• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.7
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• pp.548-554
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• 2003

This study alms to investigate the dynamic properties of express buses in the very low frequencies which cause motion sickness Incidence. Since passengers often use express buses for long distance traveling. it is a critical point whether the ride give rise to motion sickness or not. In the study accelerations at the three Points on the floor of the six test vehicles were measured during the driving at constant speeds. By applying the frequency weighting corves suggested in ISO 26.31-1, the Physical quantity of accelerations were changed into the perceptual amount used to judge quantitatively the incidence of motion sickness. Motion sickness dose values were calculated from the frequency weighted time history of acceleration signals, and compared between the vehicles, driving conditions. and the seat positions in the bus. During the 50 minutes' driving on the public road and high ways. the vomiting incidence ratios were seen to range from 0.4 to 0.8 ％. which is equivalent to 2.4 to 4.8 ％ for 5 hours' driving. Unlike the very smooth road conditions considered in this work, motion sickness dose values encountered in real situations are expected to increase.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.163-172
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• 2004

Nowadays, to analyze the dynamic characteristics of the automotive driving system, the computer simulation linked up with VR(Virtual Reality) technology is treated as the useful method with the improvement of computing ability. In this paper, the VR simulation system has been developed to investigate the driving characteristics of the ASV(Advanced Safety Vehicle) equipped with an ACC(Adaptive Cruise Control) system. For the purpose, VR environment which generates 3D graphic and sound information of the vehicle, the road, the facilities, and the terrain has been organized for the driving reality. Mathematical models of vehicle dynamic analysis including the ACC model have been constructed for computer simulation. The ACC modulates the throttle and brake functions to regulate the vehicle speed so that vehicles could keep proper spacing. Also, the real-time simulation algorithm synchronizes vehicle dynamic simulation with the graphic rendering. With the developed VR simulation system, simple scenarios are applied to analyze the dynamic characteristics. It is shown that the VR simulation system could be useful to evaluate the adaptive cruise controlled vehicle on various driving conditions.

• Journal of Drive and Control
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• v.20 no.2
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• pp.24-30
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• 2023

This study aimed to analyze the fatigue of forklifts in industrial settings by assessing their stress levels during operation. Strain gauges were affixed to the dynamic components of the forklifts to gather real-time data and enhance the reliability of the analysis. Although monitoring structural loads in harsh testing environments can be challenging, the affixed strain gauges on the dynamic components can provide more precise results and improve the interpretation of data. By creating testing modes that simulate forklift usage environments and performing experiments with selected cargo and driving modes, a comparison of the damage severity of forklift parts under different driving conditions was done. These results can be utilized to forecast the lifespan of forklift parts under extreme driving conditions and assist in the design and optimization of new parts in the future.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.5
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• pp.203-208
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• 2023

Recently, with the growing interest in the field of autonomous driving, many researchers have been focusing on developing autonomous driving software platforms. In particular, we have concentrated on developing 3D object detection models that can improve real-time performance. In this paper, we introduce a self-constructed 3D LiDAR dataset specific to domestic environments and propose a VariFocal-based CenterPoint for the 3D object detection model, with improved performance over the previous models. Furthermore, we present experimental results comparing the performance of the 3D object detection modules using our self-built and public dataset. As the results show, our model, which was trained on a large amount of self-constructed dataset, successfully solves the issue of failing to detect large vehicles and small objects such as motorcycles and pedestrians, which the previous models had difficulty detecting. Consequently, the proposed model shows a performance improvement of about 1.0 mAP over the previous model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.713-718
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• 2014

This paper proposed a real-time monitoring system that can realize effective operation of snowplows each of the local autonomous entities secures to cope with disasters in Korea like a wintertime heavy snowfall and also can promptly cope with the spot facing a heavy snowfall disaster by doing real-time monitoring on the information of the snow-removal site and the mobility of the vehicles. Also, the study has designed a relay terminal analysis tool so that the proposed system can analyze all kinds of controlling information and diagnose the relay terminal effectively. The proposed system can realize effective and emergent coping with the situations of a heavy snowfall disaster through real-time routing trace as well as effective work progress within a short time by doing real-time monitoring on the information about the status of snow-removal work and vehicle controlling for snow-removal work as well as the location information of snow-removal vehicles in the situations of a heavy snowfall.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.962-970
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• 2021

