• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.17-28
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• 2011

This study proposed a speed management strategy for the enhancement of traffic safety on freeways. A novel feature of the proposed strategy is to provide desirable speed information to individual vehicles. A microscopic traffic simulator, VISSIM, was used for the performance evaluation. Vehicle trajectory data were used to evaluate the various speed management scenarios including the different levels of proportions of heavy vehicles. The proposed speed management strategy would be a useful precursor for developing an effective traffic control and operations system to prevent traffic accidents on freeways.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.3
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• pp.193-198
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• 2016

Lane change is an important issue in microscopic traffic flow simulations and active safety. Overtaking and changing lanes are dangerous driving maneuvers. This approach presents a lane-changing system based on speed and a minimum gap between vehicles in a vehicular ad hoc network (VANET). This paper proposes a solution to ensure the safety of drivers while changing lanes on highways. Efficient routing protocols could play a crucial role in VANET applications, safeguarding both drivers and passengers, and thus, maintaining a safe on-road environment. This paper focuses on the development of an intelligent transportation system that provides timely, reliable information to drivers and the concerned authorities. A test bed is created for the techniques used in the proposed system, where analysis takes place in an on-board embedded system designed for vehicle navigation. The designed system was tested on a four-lane road in Neemrana, India. Successful simulations were conducted with real-time network parameters to maximize quality of service and performance using Simulation of Urban Mobility and Network Simulator 2 (NS-2). The system implementation, together with the findings, is presented in this paper. Illustrating the approach are results from simulation using NS-2.

• Environmental and Resource Economics Review
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• v.26 no.2
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• pp.173-203
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• 2017

The existence of rebound effect from road extension in Korea has been quantitatively verified using cross-sectional, time series data on four major cities - Seoul, Busan, Daegue and Incheon - between 2000 and 2013. The linear mixed effects model was constructed from six variables: total vehicle miles traveled (VMT), road extension, public transport users, gross regional domestic product (GRDP), regional population and fuel consumption. The main results can be summarized as VMT is positively correlated to road extension while negatively with public transport users. It indicates that the road extension-centered "supply-side" transportation policy induces "additional travel" and create "generated traffic" by enhancing driving efficiencies directly, or degrading other transport modes indirectly. Hence, the ultimate goal of road congestion reduction requires public transport-centered "demand management" rather than current supply-side policies.

• Journal of IKEEE
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• v.22 no.1
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• pp.46-52
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• 2018

The problem of traffic light detection and recognition has recently become one of the most important topics in various researches on autonomous driving. Most algorithms are based on colors to detect and recognize traffic light signals. These methods have disadvantage in that the recognition rate is lowered due to the change of the color of the traffic light, the influence of the angle, distance, and surrounding illumination environment of the image. In this paper, we propose machine learning based detection and recognition algorithm using shape information to solve these problems. Unlike the existing algorithms, the proposed algorithm detects and recognizes the traffic signals based on the morphological characteristics of the traffic lights, which is advantageous in that it is robust against the influence from the surrounding environments. Experimental results show that the recognition rate of the signal is higher than those of other color-based algorithms.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.4
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• pp.351-358
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• 2015

In the recent times, the use of gasoline direct injection (GDI) engines has been regarded as a means of enhancing conformance to emission regulations and improving fuel efficiency. GDI engines have been widely adopted in the recent years for their better engine performance and fuel economy compared to those of conventional MPI gasoline engines. However, they present some disadvantages related to the mass and quantity of particulate matter generated during their use. This study investigated the nanoparticle characteristics of the particulate matter exhausted from a GDI engine vehicle installed with different types of gasoline particulate filters, after subjecting it to ultra-lean burn driving conditions. Three metal foam and metal fiber filters were used for each experimental condition. The number concentrations of particles were analyzed for understanding their behavior, and the reduction characteristics were obtained for each type of filter.

