• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3566-3582
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• 2019

In intelligent warehouse picking system, the allocation of tasks has an important influence on the efficiency of the whole system because of the large number of robots and orders. The paper proposes a method to solve the task allocation problem that multi-robot task allocation problem is transformed into transportation problem to find a collision-free task allocation scheme and then improve the capability of task processing. The task time window and the power consumption of multi-robot (driving distance) are regarded as the utility function and the maximized utility function is the objective function. Then an integer programming formulation is constructed considering the number of task assignment on an agent according to their battery consumption restriction. The problem of task allocation is solved by table working method. Finally, simulation modeling of the methods based on table working method is carried out. Results show that the method has good performance and can improve the efficiency of the task execution.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.139-141
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• 2019

This paper proposes the application of LoRa network, which has been under various research recently, to use control system for the transfer of Unmanned Vehicle. LoRa( Long Range) has a wide coverage of up to30 km, and is characterized by large-scale low-power long-distance radio communication. LoRa has already been studied in various industries. It is also proposed to study various functions by utilizing LoRa network and applying it to the control system of the uninhabited entity.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.11
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• pp.16-22
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• 2020

This study was aimed at analyzing the velocity and pressure changes in the airflow corresponding to different configurations of a diffuser for three types of cars. According to the flow results of the three automotive models, in model 3, the vortex was formed slightly upward on the outlet plane, whereas in models 1 and 2, the vortex was generated lower than that in model 3. The values of the pressure distribution in model 3 were larger than those for models 1 and 2 on the planes located at the same distance from the end of the rear part. The maximum turbulent kinetic energies in models 1 and 2 occurred at a location lower than that in model 3. The shape corresponding to the airflow that enhanced the driving performance was determined through the flow analysis.

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.665-676
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• 2022

In modern logistics, the effective use of the vehicle volume and loading capacity will reduce the logistic cost. Many heuristic algorithms can solve this knapsack problem, but lots of these algorithms have a drawback, that is, they often fall into locally optimal solutions. A fusion optimization method based on simulated annealing algorithm (SA) and binary particle swarm optimization algorithm (BPSO) is proposed in the paper. We establish a logistics knapsack model of the fusion optimization algorithm. Then, a new model of express logistics simulation system is used for comparing three algorithms. The experiment verifies the effectiveness of the algorithm proposed in this paper. The experimental results show that the use of BPSO-SA algorithm can improve the utilization rate and the load rate of logistics distribution vehicles. So, the number of vehicles used for distribution and the average driving distance will be reduced. The purposes of the logistics knapsack problem optimization are achieved.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.2
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• pp.51-58
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• 2009

In this paper, a system which uses Bluetooth and Zigbee wireless communication and mobile device is designed. The temperature within vehicle and the distance betweeen the vehicle and the obstacle is measured by ultrasonic sensor system. The measured data is sent to the mobile PDA and displayed to assist safe driving.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.694-696
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• 2022

In this study, in order to predict KIA's K3 used car price, we used car data registered on the K Car site from 2013 to 2021, and the variables used in the correlation analysis are model year, accident presence / absence, and driving. Distance, fuel and exhaust volume were used. Based on this data, we were able to use the Google Colab platform to analyze the correlation and, through the analysis, know if it correlates with the used car price.

• Annual Conference of KIPS
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• 2021.11a
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• pp.783-786
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• 2021

In recent years, the use of LiDAR sensors is increasing as autonomous driving, robot control, and drones are considered more. Contrary to ordinary cameras, LiDAR sensors make it possible to handle challenging problems by calculating the distance between objects. This crucial characteristic makes more active research on deep learning models dealing with point clouds which are data of LiDAR. In this paper, among the schemes of using the point cloud, the Point-based approach is mainly discussed. Furthermore, future streams and insights can be considered by looking at solving methods and the limitations.

• Journal of ILASS-Korea
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• v.29 no.1
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• pp.1-6
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• 2024

This paper is a numerical analysis study for evaluating the energy efficiency of electric vehicles. Currently, the methods for testing and evaluating the energy consumption efficiency of electric vehicles have limitations such as resources and time. Therefore, there is a need for research on developing models to predict the energy consumption efficiency of electric vehicles. In this study, a numerical analysis research is conducted to predict the energy efficiency of electric vehicles using a vehicle dynamics numerical analysis model. To validate the accuracy of the simulation model, it is compared the results of dynamometer tests with the simulation results and used the Unified Diagnostic Services (UDS) protocol to acquire internal data from the electric vehicle. It is ensured the reliability of the simulation model by comparing data such as motor speed, battery voltage, current, state of charge (SOC), regenerative braking power generation, and total driving distance of the test vehicle with dynamometer test data and simulation model results.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.593-600
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• 2022

Various sensors such as lidar, radar, and camera are fused and used in autonomous vehicles. Rider and radar sensors are difficult to popularize because they are expensive equipment. In order to popularize autonomous vehicles, research that can replace expensive equipment is continuously being conducted. In this paper, we use a single camera that is inexpensive and can be easily mounted. We propose a method for detecting the wheels and adjacent lanes of a front-side vehicle of a driving vehicle and estimating distances. Our proposed method detects lanes and wheels from frame images after frame extraction via input images. In addition, the distance is measured and compared with the actual distance measured in the actual road environment. The distance could be calculated relatively accurately within the error range of ± 3 cm. Through this, it is expected that the camera can be used as an alternative means when the cost of autonomous vehicles is reduced or when the lidar or radar sensor fails.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.1
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• pp.185-194
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• 2014

This study investigates the methodology to evaluate the quantified performance of pavement markings and traffic guide signs using digital images. This methodology is significant to attempt to quantify their performance without large brightness photometer at the nighttime and bad weather. The retroreflective performance of pavement markings are evaluated through the contrast of gray levels of pavements and markings in collected digital images under the case of rain, dampness, and dryness. In addition, the appraisal of retroreflective performance of traffic guide signs are implemented through the comparison between interior illuminated and the existing retroreflective traffic guide signs using the contrast of luminance extracted from the value of RGB of backgrounds and legends in collected digital images according to geometric design, driving lanes, and the distance between the car and the sign. As a result, the retroreflective performance of pavement markings deteriorates about 3.5 times and 2 times under the case of rain and dampness respectively than dryness. Also, the performance of the existing traffic guide signs is significantly influenced by geometric design, driving lanes, and the distance, otherwise interior illuminated traffic guide signs. This methodology can be utilized to construct objective information of performance of traffic safety facilities to select appropriate position of expensive high reflective pavement markings and interior illuminated traffic guide signs considering diverse weather and geometric design.