• Title/Summary/Keyword: Vehicle Steering

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A Study on Variable Speed Limit Considering Wind Resistance on Off-Shore Bridge (해상교량의 풍하중을 고려한 제한 속도 도출 방안)

  • Lee, Seon-Ha;Kang, Hee-Chan
    • Journal of Korean Society of Transportation
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    • v.22 no.5
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    • pp.75-87
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    • 2004
  • Along the seashore regions in Korea, though strong winds with very large strength are frequently witnessed, no system which can provide appropriate speed information for driving vehicle has been introduced. The driving against strong winds could be very dangerous because of the high possibility of accidents such as rollover and collision. These accidents usually resulted from driver's forced driving try even in difficult situation for steering vehicle, and sometimes overspeed without consideration of wind impact to the vehicles. To reduce accident caused by strong winds, it is important to inform drivers of appropriate driving speeds by perceiving strong winds. By setting up WIS at the main points where strong winds frequently appear and using the variable message sign(VMS) connected to the on-line whether information system, it tis possible to provide desired speed information, which can maintain vehicles' tractive force and maximum running resistance. The case study is conducted on the case of Mokpo-Big-Bridge, which is under construction at Mokpo city. The result show that in case the annual average direction of wind is South and the wind speed is over 8m/hr, the desired speed, which is required in order for vehicles running to South direction to maintain the marginal driving power, is 60km/hr. In addition, for the case of a typhoon such as Memi generated in 2003 year, if wind speed had been 18m/sec in Mokpo city at that time, the running resistance at the speed of 40km/hr is calculated as 1131N. This resistance can not be overcome at the 4th gear(1054N) level, therefore, the gear of vehicles should be reduced down to the 3rd level. In this case, the appropriate speed is 40km/h, and at this point the biggest difference between running resistance and tractive force is generated.

Reliability-based Design Optimization on Mobility of Deep-seabed Test Miner Using Censored Data of Current Speed (중도절단 해류속도자료를 이용한 심해저 시험집광기의 주행성능에 관한 신뢰성 기반 최적설계)

  • Park, Sanghyun;Cho, Su-Gil;Lim, Woochul;Kim, Saekyeol;Choi, Sung Sik;Lee, Minuk;Choi, Jong-Su;Kim, Hyung-Woo;Lee, Chang-Ho;Hong, Sup;Lee, Tae Hee
    • Ocean and Polar Research
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    • v.36 no.4
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    • pp.487-494
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    • 2014
  • Deep-seabed test miner operated by a self-propelled mining system moving on soft soil is an essential device to secure floating and towing performances. The performances of the tracked vehicle are seriously influenced by noise factors such as the shear strength of the seafloor, bottom current, seafloor slope, speed of tracked vehicle, reaction forces of flexible hose, steering ratio, etc. Due to uncertainties related to noise factors, the design of a deep-sea manganese nodules test miner that satisfies target reliabilities is difficult. Therefore, reliability-based design optimization (RBDO) is required to guarantee system reliability under circumstances where uncertainties related to noise factors prevail. Among noise factors, the bottom current, a bimodal distribution, is censored due to the observation limit of measurement devices. Therefore, estimated distribution of the bottom current is inaccurate without considering these characteristics and the result of RBDO cannot be guaranteed. In this paper, we define censored data as unknown values over the limit of observation. If this data is estimated by using Akaike information criterion (AIC) that cannot consider the characteristics of censored data, the distribution of estimated data cannot guarantee accurate reliability. Therefore, censored AIC that can consider the characteristics of data is used to estimate accurate distribution of the bottom current. Finally, RBDO, under circumstances where uncertainties related to noise factors combined censored data are present, is performed on the mobility of a deep-sea manganese nodules test miner.

