• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.183-192
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• 2003

Obstacle detection and avoidance are considered as one of the key technologies on an unmanned vehicle system. In this paper, we propose a method of obstacle detection and avoidance and it is composed of vehicle control, modeling, and sensor experiments. Obstacle detection and avoidance consist of two parts: one is longitudinal control system for acceleration and deceleration and the other is lateral control system for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control system of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. In this paper, we propose a method for vehicle control, modeling, and obstacle avoidance, which are evaluated through road tests.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.323-330
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• 2020

This paper proposes the road roughness based Braking Pressure Calculation System(BPCS) for an Autonomous Vehicle Stability. The system consists of an image normalization module that processes the front image of a vehicle to fit the input of the random forest, a Random Forest based Road Roughness Classification Module that distinguish the roughness of the road on which the vehicle is travelling by using the weather information and the front image of a vehicle as an input, and a brake pressure control module that modifies a friction coefficient applied to the vehicle according to the road roughness and determines the braking strength to maintain optimal driving according to a vehicle ahead. To verify the efficiency of the BPCS experiment was conducted with a random forest model. The result of the experiment shows that the accuracy of the random forest model was about 2% higher than that of the SVM, and that 7 features should be bagged to make an accurate random forest model. Therefore, the BPCS satisfies both real-time and accuracy in situations where the vehicle needs to brake.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.8
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• pp.720-728
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• 2012

It is important for identification of noise and vibration problem of tire to consider influence of interaction between road and tire. A quantification of road noise is a challenging issue in vehicle NVH due to extremely complicated transfer paths of road noise as well as the difficulty in an experimental identification of input force from tire-road interaction. A noise caused by tire is divided into road noise(structure-borne noise) and pattern noise(air-borne noise). Pattern noise is caused by pattern shape of tire, which has larger than 500 Hz, but road noise is generated by the interactions between a tire and a vehicle body. In this paper, we define the quantitative analysis for road noise caused by interactions between tire and road parameters. For the identification of road noise, the chassis dynamometer that is equipped $10mm{\times}10mm $ square cleat in the semi-anechoic chamber is used, and the tire spindle forces are measured by load cell. The vibro-acoustic transfer function between ear position and wheel center was measured by the vibro-acoustic reciprocity method. In this study three tires with different type of mechanical are used for the experiment work.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.341-343
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• 1995

In this paper, an algorithm is presented to recogniz the driving direction of a vehicle and obstacles in front of it based on highway road image. The algorithm employs a neural network with 27 sub sets obtained from the road image as its input. The outputs include the direction of the vehicle movement and presence or absence of obstacles. The road image, obtained by a video camera, was digitized and processed by a personal computer equipped with an image processing board.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.145-150
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• 2003

Mobile mapping system is a surveying system that use vehicle carrying various sensors as CCD camera, GPS and IMU(Inertial measurement Unit). This system capturing images of forward direction continuously while running road. Use these images, then acquire road and road facilities information as facilities position, size or maintenance condition. In this study, we organized data and each data processing steps that are needed for 3 dimensional positioning. And develop digital photogrammetry S/W easy to use and accurate for mobile mapping system.

• Proceedings of the KOR-KST Conference
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• 2003.02a
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• pp.119-126
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• 2003

The aim of this research was to compare driver's workload among AHS (Automate Highway Systems) road sections in a virtual AHS environment that is based on a re Korean expressway in order to predict and compare the workloads imposed by the change (driver-vehicle interface and vehicle control authority. Road sections included the M (Manual Lane), TL1 (Transition Lane to enter the automated lane), AL (Automated Lane TL2 (Transition Lane to enter the manual lane after the end of automated driving), an post-AHS manual lane.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.2 s.245
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• pp.136-143
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• 2006

A particle image velocimetry (PlV) technique has been applied to measure the quantitative flow field characteristics behind a road vehicle with/without an air spoiler attached on its trunk and to estimate its effect on the wake. A vehicle model scaled in the ratio of 1/43 is set up in the mid-section of a closed-loop water tunnel. The Reynolds number based on the vehicle length is $10^5$. To investigate the three-dimensional structure of the recirculation zone and vortices, measurements are carried out on the planes both parallel and perpendicular to the free stream, respectively. The results show significant differences in the recirculation region and the vorticity distributions according to the existence of the air spoiler. The focus and the saddle point, appearing just behind the air spoiler, are disposed differently along the spanwise direction. Regarding the streamwise vortices, the air spoiler produces large wing tip vortices. They have opposite rotational directions to C-pillar vortices which are commonly observed in case that the air spoiler is absent. The wing tip vortices generate the down-force and as a result, they can make the vehicle more stable in driving.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.11 s.116
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• pp.1124-1131
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• 2006

This paper presents a novel method to determine sound power level(PWL) emitted by a travelling vehicle for road traffic noise simulation. The PWL is evaluated by the equivalent sound pressure level (SPL) measured by close proximity method and the sound power correction factor derived from the maximum SPL measured by pass-by method and the propagation attenuation of vehicle noise during the pass-by measurement. Using the method, we derive the empirical formula for PWL estimation in 1/1-octave and overall frequency bands for 8 vehicles (automobile, SUV, small truck, large bus, trailer, 3 dump trucks) tested at two road surfaces (dense graded asphalt, 30mm transverse tinning concrete) of Korean highway test road. The suggested approach, if securing sufficient data to represent the acoustic characteristics of all vehicle types, has il strong merit to be able to evaluate sound power levels for any combination of vehicle categories and traffic volumes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.11 s.170
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• pp.1960-1969
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• 1999

This paper presents dynamic modeling and controller design of a tracked vehicle installed with the double rod type ERSU(electro-rheological suspension unit). A 16 degree-of-freedom model for the tracked vehicle is established by Lagrangian method followed by the formulation of a new sky-ground hook controller. This controller takes account for both the ride quality and the steering stability. The weighting parameter between the two performance requirements is adopted to adjust required performance characteristics with respect to the operation conditions such as road excitation. The parameter is appropriately determined by employing a fuzzy algorithm associated with the vehicle motion. Computer simulations are undertaken in order to demonstrate the effectiveness of the proposed control system. Acceleration values at the driver's seat are analyzed under bump road profile, while frequency responses of vertical acceleration are investigated under random road excitation.

• Journal of Power Electronics
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• v.13 no.4
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• pp.536-545
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• 2013

In this study, an integrated motor control algorithm for an in-wheel electric vehicle is suggested. It consists of slip control that controls the in-wheel motor torque using the road friction coefficient and slip ratio; yaw rate control that controls the in-wheel motor torque according to the road friction coefficient and the yaw rate error; and velocity control that controls the vehicle velocity by a weight factor based on the road friction coefficient and the yaw rate error. A co-simulator was developed, which combined the vehicle performance simulator based on MATLAB/Simulink and the vehicle model of CarSim. Based on the co-simulator, a human-in-the-loop simulation environment was constructed, in which a driver can directly control the steering wheel, the accelerator pedal, and the brake pedal in real time. The performance of the integrated motor control algorithm for the in-wheel electric vehicle was evaluated through human-in-the-loop simulations.