• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.872-876
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• 2007

Road traffic noise map is effective method to save cost and time for environmental noise assessment. Generally, noise is calculated by using theoretical equation of noise prediction, and the calculated result can be influenced by various input factors. Especially, domestic vehicle classification method for traffic flow and heavy vehicle percentage is different from that of foreign countries. Thus, this can cause effect on the noise prediction results. In this study, noise prediction results by using domestic vehicle classification method are compared with those by foreign methods.

• Proceedings of the Korea Society of Design Studies Conference
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• 2004.05a
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• pp.332-333
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• 2004

• Proceedings of KOSOMES biannual meeting
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• 2004.05b
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• pp.57-60
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• 2004

In this paper, the technology road map, as a useful methodology for the planning of R&Ds in government and/or industries, is introduced Also the road map for the maritime safety technology, which is being developed in KRISO, is discussed as a framework for the planning of national R&D projects in maritime safety.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.284-288
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• 2004

Standardization strategy is considered as an important approach for the organization growth and competitiveness. Major contents of standardization are the selection of standardization area and management of standardization timing under limited resources. The developments of standardization road map and its driving strategy in construction area are important policy subjects in view of investment scale and national economy. In this paper, we aim to survey on the standardization theory and its application in construction field and suggest research direction for driving strategy of standardization road map development.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.2
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• pp.193-197
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• 2012

Road traffic noise map is effective method to save cost and time for environmental noise assessment. Generally, noise is calculated by using theoretical equation of noise prediction, and the calculated result can be influenced by various input factors. Especially, domestic vehicle classification method for traffic flow and heavy vehicle percentage is different from that of foreign countries. Thus, this can cause effect on the noise prediction results. In this study, noise prediction results by using domestic vehicle classification method are compared with those by foreign methods.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.203-208
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• 2006

The unutilized energy in urban area is commercially and environmentally worth recycling since it can be used as a good energy resource for the heating and cooling supply. Therefore, once heating and cooling demands are near the available unutilized energy resources, a high performance district heating and cooling can be realized by the network of unutilized energy technology. In relation to this circumstance, a road map of the unutilized energy technology is presented in this study.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.262-265
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• 2008

We design level 1 traffic thematic map for common data structure. Level 1 means the road that can passing cars. If public office and private company use this form, they can save amount of money from overlapping update. And widely use of traffic analysis, navigation and traffic information system. For design common data structure we compared several data structure(traffic thematic map, ITS standard node/link, Car navigation map), and generalization these characteristic data. After generalization we considered about application parts. It can use of public part(traffic analysis, road management, accident management) and private part(car navigation, map product, marketing by variable analysis) etc.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.2
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• pp.217-224
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• 2012

In general, transportation sources include both on-road vehicles and off-road equipment. Off-road vehicles have usually used diesel engines, which have the disadvantage of high NOx emission. Common rail direct injection (CRDI) and after-treatment systems have been applied to meet the exhaust gas emission regulations for diesel vehicles. In the present, agricultural machinery has satisfied the Tier 3 emission regulations by using waste gate turbocharger (WGT) and internal exhaust gas recirculation (EGR). In this paper, the combustion and emission characteristics of an EGR system applied to a 56kW off-road vehicle in non-road transient cycle (NRTC) mode have been investigated. The EGR map was made from foundation experiments determining the EGR duty for all engine operating conditions, and then this map was applied to the NRTC mode. Consequently, the NOx emission was reduced by the EGR system, and the Tier 4 interim emission regulations were satisfied by using both the EGR system and an after-treatment system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.133-139
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• 2021

Currently, the process of constructing a high-definition road map has a high proportion of manual labor, so there are limitations in construction time and cost. Research to automate map production with high-definition road maps using artificial intelligence is being actively conducted, but since the construction of training data for the map construction is also done manually, there is a need to automatically build training data. Therefore, in this study, after converting to images using point clouds acquired by a mobile mapping system, the road marking areas were extracted through image reclassification and overlap analysis using thresholds. Then, a methodology was proposed to automatically construct training data for deep learning data for the high-definition road map through the classification of the polygon types in the extracted regions. As a result of training 2,764 lane data constructed through the proposed methodology on a deep learning-based PointNet model, the training accuracy was 99.977%, and as a result of predicting the lanes of three color types using the trained model, the accuracy was 99.566%. Therefore, it was found that the methodology proposed in this study can efficiently produce training data for high-definition road maps, and it is believed that the map production process of road markings can also be automated.

• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.39-51
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• 2021

Recently, there has been much interest in practical use of standardized HD map that can effectively define roads, lanes, junctions, road signs, and road facilities in autonomous driving. Various kinds of de jure or de facto standards such as ISO 22726-1, ISO 14296, HERE HD Live map, NDS open lane model, OpenDRIVE, and NGII HD map are currently being used. However, there are lots of differences in data modeling among these standards, it makes difficult to use them together in autonomous driving. Therefore, we propose a data model conversion method to enable an efficient use of various kinds of HD map standards in autonomous driving in this study. Specifically, we propose a conversion method between the NGII HD map model, which is easily accessible in the country, and the OpenDRIVE model, which is commonly used in the autonomous driving industry. The proposed method consists of simple conversion of NGII HD map layers into OpenDRIVE objects, new OpenDRIVE objects creation corresponding to NGII HD map layers, and linear transformation of NGII HD map layers for OpenDRIVE objects creation. Finally, we converted some test data of NGII HD map into OpenDRIVE objects, and checked the conversion results through Carla simulator. We expect that the proposed method will greatly contribute to improving the use of NGII HD map in autonomous driving.