Analysis of Muscle Activities and Driving Performance for Manipulating Brake and Accelerator Pedal by using Left and Right Hand Control Devices (장애인용 핸드컨트롤을 이용한 가속 및 제동 페달을 동작할 때의 상지 근육 EMG 분석 및 운전 성능 평가)

  • Song, Jeongheon;Kim, Yongchul
    • Journal of Biomedical Engineering Research
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    • v.38 no.2
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    • pp.74-81
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    • 2017
  • The purpose of this study was to investigate the EMG characteristics of driver's upper extremity and driving performance for manipulating brake and accelerator pedal by using left and right hand control devices during simulated driving. The people with disabilities in the lower limb have problems in operation of the motor vehicle because of functional loss for manipulating brake and accelerator pedal. Therefore, if hand control device is used for adaptive driving controls in people with lower limb impairments, the disabled people can improve their quality of life by driving a motor vehicle. Six subjects were participated in this study to evaluate driving performance and muscle activities for operating brake and accelerator pedal by using two different hand controls (steering column mounted hand control and floor mounted hand control) in driving simulator. We measured EMG activities of six muscles (posterior deltoid, middle deltoid, triceps, biceps, flexor carpi radialis, and extensor carpi radialis) during pushing and pulling movement with different hand controls for acceleration and braking. STISim Drive 3 software was used for the performance test of different hand control devices in straight lane course for time to reach target speed and brake reaction time. While pulling the hand control lever toward the driver, normalized EMG activities of middle deltoid, triceps and flexor carpi radialis in subjects with disabilities were significantly increased (p < 0.05) compared to the normal subjects. It was also found that muscle responses of posterior deltoid were significantly increased (p < 0.05) when using the right hand control than left hand control. While pushing the hand control lever forward away from the driver, normalized EMG activities of posterior deltoid, middle deltoid and extensor carpi radialis in subjects with disability were significantly increased (p < 0.05) compared to the normal subjects. It was shown that muscle responses of middle deltoid, biceps and extensor carpi radialis were significantly increased when using the right hand control than left hand control. Brake reaction time and time to reach target speed in subjects with disability was increased by 12% and 11.3% on average compared to normal subjects. The subjects with physical disabilities showed a tendency to relatively slow acceleration at the straight lane course.

A Study on Design and Implementation of Driver's Blind Spot Assist System Using CNN Technique (CNN 기법을 활용한 운전자 시선 사각지대 보조 시스템 설계 및 구현 연구)

  • Lim, Seung-Cheol;Go, Jae-Seung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.2
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    • pp.149-155
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    • 2020
  • The Korea Highway Traffic Authority provides statistics that analyze the causes of traffic accidents that occurred since 2015 using the Traffic Accident Analysis System (TAAS). it was reported Through TAAS that the driver's forward carelessness was the main cause of traffic accidents in 2018. As statistics on the cause of traffic accidents, 51.2 percent used mobile phones and watched DMB while driving, 14 percent did not secure safe distance, and 3.6 percent violated their duty to protect pedestrians, representing a total of 68.8 percent. In this paper, we propose a system that has improved the advanced driver assistance system ADAS (Advanced Driver Assistance Systems) by utilizing CNN (Convolutional Neural Network) among the algorithms of Deep Learning. The proposed system learns a model that classifies the movement of the driver's face and eyes using Conv2D techniques which are mainly used for Image processing, while recognizing and detecting objects around the vehicle with cameras attached to the front of the vehicle to recognize the driving environment. Then, using the learned visual steering model and driving environment data, the hazard is classified and detected in three stages, depending on the driver's view and driving environment to assist the driver with the forward and blind spots.

Automated Driving Lane Change Algorithm Based on Robust Model Predictive Control for Merge Situations on Highway Intersections (고속도로 합류점 주행을 위한 강건 모델 예측 기법 기반 자율주행 차선 변경 알고리즘 개발)

  • Chae, Heongseok;Jeong, Yonghwan;Min, Kyongchan;Lee, Myungsu;Yi, Kyongsu
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.41 no.7
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    • pp.575-583
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    • 2017
  • This paper describes the design and evaluation of a driving mode decision algorithm for automated driving for merge situations on highways. For the development of a highly automated driving control algorithm for merge situations, the driving mode decision is crucial for merging appropriately. There are two driving modes: lane keeping and lane changing (merging). The merge mode decision is determined based on the state of the surrounding vehicles and the remaining length of the merge lane. In the merge mode decision algorithm, merge possibility and the desired merge position are decided to change the lane safely and quickly. A safety driving envelope is defined based on the desired driving mode using the information on the surrounding vehicles' behaviors. To obtain the desired steering angle and longitudinal acceleration for maintaining the subject vehicle in the safe driving envelope, a motion planning controller is designed using model predictive control (MPC), with constraints that are decided considering the vehicle dynamics, safe driving envelope, and actuator limit. The proposed control algorithm has been evaluated via computer simulation studies.