The cause of the majority of vehicle accidents is a safety issue due to the driver's inattention, such as drowsy driving. A forward collision warning system (FCWS) can significantly reduce the number and severity of accidents by detecting the risk of collision with vehicles in front and providing an advanced warning signal to the driver. This paper describes a low power embedded system based FCWS for safety. The algorithm computes time to collision (TTC) through detection, tracking, distance calculation for the vehicle ahead and current vehicle speed information with a single camera. Additionally, in order to operate in real time even in a low-performance embedded system, an optimization technique in the program with high and low levels will be introduced. The system has been tested through the driving video of the vehicle in the embedded system. As a result of using the optimization technique, the execution time was about 170 times faster than that when using the previous non-optimized process.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.303-311
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• 2010

There have been various forms of systems such as a digital speedometer or a black box etc. to meet the social requirement for reducing traffic accidents and safe driving. However that systems are based on after-accident vehicle data, there is limit to prevent the accident before. So in our previous research, by storing, analyzing the Vehicle-dynamic information coming from driver's behavior, we are developing the decision-device which could provide driver with Alerting-Information in real-time to enhance the driver's safety drive. but the performance valuation is not yet executed. Finally, this study developed positional recognition system by using the DGPS for pre-developed risky driving decision device. The result of test analyzed with the same that the aggregated vehicle dynamics data in DGPS and dangerous risky driving decision device. If the performance of risky driving decision device is verified by precisely positional recognition system, the risky driving management of vehicle would be effected.

• Journal of KIISE
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• v.42 no.2
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• pp.203-212
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• 2015

This paper proposes a traffic sign recognition method in real road environments. The video stream in driving environments has two different characteristics compared to a general object video stream. First, the number of traffic sign types is limited and their shapes are mostly simple. Second, the camera cannot take clear pictures in the road scenes since there are many illumination changes and weather conditions are continuously changing. In this paper, we improve a modified census transform(MCT) to extract features effectively from the road scenes that have many illumination changes. The extracted features are collected by histograms and are transformed by the dense descriptors into very high dimensional vectors. Then, the high dimensional descriptors are encoded into a low dimensional feature vector by Fisher-vector coding and Gaussian Mixture Model. The proposed method shows illumination invariant detection and recognition, and the performance is sufficient to detect and recognize traffic signs in real-time with high accuracy.

• Journal of Auto-vehicle Safety Association
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• v.13 no.2
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• pp.35-41
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• 2021

In this study, improved path tracking control algorithm based on pure pursuit algorithm is newly proposed by using improved lane detection algorithm through real time post-processing with interpolation methodology. Since the original pure pursuit works well only at speeds below 20 km/h, the look-ahead distance is implemented as a sigmoid function to work well at an average speed of 45 km/h to improve tracking performance. In addition, a smoothing filter was added to reduce the steering angle vibration of the original algorithm, and the stability of the steering angle was improved. The post-processing algorithm presented has implemented more robust lane recognition system using real-time pre/post processing method with deep learning and estimated interpolation. Real time processing is more cost-effective than the method using lots of computing resources and building abundant datasets for improving the performance of deep learning networks. Therefore, this paper also presents improved lane detection performance by using the final results with naive computer vision codes and pre/post processing. Firstly, the pre-processing was newly designed for real-time processing and robust recognition performance of augmentation. Secondly, the post-processing was designed to detect lanes by receiving the segmentation results based on the estimated interpolation in consideration of the properties of the continuous lanes. Consequently, experimental results by utilizing driving guidance line information from processing parts show that the improved lane detection algorithm is effective to minimize the lateral offset error in the diverse maneuvering roads.

• Journal of IKEEE
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• v.26 no.3
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• pp.401-407
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• 2022

Recently, image processing technology for autonomous driving by recognizing objects and lanes through camera images to realize autonomous vehicles is being studied. Haze reduces the visibility of images captured by the camera and causes malfunctions of autonomous vehicles. To solve this, it is necessary to apply the haze removal function that can be processed in real time to the camera. Therefore, in this paper, the fog removal method of Sim with excellent performance is implemented with hardware capable of real-time processing. The proposed hardware was designed using Verilog HDL, and FPGA was implemented by setting Xilinx's xc7z045-2ffg900 as the target device. As a result of logic synthesis using Xilinx Vivado program, it has a maximum operating frequency of 276.932MHz and a maximum processing speed of 31.279fps in a 4K (4096×2160) high-resolution environment, thus satisfying the real-time processing standard.