• Journal of Drive and Control
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• v.17 no.1
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• pp.27-36
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• 2020

The aim of this study is to design a simulation model for an electric All-Wheel-Drive (AWD) tractor to evaluate the performance of the selected component and agricultural work ability. The electric AWD tractor consists of four motors independently for each drive wheel, and each motor is combined with an engine generator, a battery pack, and reducers. The torque data of a 78 kW-class tractor was measured during plow tillage and driving operation to develop a workload cycle. A simulation model was developed by using commercial software, Simulation X, and it used the workload as the simulation condition. As a result of simulation analysis, the drive system, including an electric motor and reducers, was able to cope with high load during plow tillage. The SOC (State of Charge) level was influenced by the output power of the motor, and it was maintained in the range of 50~80%. The fuel consumed by the engine was about 18.23 L during working on a total of 8 fields. The electric AWD tractor was able to perform agricultural work for about 7 hours. In the future study, the electric AWD tractor will be developed reflecting the simulation condition. Research on the comparison between the simulation model and the electric AWD tractor should be performed.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.6
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• pp.46-51
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• 2012

Fuel Cell Hybrid Vehicles (FCHVs) have become a major topic of interest in the automotive industry owing to recent energy supply and environmental problems. Several types of power management strategies have been developed to improve the fuel economy of FCHVs including optimal control strategy based on optimal control theory, rule-based strategy, and equivalent consumption minimization strategy (ECMS). The ECMS is applied in this study. This strategy is based on the heuristic concept that the usage of the electric energy can be exchanged to equivalent fuel consumption. This strategy is known as one of the promising solutions for real-time control of hybrid vehicles. The ECMS for an FCHV is introduced in this paper as well as the equivalent fuel consumption parameter. The relationship between the battery final state of charge (SOC) and the fuel consumption while changing the equivalent fuel consumption parameter is obtained for three different driving cycles. The function of the equivalent fuel consumption parameter is also discussed.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.1
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• pp.95-105
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• 2012

The selective catalytic reduction (SCR) system is a highly-effective aftertreatment device for NOx reduction of diesel engines. Generally, the ammonia ($NH_3$) was generated from reaction mechanism of SCR in the SCR system using the liquid urea as the reluctant. Therefore, the precise urea dosing control is a very important key for NOx and $NH_3$ slip reduction in the SCR system. This paper investigated NOx and $NH_3$ emission characteristics of urea-SCR dosing system based on model-based control algorithm in order to reduce NOx. In the map-based control algorithm, target amount of urea solution was determined by mass flow rate of exhaust gas obtained from engine rpm, torque and $O_2$ for feed-back control NOx concentration should be measured by NOx sensor. Moreover, this algorithm can not estimate $NH_3$ absorbed on the catalyst. Hence, the urea injection can be too rich or too lean. In this study, the model-based control algorithm was developed and evaluated on the numerical model describing physical and chemical phenomena in SCR system. One channel thermo-fluid model coupled with finely tuned chemical reaction model was applied to this control algorithm. The vehicle test was carried out by using map-based and model-based control algorithms in the NEDC mode in order to evaluate the performance of the model based control algorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.6
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• pp.87-93
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• 2007

It is complicate to analysis the systems, dual mode hybrid systems, because they are composed of many planetary gear sets. For the performance test, it needs to define the systems with representative parameters. In this paper, system parameters, $\alpha$, $\beta$, $\zeta$, are introduced to define the systems, and an arbitrary system like E-IVT developed by Renault Motors is converted to the general system having equivalent parameters, such as $\beta'$, $R'_b$. Pontryagin principle and Kuhn-Tucker condition method are applied to solve the constrained problems, by which the methodology for accelerating test is generalized, and the results of the simulation are reported. In addition, the effects of alternative strategies are mentioned. The method of fuel economy test at engine mode is also introduced. The results of test at engine mode is different from the results of optimal trajectory, but the fuel economy of the engine mode is related to the highway driving and optimized operating of the system.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.59-70
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• 2009

This study presents a novel traffic information system which is capable of detecting unsafe traffic events leading to accident occurrence and providing warning information to drivers for safer driving. Unsafe traffic events are captured by a vehicle image processing-based detection system in real time. Surrogate safety measures (SSM) representing quantitative accident potentials were derived, and further utilized to develop a data processing algorithm and analysis techniques in the proposed system. This study also defined 'emergency warning area' and 'general warning area' for more effective provision of warning information. In addition, methodologies for determining thresholds to trigger warning information were presented. Technical issues and further studies to fully exploit the benefits of the proposed system were discussed. It is expected that the proposed system would be effective for better management of traffic flow to prevent traffic accidents on freeways.