• Journal of the Korean Society of Safety
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• v.28 no.1
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• pp.63-73
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• 2013

Dynamic strain history curve measured in the field is influenced by various factors such as vehicle type, speed, noise, temperature and running location etc.. Because such curve is used for vehicle weight estimation methodology suggested by Moses, exact strain history curve is the most important thing for exact estimation of vehicle weight. In this paper, effect of such factors mentioned above is investigated on the measured strain history curves, and results of weight estimation of vehicles are discussed quantitatively. From this study, it was known that temperature effect contained in the strain history curve measured for long time in-site gives the biggest effect on result of weight estimation and it can be removed by using the mode value. Furthermore, gross vehicle weight can be estimated within 5% error corresponding to A class of the European classification if effects of temperature and noise are removed and vehicle properties such as speed, axle arrangement and running location are considered properly.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1153-1166
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• 2011

Detecting misbehavior in vehicular ad-hoc networks is very important problem with wide range of implications including safety related and congestion avoidance applications. Most misbehavior detection schemes are concerned with detection of malicious nodes. In most situations, vehicles would send wrong information because of selfish reasons of their owners. Because of rational behavior, it is more important to detect false information than to identify misbehaving nodes. In this paper, we propose the variable precision rough sets based misbehavior detection scheme which detects false alert message and misbehaving nodes by observing their action after sending out the alert messages. In the proposed scheme, the alert information system, alert profile is constructed from valid actions of moving nodes in vehicular ad-hoc networks. Once a moving vehicle receives an alert message from another vehicle, it finds out the alert type from the alert message. When the vehicle later receives a beacon from alert raised vehicle after an elapse of time, then it computes the relative classification error by using variable precision rough sets from the alert information system. If the relative classification error is lager than the maximum allowable relative classification error of the alert type, the vehicle decides the message as false alert message. Th performance of the proposed scheme is evaluated as two metrics: correct ratio and incorrect ratio through a simulation.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.7-16
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• 2008

There are unique aspects of truck vehicle movements compared with the personal travel in trip chaining. This paper reports an analysis on the truck vehicle trip chaining which intercity/metropolitan/intraregional trips are classified. Data collected from the travel dairy survey is used the truck trip-chaining analysis. The pattern of trip chaining classes is classified by the GIS mapping based on orgin-destination trip information. The physical index and efficiency index for each trip diary is used to the truck vehicle activity. Truck trips lengths and time differs from its truck type, service type and travel patterns. It is shown that the efficiency of the truck trip chaining depends on vehicle types and its delivery patterns. There are many other topics for research on trip chaining modeling such as the classification of trip chain, time use and mode choice by trip chaining.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.4
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• pp.52-61
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• 2015

PCE(Passenger Car Equivalents) is used to analysis of road capacity and LOS(Level of Service). In this study calculates PCE by number of lane and 12 vehicle type by MOLIT(Minister of Land, Infra Structure and Transport) using individual vehicle data. The results of the calculation, PCEs are increased when high vehicle classification level, many number of lanes and weekend. Heavy vehicle factors are smaller than KHCM on 4, 6 lane. Also, In this study estimates of PCE variation model by heavy vehicle percentage. Impact of Heavy vehicles on PCEs is the most sensitive on 2 lane. The results of the study, heavy vehicles low impact on PCE on multi-lane and business trips are a little in weekend.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.4
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• pp.487-494
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• 2016

In order to comply with the Federal Motor Vehicle Safety Standard(FMVSS) No. 208 that has been in force since September 2003, an automatic airbag suppression system has become an essential option for detecting and protecting infants and children seated in the front passenger seat of vehicles in the U.S. market. MOBIS has developed the world's first weight-based OCS under the name NWCS. NWCS is composed of two sensors and ECU. It is sub-packaged in order to minimize the seat structure deviation. In this paper, technical features, robustness and performance of NWCS are summarized and discussed.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.61-64
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• 2024

As research on autonomous driving technology becomes more active, various studies on signal recognition of traffic lights are also being conducted. When recognizing traffic lights with different purposes and shapes, such as pedestrian traffic lights, vehicle-only traffic lights, and right-turn traffic lights, existing classification methods may cause misrecognition problems. Therefore, in this study, we studied a model that allows accurate signal recognition by subdividing the classification of signals according to the purpose and type of traffic lights. A signal recognition model was created by classifying traffic lights according to their shape and purpose into horizontal, vertical, right turn, etc., and by comparing them with the existing signal recognition model based on YOLOv5, it was confirmed that more correct and accurate recognition was possible.

• Fashion & Textile Research Journal
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• v.1 no.3
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• pp.246-251
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• 1999

Headdress which adorns the head has been used not only as a type of dress but also as a vehicle to express the human's mentality and a tool to convey ideas. This study first examines the type of headdress observed in the world folk costumes and investigates their geographical distribution and aims to examine how the types of headdress are inter-related to the peoples' natural environments, way of life and cultural background such as religion and aesthetic, ethical standards. Headdress used as important elements of many peoples' folk costumes can be categorized into scarf-type, hat-type and adornment-type. Veil-type, the one of scarf-types, was developed in Southwestern Asia and Arabic Africa influenced by natural and religious factors. This type is more simplified in Turkey and Eastern Europe and only covers head and neck in the former and only head in the latter while also being called 'headkerchief-type'. Hat-type is observed in many different parts of the world. Adornment-type has been used to symbolized one's noble social status and authority in societies dominated by shamanistic cultural background; it was also used in Far East out of the motivation to fulfil one's aesthetic desire. Headdress though it was originally made from the idential purpose of wearing, has developed into the various types affected by each people's natural environments, emotion and ways of life.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.210-216
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• 2015

This paper proposes a method to determine vehicle driving state using the driving characteristics index. This index is a quantitative value to classify the driving state of a vehicle with its velocity and heading angle in that instant. It can classify driving state into straight driving, lane changing driving and curve driving in real time. In addition, the number of positional information is movably set up by designed region of interest. The proposed index is expressed on the stable driving states. Each driving state has characteristic tendency, and is compared with index distributional areas. The proposed method is verified by the actual driving experiment on the KATECH proving ground.

• Proceedings of the KSR Conference
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• 2002.10b
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• pp.1035-1040
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• 2002

Railway plate girder bridges have characteristics that are not show dominant frequency in dynamic response frequencies like obtained vertical acceleration on the bridge during the train passing because the train loading relatively bigger than the bridge self-weight. This paper experimentally confirmed in FFT result has various frequencies due to inherent characteristic of railway train loading. To establish classification of dynamic frequency range in railway bridge acceleration during the train passing, vibration frequencies result from experimental test are analyzed concerning actuation vibration factors. Factors are train velocity, train type, mass ratio of vehicle/bridge, stiffness of bridge, bridge/track and vehicle/track. From the result, it is proposed that the frequencty classfication table with corresponding factors. Using the proposed table to develop rehabilitation technique of the plate girder bridge, to expect vibration reduction and comfort enhancement of the railway plate girder bridge.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.313-316
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• 2022

In this paper, we implement a system that detects abnormalities in the charging data transmitted from the charger during the charging process of electric vehicles and controls them remotely. Using classification algorithms such as logistic regression, KNN, SVM, and decision trees, to do this, an analysis model is created that judges the data received from the charger as normal and abnormal. In addition, a model is created to determine the cause of the abnormality using the existing charging data based on the analysis of the type of charger abnormality. Finally, it is solved using unsupervised learning method to find new patterns of abnormal data.