A Study on Design Optimization of an Axle Spring for Multi-axis Stiffness (다중 축 강성을 위한 축상 스프링 최적설계 연구)

  • Hwang, In-Kyeong;Hur, Hyun-Moo;Kim, Myeong-Jun;Park, Tae-Won
    • Journal of the Korean Society for Railway
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    • v.20 no.3
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    • pp.311-319
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    • 2017
  • The primary suspension system of a railway vehicle restrains the wheelset and the bogie, which greatly affects the dynamic characteristics of the vehicle depending on the stiffness in each direction. In order to improve the dynamic characteristics, different stiffness in each direction is required. However, designing different stiffness in each direction is difficult in the case of a general suspension device. To address this, in this paper, an optimization technique is applied to design different stiffness in each direction by using a conical rubber spring. The optimization is performed by using target and analysis RMS values. Lastly, the final model is proposed by complementing the shape of the weak part of the model. An actual model is developed and the reliability of the optimization model is proved on the basis of a deviation average of about 7.7% compared to the target stiffness through a static load test. In addition, the stiffness value is applied to a multibody dynamics model to analyze the stability and curve performance. The critical speed of the improved model was 190km/h, which was faster than the maximum speed of 110km/h. In addition, the steering performance is improved by 34% compared with the conventional model.

Discovery of the Dmitri Donskoi ship near Ulleung Island(East Sea of Korea), using geophysical surveys (물리탐사기술을 이용한 침몰선 Dmitri Donskoi호 탐사)

  • Yoo, Hai-Soo;Kim, Su-Jeong;Park, Dong-Won
    • Geophysics and Geophysical Exploration
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    • v.8 no.1
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    • pp.104-111
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    • 2005
  • Dmitri Donskoi, the Russian cruiser launched in 1883, is known to have sunk near Ulleung Island (East Sea, Korea) on May 29, 1905, while it was participating in the Russo-Japanese War. In order to find this ship, information about its possible location was obtained from Russian and Japanese maritime historical records. The supposed location of the ship was identified, and we conducted a five-year geophysical survey from 1999 to 2003. A reconnaissance three-dimensional topographic survey of the sea floor was carried out using multi-beam echo sounder, marine magnetometer, and side-scan sonar. An anomalous body identified through the initial reconnaissance survey was identified by a detailed survey using a remotely operated vehicle, deep-sea camera, and the mini-submarine Pathfinder. Interpretation of the acquired data showed that the ship is hanging on the side of a channel, at the bottom of the sea 400 m below sea level. The location is about 2 km from Port Jeodong, Uleung Island. We discovered 152 mm naval guns and other war materiel still attached to the hull of the ship. In addition, the remnants of the steering gear and other machinery that were burnt during the final action were found near the hull. Strong magnetic fields, resulting from the presence of volcanic rocks in the survey area, affected the resolution of the magnetic data gathered; as a result, we could not locate the ship reliably using the magnetic method. Severe sea floor topography in the gully around the hull gave rise to diffuse reflections in the side-scan sonar data, and this prevented us from identifying the anomalous body with the side-scan sonar technique. However, the sea-floor image obtained from the multi-bean echo sounder was very useful in verifying the location of the ship.

