• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.6
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• pp.91-96
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• 2008

As a remarkable reduction of the vehicle noise, the important of tire noise which is generated from the vehicle and the necessity of the research for the noise reduction is being emphasized. In this study, the road noise which is excited by the interaction between tire and road has been studied. The subjective test(feeling test) according to SAE J1060 rating scale is applied to the evaluation of the road noise. The combination of the several tires and vehicles are made to consider the effect of the vehicle suspension and the tire structure for road noise. The vehicles with 3-different suspension system are applied to road noise test and the eight kinds of tires are selected. As the results, the effects of the vehicle suspension and tire structure which affects on road noise are investigated.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.389-395
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• 2022

In order to ensure reliability the high-level automated driving such as Advanced Driver Assistance System (ADAS) and universal robot taxi provided by autonomous driving systems, the operation with high integrity must be generated within the defined Operation Design Domain (ODD). For this, the position and posture accuracy requirements of autonomous driving systems based on the safety driving requirements for autonomous vehicles and domestic road geometry standard are necessarily demanded. This paper presents localization requirements for safe road driving of autonomous ground vehicles based on the requirements of the positioning system installed on autonomous vehicle systems, the domestic road geometry standard and the dimensions of the vehicle to be designed. Based on this, 4 Protection Levels (PLs) such as longitudinal, lateral, vertical PLs, and attitude PL are calculated. The calculated results reveal that the PLs are more strict to urban roads than highways. The defined requirements can be used as a basis for guaranteeing the minimum reliability of the designed autonomous driving system on roads.

• Wind and Structures
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• v.31 no.5
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• pp.393-402
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• 2020

Long-span bridges with high flexibility and low structural damping are very susceptible to the vortex-induced vibration (VIV), which causes extremely negative impacts on the ride comfort of vehicles running on the bridges. To assess the ride comfort of vehicles running on the long-span bridges subjected to VIV, a coupled wind-vehicle-bridge system applicable to the VIV case is firstly developed in this paper. In this system, the equations of motion of the vehicles and the bridge subjected to VIV are established and coupled through the vehicle-bridge interaction. Based on the dynamic responses of the vehicles obtained by solving the coupled system, the ride comfort of the vehicles can be evaluated using the method given in ISO 2631-1. At last, the proposed framework is applied to several case studies, where a long-span suspension bridge and two types of vehicles are taken into account. The effects of vehicle speed, vehicle type, road roughness and vehicle number on the ride comfort are investigated.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.244-257
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• 2017

Traffic congestion occurs from drivers' human factors such as driver reaction time, reckless lane change, and inexperienced driving. When Automated Vehicles are introduced, human factors are excluded, resulting in increased average vehicle speed, stabilizing traffic flow, and increasing road capacity. This study analyzed traffic flow changes through traffic volume-speed-density plots, and increased road capacity due to Automated Vehicles. As a result of the analysis, when rate of automated vehicles gests higher, the traffic flow became stable. Additionally, it was analyzed that when all vehicles were automated, the road capacity increased by about 120 %. It is expected that there will be a positive expectation in terms of traffic congestion and traffic demand management due to the introduction of Automated Vehicles.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.47-54
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• 2022

For safe driving of autonomous vehicles, road damage detection is very important to lower the potential risk. In order to ensure safety while an autonomous vehicle is driving on the road, technology that can cope with various obstacles is required. Among them, technology that recognizes static obstacles such as poor road conditions as well as dynamic obstacles that may be encountered while driving, such as crosswalks, manholes, hollows, and speed bumps, is a priority. In this paper, we propose a method to extract similarity of images and find damaged road images using OpenCV image processing and CNN algorithm. To implement this, we trained a CNN model using 280 training datasheets and 70 test datasheets out of 350 image data. As a result of training, the object recognition processing speed and recognition speed of 100 images were tested, and the average processing speed was 45.9 ms, the average recognition speed was 66.78 ms, and the average object accuracy was 92%. In the future, it is expected that the driving safety of autonomous vehicles will be improved by using technology that detects road obstacles encountered while driving.

• Journal of KSNVE
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• v.9 no.1
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• pp.25-32
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• 1999

Ground vibrations induced from road were investigated to get the basic data that can be used to prepare countermeasures for environmental vibration problems. Vibration levels were measured simultaneously at three points in double distances from road. These data were analyzed with the type of vehicles. roads, media to understand the magnitudes and characteristics of distance attenuation of road vibrations. Vibration levels recorded on tapes were analyzed to understand the characteristics of frequency of road vibration. The range which could be influenced by the road vibration was estimated to take into account the mean of$L_{max}$ and distance attenuation of vibration level 5 m from roadside.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2000.11a
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• pp.136-138
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• 2000

The vehicle emissions of primary air pollutants are described by the emission factor (EF), defined as the emitted mass (g) of a compound per distance (km) and vehicle. The EF can be determined by exhaust measurements from single vehicles in dynamometric tests. However, the EF of a large number of vehicles has to be measured to obtain the representative results for actual road traffic emissions. Road traffic emissions can also be determined by exhaust measurements of driving vehicles or in tunnel measurements. (omitted)

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1836-1842
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• 2015

On road networks, the clustering of moving objects is important for traffic monitoring and routes recommendation. The existing schemes find out density route by considering the number of vehicles in a road segment. Since they don’t consider the features of each road segment such as width, length, and directions in a road network, the results are not correct in some real road networks. To overcome such problems, we propose a clustering method for congested routes discovering from the trajectories of moving objects on road networks. The proposed scheme can be divided into three steps. First, it divides each road network into segments with different width, length, and directions. Second, the congested road segments are detected through analyzing the trajectories of moving objects on the road network. The saturation degree of each road segment and the average moving speed of vehicles in a road segment are computed to detect the congested road segments. Finally, we compute the final congested routes by using a clustering scheme. The experimental results showed that the proposed scheme can efficiently discover the congested routes in different directions of the roads.

• Journal of the Korea Society of Computer and Information
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• v.8 no.2
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• pp.37-43
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• 2003

The purpose of this thesis is to detect multiple vehicles using sequence image analysis at process that detect forward vehicles and lane from sequential color images. Detection of vehicles candidate area uses shadow characteristic and edge information in one frame. And, method to detect multiple vehicles area analyzes Estimation of Vehicle(EOV) and Accumulated Similarity Function(ASF) of vehicles candidate areas that exist in sequential images and examine possibility to be vehicles. Most researches detected a forward vehicles in road images but this research presented method to detect several vehicles and apply enough in havy traffic. To verify the effects of the proposed method, we capture the road images with notebook and CCD camera for PC and present the results such as processing time, accuracy and vehicles detection in the images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.620-623
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• 2014

Network topology for communication between vehicles are quickly changing because vehicles have a special movement pattern, especially character which is quickly changed by velocity and situation of road. Because of these feature, it is not easy to apply reliable routing on VANET(Vehicular Ad-hoc Network). Clustering method is one of the alternatives which are suggested for overcoming weakness of routing algorithm. Clustering is the way to communicate and manage vehicles by binding them around cluster head. Therefore choosing certain cluster head among vehicles has a decisive effect on decreasing overhead in relevant clustering and determining stability and efficiency of the network. This paper introduces new cluster head selection algorithm using RSU(Road Side Unit) different from existing algorithms. We suggest a more stable and efficient algorithm which decides a priority of cluster head by calculating vehicles' velocity and distance through RSU than existing algorithms.