• Journal of Auto-vehicle Safety Association
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• v.11 no.3
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• pp.30-36
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• 2019

This paper suggests a car-following algorithm for urban environment, with multiple target candidates. Until now, advanced driver assistant systems (ADASs) and self-driving technologies have been researched to cope with diverse possible scenarios. Among them, car-following driving has been formed the groundwork of autonomous vehicle for its integrity and flexibility to other modes such as smart cruise system (SCC) and platooning. Although the field has a rich history, most researches has been focused on the shape of target trajectory, such as the order of interpolated polynomial, in simple single-lane situation. However, to introduce the car-following mode in urban environment, realistic situation should be reflected: multi-lane road, target's unstable driving tendency, obstacles. Therefore, the suggested car-following system includes both in-lane preceding vehicle and other factors such as side-lane targets. The algorithm is comprised of three parts: path candidate generation and optimal trajectory selection. In the first part, initial guesses of desired paths are calculated as polynomial function connecting host vehicle's state and vicinal vehicle's predicted future states. In the second part, final target trajectory is selected using quadratic cost function reflecting safeness, control input efficiency, and initial objective such as velocity. Finally, adjusted path and control input are calculated using model predictive control (MPC). The suggested algorithm's performance is verified using off-line simulation using Matlab; the results shows reasonable car-following motion planning.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.299-305
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• 2019

This study was initiated to solve the difficulties of aged and female workers in agriculture society due to aging and demise of young people. In the case of the conventional elevated lift, the risk of exposure to uneven road or work environment, not the difficulty of professional qualification and operation, and the risk of exposure to the uneven road or working environment, were also studied based on previous researches so that women could easily and efficiently perform productive agriculture. First, the simulation was carried out through the prediction model of traction performance using the object of agricultural forklift, and the soil of the Kimhae city in Gyeongnam (34.125kPa, internal friction angle 35.294deg, external friction angle 13.620deg, Adhesion force 5.750 kPa, average cone index 0-15 cm cl, 1001.8 kPa). In the case of the forklift for simulation, the driving force and the kinetic resistance prediction modeling of the agricultural electric forklift are modeled. Based on this model, the motor control drive adopts the 1232E model, which is a drive dedicated to AC motor, and divides the two drivers into master and slave And the model for the simulation was designed to control motor drive, hydraulic drive, and various outputs on the main PCB. The simulation model is undergoing continuous simulation, modification and supplementation. Based on this research, we will continue research for development of safer and more efficient agricultural electric forklift.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.2
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• pp.57-64
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• 2021

This study presents a method for realtime fuel consumption prediction using real data collected from OBDII. With the advent of the era of self-driving cars, electronic control units(ECU) are getting more complex, and various studies are being attempted to extract and analyze more accurate data from vehicles. But since ECU is getting more complex, it is getting harder to get the data from ECU. To solve this problem, the firmware was developed for acquiring accurate vehicle data in this study, which extracted 53,580 actual driving data sets from vehicles from January to February 2019. Using these data, the ensemble stacking technique was used to increase the accuracy of the realtime fuel consumption prediction model. In this study, Ridge, Lasso, XGBoost, and LightGBM were used as base models, and Ridge was used for meta model, and the predicted performance was MAE 0.011, RMSE 0.017.

• Proceedings of the KIEE Conference
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• 1999.07a
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• pp.49-51
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• 1999

This paper presents an efficient 2D finite element analysis(FEA) for brushless DC motor (BLDCM) taking into account the eddy current and lamination effect of stator. In BLDCM, the dynamic characteristic analysis considering the eddy current and driving circuit is applied for the accurate prediction of motor performance in high speed because the eddy current loss is proportional of square of the driving frequency. According to the variation of lamination number, the characteristics of electro magnetic force, torque, and eddy current loss are analyzed. From the results, it is known that the effect of the lamination of stator on the eddy current loss is verified.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.9
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• pp.902-907
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• 2011

In this paper, we deal with performance evaluation of visual path following using 2D and 3D information. Visual path follow first teaches driving path by selecting milestone images then follows the same route by comparing the milestone image and current image. We follow the visual path following algorithm of [8] and [10]. In [8], a robot navigated with 2D image information only. But in [10], local 3D geometries are reconstructed between the milestone images in order to achieve fast feature prediction which allows the recovery from tracking failures. Experimental results including diverse indoor cases show performance of each algorithm.

