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IN-DEPTH UNDERSTANDING OF LANE CHANGING INTERACTIONS FOR IN-VEHICLE DRIVING ASSISTANCE SYSTEMS
C. OH,J. CHOI,S. PARK 한국자동차공학회 2017 International journal of automotive technology Vol.18 No.2
Lane-changing events are often related with safety concern and traffic operational efficiency due to complex interactions with neighboring vehicles. In particular, lane changes in stop-and-go traffic conditions are of keen interest because these events lead to higher risk of crash occurrence caused by more frequent and abrupt vehicle acceleration and deceleration. From these perspectives, in-depth understanding of lane changes would be of keen interest in developing in-vehicle driving assistance systems. The purpose of this study is to analyze vehicle interactions using vehicle trajectories and to identify factors affecting lane changes with stop-and-go traffic conditions. This study used vehicle trajectory data obtained from a segment of the US-101 freeway in Southern California, as a part of the Next Generation Simulation (NGSIM) project. Vehicle trajectories were divided into two groups; with stop-and-go and without stop-and-go traffic conditions. Binary logistic regression (BLR), a well-known technique for dealing with the binary choice condition, was adopted to establish lane-changing decision models. Regarding lane changes without stop-and-go traffic conditions, it was identified based on the odd ratio investigation that he subject vehicle driver is more likely to pay attention to the movement of vehicles ahead, regardless of vehicle positions such as current and target lanes. On the other hand, the subject vehicle driver in stop-and-go traffic conditions is more likely to be affected by vehicles traveling on the target lane when deciding lane changes. The two BLR models are adequate for lanechanging decisions in normal and stop-and-go traffic conditions with about 80 % accuracy. A possible reason for this finding is that the subject vehicle driver has a tendency to pay greater attention to avoiding sideswipe or rear-end collision with vehicles on the target lane. These findings are expected to be used for better understanding of driver’s lane changing behavior associated with congested stop-and-go traffic conditions, and give valuable insights in developing algorithms to process sensor data in designing safer lateral maneuvering assistance systems, which include, for example, blind spot detection systems (BSDS) and lane keeping assistance systems (LKAS).
C. OH,G. CHA 한국자동차공학회 2015 International journal of automotive technology Vol.16 No.6
The characteristics of particulate emission, in relation to factors such as fuel, injection type, after-treatment system and test cycle, were investigated. Five light-duty vehicles with different fuel, injection types and after-treatment systems - Compressed Natural Gas (CNG), Gasoline (Port Injection/Direct injection), and Diesel (with/without Diesel Particulate Filter (DPF)) - were tested on Federal Test Procedure (FTP) -75 and Highway Fuel Economy Test (HWFET) cycles. Particulate emissions were measured using a TSI 3090 Engine Exhaust Particle Sizer (EEPS) and Horiba Solid Particulate Counting system (SPCS). For the FTP-75 cycle, the DPF-equipped diesel vehicle showed the lowest particulate emission for the EEPS system, while CNG showed the lowest emission for the SPCS system due to the difference between the two measurement systems. However, the DPF-equipped diesel showed the least PN emission for both EEPS and SPCS method on the HWFET test cycle. Except for the DPF-equipped diesel, fuels with lighter molecular weight generated fewer particulates. Aside from fuel-type, the status of the engine was the most important factor determining particulate emission. When the engine was cold, a large number of particulates is formed regardless of engine-operating conditions. In contrast, warm engines form particulates only if the load on the engine is high enough, and the absolute magnitude is also lower than during the cold-start condition.