Development for the Azimuth Measurement Algorithm using Multi Sensor Fusion Method (멀티센서 퓨전 기법을 활용한 방위 측정 알고리즘의 설계)

  • Kim, Tae-Yeong;Kim, Young-Chul;Song, Moon-Kyou;Chong, Kil-To
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.2
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    • pp.865-871
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    • 2011
  • Presently, the location and direction information are certainly needed for the autonomous vehicle of the ship. Among them, the direction information is a essential elements to automatic steering system. And the gyro-compass, the magnetic-compass and the GPS compass are the sensor indicating the direction. The gyro-compasses are mainly used in the large-sized ship of the GMDSS(Global Maritime Distress & Safety System). The precision and the reliability of the gyro-compasses are excellent but big volume and high price are disadvantage. The magnetic-compass has relatively fine precision and inexpensive price. However, the disadvantage is in the influence by the magnetism object including the steel structure of a ship, and etc. In the case of the GPS compass, the true north is indicated according to the change of the location information but in case of the minimum number of satellites or stopping of a ship or exercise in the error range, the exact direction cannot be obtained. In this paper, the performance of the GPS compass was improved by using the least-square curve fitting method for the mutual trade off of the angle sensor. The algorithm which improves the precision of an azimuth by applying the weighted value according to the size of covariance error was proposed with GPS-compass and magnetic compass. The characteristic and the performance of the proposed algorithm were analyzed and verified through experimentation. The applicability of the proposed algorithm was shown through the experimental result.

Study of Deepsea Mining Robot "MineRo" Using Table of Orthogonal Arrays (직교 배열표를 이용한 심해저 채광로봇 미내로의 주행 특성 연구)

  • Lee, Chang-Ho;Kim, Hyung-Woo;Choi, Jong-Su;Yeu, Tae-Kyeong;Lee, Min-Uk;Oh, Jae-Won;Hong, Sup
    • Journal of Ocean Engineering and Technology
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    • v.28 no.2
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    • pp.152-159
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    • 2014
  • KRISO(Korea Research Institute of Ships & Ocean Engineering) designed and manufactured a pilot mining robot called "MineRo" in 2012. MineRo is composed of four track modules. In general, much time and money are needed for deep-sea tests. Therefore, a numerical analysis to predict the dynamic behaviors has to be performed before a deep-sea test. In the numerical analysis, the information about the mining robot and soil properties are the most important factors to analyze the driving performance and dynamic response of MineRo. A terra-mechanics model of extremely cohesive soft soil is implemented in the form of the relationships between the normal pressure and sinkage, and between the shear stress and shear displacement. It is possible to acquire information about MineRo from the CAD model in the design phase. The Wong model is applied to the terra-mechanics model. This model is necessary to acquire many soil coefficients for a numerical analysis. However, in soil testing, the amount of soil property data obtained is limited. Moreover, it is difficult to analyze all of the cases for the many soil coefficients. In this paper, the dynamic behaviors of MineRo are analyzed according to the driving velocity, steering ratio, and variable extremely cohesive soft soil properties using a table of orthogonal arrays. The dynamic responses of MineRo are the turning radius, sinkage, and slip ratio. The relationships between the dynamic responses and variable soil properties are derived for MineRo.

Encoder Type Semantic Segmentation Algorithm Using Multi-scale Learning Type for Road Surface Damage Recognition (도로 노면 파손 인식을 위한 Multi-scale 학습 방식의 암호화 형식 의미론적 분할 알고리즘)

  • Shim, Seungbo;Song, Young Eun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.2
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    • pp.89-103
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    • 2020
  • As we face an aging society, the demand for personal mobility for disabled and aged people is increasing. In fact, as of 2017, the number of electric wheelchair in the country continues to increase to 90,000. However, people with disabilities and seniors are more likely to have accidents while driving, because their judgment and coordination are inferior to normal people. One of the causes of the accident is the interference of personal vehicle steering control due to unbalanced road surface conditions. In this paper, we introduce a encoder type semantic segmentation algorithm that can recognize road conditions at high speed to prevent such accidents. To this end, more than 1,500 training data and 150 test data including road surface damage were newly secured. With the data, we proposed a deep neural network composed of encoder stages, unlike the Auto-encoding type consisting of encoder and decoder stages. Compared to the conventional method, this deep neural network has a 4.45% increase in mean accuracy, a 59.2% decrease in parameters, and an 11.9% increase in computation speed. It is expected that safe personal transportation will be come soon by utilizing such high speed algorithm.