• International Journal of Fluid Machinery and Systems
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• v.1 no.1
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• pp.76-85
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• 2008

In order to extract micro hydropower in the very low specific speed range, a Positive Displacement Turbine (PDT) was proposed and steady performance was determined experimentally. However, the suppression of large pressure pulsation is inevitable for practical application of PDT. The objective of the present study is to reveal the mechanism and the characteristics of pressure pulsation in PDT by use of CFD and to suppress the pressure pulsation. Unsteady CFD analysis has revealed that large pressure pulsation is caused by large variation of rotational speed of the following rotor, while the driving rotor, which is output rotor, keeps constant speed. Here is newly proposed a 4-lobe helical type rotor which can reduce the pressure pulsation drastically and the performance prediction of new PDT is determined.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3416-3435
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• 2023

Task offloading in vehicular networks is hot topic in the development of autonomous driving. In these scenarios, due to the role of vehicles and pedestrians, task characteristics are changing constantly. The classical deep learning algorithm always uses a pre-trained neural network to optimize task offloading, which leads to system performance degradation. Therefore, this paper proposes a neural network fine-tuning task offloading algorithm, combining with location prediction for pedestrians and vehicles by the Payne model of fluid dynamics and the car-following model, respectively. After the locations are predicted, characteristics of tasks can be obtained and the neural network will be fine-tuned. Finally, the proposed algorithm continuously predicts task characteristics and fine-tunes a neural network to maintain high system performance and meet low delay requirements. From the simulation results, compared with other algorithms, the proposed algorithm still guarantees a lower task offloading delay, especially when congestion occurs.

• Journal of Biosystems Engineering
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• v.34 no.5
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• pp.297-304
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• 2009

This study was conducted to investigate the adequacy of the representative empirical models which are developed for predicting the tractive performance of the tractor operating in various soil conditions. Four representative empirical models which are widely used in the traction prediction of tractor were selected through literature review. Four models were Wismer-Luth, Brixius, Dwyer and Hernandez model, which were empirical traction models of a single wheel. The efficacy of four models were confirmed via comparison of the tractions of tractor predicted using the four models with those measured from traction tests which were conducted for two different driving type (2WD and 4WD) of the tractor on two different soil conditions. The results showed that tractions predicted by Brixius' model, especially for slip range under 20% which the operating efficiency of a tractor is very high, were well consistent with the ones measured from traction test better than the tractions predicted by models which are proposed by Wismer-Luth, Dwyer and Hernandez.

• Tribology and Lubricants
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• v.27 no.4
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• pp.218-223
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• 2011

To improve the performance of a bent-axis type axial piston pump driven by the tapered pistons, it is necessary to know the pressure ripple characteristics. The purpose of this paper is to understand the effect on the pressure ripple characteristics and the prediction by comparing experimental and theoretical results. The simulation model of the bent-axis type axial piston pump is developed in the AMESim environment using the geometrical dimension and the driving mechanism of the piston pump. The results can be obtained to predict the performance characteristics of the bent-axis type axial piston pump.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.613-616
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• 2012

A multi body simulation (MBS) model is developed for predicting the impact harshness of the vehicle. Impact harshness is the vehicle performance to evaluate the impulsive vibration behavior during driving over an obstacle of the road. Thus, the approach is simulated on the time domain for considering the transient behavior of the vehicle. The validity of vehicle component modeling of bushes, dampers and structure flexibilities is verified. The simulations are compared with the test results in both of vertical and longitudinal directions. In particular, the vertical vibration of the vehicle is significantly affected by the body flexibility. Through the sensitivity analysis, main factors for the impact harshness performance are investigated.