• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.5
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• pp.777-781
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• 2012

In this paper, an electrical power simulation program was developed to predict the energy consumption of the electrical railway propulsion system, which considered the actual operating conditions of the electric railway vehicles. The developed program was designed to predictable the energy consumption during a virtual driving in the actual route of the virtual railway vehicles equipped with a propulsion system consisting of power conversion equipments and traction motors. In addition, the accuracy verification of the electrical power simulation program for a propulsion system was performed by using a real power consumption data, which was measured during the driving of the railway vehicles in the Gyeongui Line. In conclusion, the electrical power simulation program for a propulsion system was validated throughout a comparative investigation between the simulated values and the experimental values and the energy consumption characteristics of electric railway vehicles on the existing route or the new route will be possible to predict throughout the virtual simulation considering the driving conditions of the electric railway vehicles.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1990-1994
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• 2008

In this paper, we present a usable method of driving path in automatic guidance vehicle(AGV). The AGV is precisely driving to follow reference route. The Phileas in Netherland and Bi-modal tram in Korea have one wheel for the each side because of all wheels steering. For this reason, the loading area of wheels is very small. It is a disadvantage for asphalt load. The precise route tracking of vehicle can distort the flexible asphalt load. In this paper, we propose a driving method for alleviation of distortion on asphalt load.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.150-157
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• 2016

In this paper, a control system for E-bike based on IOT was developed, which collects and monitors information of states of E-bike and surrounding environments from several sensors and control devices in E-bike, and informs the possible dangers to rider when riding the E-bike. Developed electronic control system can manage battery efficiently, obtain battery's remaining power in real-time and provide possible riding distance to rider. It makes possible for rider to schedule near optimal riding route in terms of battery usage and respond quickly to battery discharge. Results of applying developed system to E-bike show that according to driving-mode, possible driving distance can be calculated efficiently and using user application App, real-time driver position marking and driving route searching functions lead to energy efficient E-bike driving. Later we will endeavor to integrate BMS, ECU, smart-phone and PC(server) to provide stable driving system based on various driving information of E-bike.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.164-172
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• 2019

In this paper, we implement a wheeled mobile robot that accurately and autonomously finds the optimal route from the starting point to the destination point based on computer vision in a complex indoor environment. We get a number of waypoints from the starting point to get the best route to the target through deep reinforcement learning. However, in the case of autonomous driving, the majority of cases do not reach their destination accurately due to external factors such as surface curvature and foreign objects. Therefore, we propose an algorithm to deepen the waypoints and destinations included in the planned route and then correct the route through the waypoint recognition while driving to reach the planned destination. We built an autonomous wheeled mobile robot controlled by Arduino and equipped with Raspberry Pi and Pycamera and tested the planned route in the indoor environment using the proposed algorithm through real-time linkage with the server in the OSX environment.

• Journal of Korean Society of Transportation
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• v.28 no.6
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• pp.147-158
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• 2010

Studies on the distribution of traffic demands have been proceeding by providing traffic information for reducing greenhouse gases and reinforcing the road's competitiveness in the transport section, however, since it is preferentially required the extensive studies on the driver's behavior changing routes and its influence factors, this study has been developed a discriminant model for changing routes considering driving conditions including traffic conditions of roads and driver's preferences for information media. It is divided into three groups depending on driving conditions in group classification with the CART analysis, which is statistically meaningful. And, elements of the driving conditions and the preferred media affecting the change of paths are classified into statistical meaningful groups through the CHAID analysis, and the major factors affecting the change of paths are examined. Finally, the extent that driving conditions and preferred media affect a route change is examined through a discriminant analysis, and it is developed a discriminant model equation to predict a route change. As a result of building the discriminant model equation, it is shown that driving conditions affect a route change much more, the entire discriminant hit ratio is derived as 64.2%, and this discriminant equation shows high discriminant ability more than a certain degree.

