distance or with respect to the time at the starting point of a travel distance. The models also assume that the dynamic traffic flow can be represented as an exponential distribution function among other types of probability density functions.