INFLUENCE OF OXYGENATE CONTENT ON PARTICULATE MATTER EMISSION IN GASOLINE DIRECT INJECTION ENGINE
C. OH,G. CHA 한국자동차공학회 2013 International journal of automotive technology Vol.14 No.6
The relationship between the oxygen content in gasoline and the particulate emission (particle number and weight) was investigated. In order to study the influence of the engine configuration on the particulate emission, four vehicles were tested in which the following systems were installed: Vehicle 1 was equipped with direct injection system which uses central mounted outwardly opening injectors. Vehicle 2 and 3 used direct injection with a side mounted multihole injectors and Vehicle 4 had port fuel injection system. Methyl tert-butyl ether (MTBE) was used as the oxygen booster. The oxygen content in the gasoline was varied from 1 to 3 wt%, which corresponds with an MTBE dosage from 3.55% to 16.11%. This study used fuel that contained the same octane number with a 2% oxygen content without oxygen components, and it was used as the reference fuel in order to distinguish the effect of the oxygen content increases and the octane boosts that result from the MTBE. All vehicle tests were performed on a roller type chassis dynamometer using the New European Driving Cycle (NEDC) and Federal Test Procedure-75 (FTP-75) cycle. The experiment results demonstrate that the oxygen content increases in the gasoline reduced the particulate emission in vehicles with direct injection engines. An equivalent phenomenon was observed in a vehicle with a port fuel injection engine, but its absolute particle number was much smaller than that of the gasoline direct injection engine. The amount of reduction of the particle number in the start (cold) phase of the test cycle was significant compared with the later (hot) phase engine operation. However, particulates were emitted even though the engine was fully warmed up, especially when the engine was highly loaded. Other factors such as fuel economy or other exhaust emissions were not significantly affected by the oxygen content.
( Byoung YouI Coh ),( Jin Mok Hur ),( Ho In Lee ) 한국화학공학회 1997 Korean Journal of Chemical Engineering Vol.14 No.6
One step synthesis of MIBK from acetone over Ni/CaO catalysts was studied. 10 wt% Ni/CaO catalysts were prepared by conventional impregnation method (catalyst I), and liquid phase oxidation method using NaOCl as an oxidant (catalyst L). Catalyst L showed much higher activity than catalyst I because of recovered CaO pore structure and high BET surface area. Catalyst C, prepared by coprecipitation method, showed 60 % of MIBK selectivity with a fairly high overall acetone conversion. catalysts L and C had two CO₂desorption states (α, β). Incorporated Ni enabled support precursor [Ca(CO₃)] to decompose easily into CaO and CO₂even at low temperature and generated weak CO₂desorption state (α) which was from active state.
27대 중점녹색기술의 기술산업연계구조분석을 통한 산업녹색도 지수 연구
고병열 ( Byoung Youl Coh ) 기술경영경제학회 2010 Journal of Technology Innovation Vol.18 No.2
미국특허를 대상으로 국가 27대 녹색기술의 기술산업연계구조 분석을 수행하였고, 이를 통해서 산업 녹색도 지수를 개발하였다. 산업의 녹색도 지수는 녹색기술 창출지수 및 활용지수의 합으로 규정하였으며, 산업의 녹색기술 수용도의 의미를 갖는다. 지수 분석결과, 전체특허기술에 대한 수용도가 매우 높았던 대부분의 IT 관련 산업들은 27대 녹색기술에 대한 수용도 즉, 산업 녹색도는 상대적으로 낮게 나타나는 경향을 나타내었다. 반면, 배터리, 무기화합물 등 화학 관련 산업 및 에너지 관련 산업의 경우 산업의 녹색도가 전체특허 기술 수용도 대비 월등히 증가하여, 녹색성장시대에 크게 주목받는 산업으로 나타났다. 녹색 기술에 대한 효과적인 투자전략 수립을 위해서는, 관련 산업으로의 파급효과를 측정하는 것이 매우 중요하며, 본 연구에서 제시한 산업녹색도 지수는 이에 대한 정량적이면서 활용이 용이한 대안으로 제시된다. 한편, 본 연구결과로 제시된 산업의 기술 수용지수는 녹색기술 분야에 한정되지 않고 타 기술분야를 대상으로도 범용적으로 활용할 수 있다. This study relates to measure impact of green technology on industry sector by uses of industry greening indices. For this study, we performed patent trend analysis, technology-industry concordance analysis, and designed some industry greening indices. Through the results of this research, we found out the impact of Korean high priority green technologies on respective industries, and consequently identified which industries play an important role in the era of green innovation. IT related industries would catch somewhat weak attention in green technology policy, though they manufacture and use plenty of patents at present. Meanwhile, Energy related industry, such as battery industry would catch strong attention in green innovation, showed very high value of industry greening indices. In order to design proper R&D strategy for green technologies, understanding industry and market structure that can adapt and promote green technology innovation is important. In this context, this study could be an effective and systematic tool for assisting green innovation policy. Also, these indices developed are not limited to the case of green technology, other technologies can be used universally as a input for analysis.