• Journal of Drive and Control
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• v.20 no.1
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• pp.8-15
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• 2023

With the recent trend of intelligence and automation of construction work, a double-blade road cutter is being developed that automatically enables cutting along the cutting line marked on the road using a vision system. The road cutter can recognize the cutting line through the camera and correct the driving route in real-time, and it detects the load of the cutting blade in real-time to control the driving speed in case of overload to protect workers and cutting blades. In this study, a vision system mounted on a double-blade road cutter was developed. A cutting route recognition technology was developed to stably recognize cutting lines displayed on non-uniform road surfaces, and performance was verified in similar environments. In addition, a vision sensor protection module was developed to prevent foreign substances (dust, water, etc.) generated during cutting from being attached to the camera.

• Journal of ILASS-Korea
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• v.22 no.4
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• pp.218-224
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• 2017

In order to improve the quality of air in urban areas, the emission regulations are being strengthened by the government. The on-road test of light-duty vehicles was started with PEMS because certification test mode does not sufficiently reflect on-road conditions. Therefore, The PEMS-based test was implemented from Sep. 2017 in Europe and Korea. However, this is lack of data on various on-road patterns in Korea. The purpose of the present study has analyzed the effect of speed per acceleration and acceleration on NOx emission on-road driving. The test route consisted of urban, rural, and motorway in Seoul. This study has been conducted by Euro-6 vehicles using on SCR system with PEMS. The on-road emission characteristics were evaluated by moving averaging windows (MAW) method. In results, RDE-NOx by severe driving pattern has been 1.4 times higher than soft driving pattern NIER Route 1.

• CDE review
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• v.21 no.2
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• pp.34-38
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• 2015

In case of the big city, choosing the adequate root of which we can reach the destination can affect the driver's condition and driving time. so it is quite important to find the optimal routes for arriving the destination as considering the factors, such as driving conditions or travel time and so on. In this paper, we develop route choice model with considering driving conditions and travel time, and it can search the optimal path which make drivers reduce their fatigues using genetic algorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.1
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• pp.130-138
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• 2015

Despite of recently strengthened vehicle emission regulations, NOx emissions are not decreased in urban areas because of discrepancies between certification emission test modes and real driving conditions. Thus, researches on RDE-LDV (Real-driving Emission-Light-duty Vehicle) have been conducted actively using PEMS (Portable Emissions Measurement Systems). In the present study, NOx emissions were measured for 5 Korean light duty vehicles for real driving conditions including city, combined, highway, and up-downhill test route. Emission characteristics were analyzed for averaged NOx emissions per unit driving distance of each driving test routes. Furthermore, MAW (Moving Average Window) method based on $CO_2$ emissions from WLTC, which will be supported for EU regulations, was utilized. It was revealed that DRs (deviation ratios) for diesel vehicles (i.e., 5.1 ~ 8.4) were greater than gasoline vehicles (less than 0.15). Especially DR of diesel vehicle for up-downhill test route was 8.4, which indicates severe NOx emissions.

• The Journal of Information Technology and Database
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• v.7 no.1
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• pp.42-53
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• 2000

The major goal of this research is to develop an optimal route search algorithm for an intelligent route guidance system, one sub-area of ITS. ITS stands for intelligent Transportation System. ITS offers a fundamental solution to various issues concerning transportation and it will eventually help comfortable and swift moves of drivers by receiving and transmitting information on humans, roads and automobiles. Genetic algorithm, and fuzzy logic are utilized in order to implement the proposed algorithm. Using genetic algorithm, the proposed algorithm searches shortest routes in terms of travel time in consideration of stochastic traffic volume, diverse turn constraints, etc. Then using fuzzy logic, it selects driver-preference optimal route among the candidate routes searched by GA, taking into account various driver's preferences such as difficulty degree of driving and surrounding scenery of road, etc. In order to evaluate this algorithm, a virtual road-traffic network DB with various road attributes is simulated, where the suggested algorithm promptly produces the best route for a driver with reference to his or her preferences.