• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.154-162
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• 2004

In this study, a mathematical model for analyzing the shifting transients of the passenger car with an automatic transmission is proposed. The proposed model comprises a power transmission system and a vehicle system, which are coupled. In order to extract the modeling parameters, on-road car test is carried out. The model is composed of a detailed powertrain, an engine/AT housing, a simplified suspension system, tires and a vehicle body model. On the test, the vehicle accelerations and pitch ratio are measured by using accelerometers and a gyro sensor. The speeds, the brake signal, and the throttle position are taken from sensors which already exist in the vehicle. Considering natural ftequencies, which is calculated from the measured accelerations, and the characteristic equation, vehicle model parameters are identified. Dynamic behaviors during upshift or downshift are simulated using the proposed vehicle model. By comparing and analyzing the simulation result and on-road car test data, the vibration of the Engine/AT housing influences the shifting transients. The effect of model parameters are also studied. Among model parameters, the location of engine mountings influences the vibration of the vehicle body.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.894-902
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• 2010

This paper presents a vision-based robust off-road terrain classification method against environmental variation. As a supervised classification algorithm, we applied a neural network classifier using wavelet features extracted from wavelet transform of an image. In order to get over an effect of overall image feature variation, we adopted environment sensors and gathered the training parameters database according to environmental conditions. The robust terrain classification algorithm against environmental variation was implemented by choosing an optimal parameter using environmental information. The proposed algorithm was embedded on a processor board under the VxWorks real-time operating system. The processor board is containing four 1GHz 7448 PowerPC CPUs. In order to implement an optimal software architecture on which a distributed parallel processing is possible, we measured and analyzed the data delivery time between the CPUs. And the performance of the present algorithm was verified, comparing classification results using the real off-road images acquired under various environmental conditions in conformity with applied classifiers and features. Experiments show the robustness of the classification results on any environmental condition.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.6
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• pp.259-266
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• 2000

Crash test data from different impact modes and threshold speeds were used to assess the effects of impact conditions on air bag electronic single point sensing (ESPS) activation requirements. The requirements are expressed in terms of the desired sensor activation time based on unbelted driver dummy kinematics. A crash discriminator pre-displacement is introduced to crash recognition algorithm to the ESPS. The new crash recognition algorithm named Velocity Energy Pre-displacement(VEPD) method is developed and the ESPS algorithm based on the VEPD technique is used to assess the ESPS system performance. It is shown that VEPD method correlates very well with desired sensor activation time and meets the activation requirement.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.257-257
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• 2000

The objective of this research is to monitor and control the vehicle motion in order to remove out the existing safety risk based upon the human-machine cooperative vehicle control. A predictive control method is proposed to control the steering wheel of the vehicle to keep the lane. Desired angle of the steering wheel to control the vehicle motion could be calculated based upon vehicle dynamics, current and estimated pose of the vehicle every sample steps. The vehicle pose and the road curvature were calculated by geometrically fusing sensor data from camera image, tachometer and steering wheel encoder though the Perception Net, where not only the state variables, but also the corresponding uncertainties were propagated in forward and backward direction in such a way to satisfy the given constraint condition, maintain consistency, reduce the uncertainties, and guarantee robustness. A series of experiments was conducted to evaluate the control performance, in which a car Like robot was utilized to quit unwanted safety problem. As the results, the robot was keeping very well a given lane with arbitrary shape at moderate speed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.131-146
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• 2017

Unlike in the past based on autonomous vehicle development sensor, In recent years, research has been conducted using external data such as LDM to compensate for the disadvantages of sensors. So, this study suggested the construction method of static map that provides road information for autonomous driving of vehicles as LDM - based information. In other to suggest, after review LDM's ISO 14296 and data specification and map of precise roda map of NGII, we had confirmed the correspondence wiht the international standard of NGII specification. As a result of the review, it is relatively good in terms of provided data and information, but the road structure expression is partially incompatible with the international standard. AS it is necessary to supplement about currently specification and method and suggest, this study had suggested ways to supplement the insuficient and to express the road structure.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.74-88
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• 2020

A Cooperative Intelligent Transportation System (CITS) provides useful information on upcoming hazards in order to prevent vehicle collisions. In addition, the availability of individual vehicle travel information obtained from the CITS infrastructure allows us to identify the level of road safety in real time and based on analysis of the indicators representing the crash potential. This study proposes a methodology to derive road safety content, and presents evaluation results for its applicability in practice, based on simulation experiments. Both jerk and Stopping Distance Index (SDI) were adopted as safety indicators and were further applied to derive road section safety information. Microscopic simulation results with VISSIM show that 5% and 20% samples of jerk and SDI are sufficient to represent road safety characteristics for all vehicles. It is expected that the outcome of this study will be fundamental to developing a novel and valuable system to monitor the level of road safety in real time.

• Journal of Sensor Science and Technology
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• v.24 no.5
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• pp.306-310
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• 2015

IoT(Internet of Things) based underground risk assessment system surrounding water pipeline enables an advanced monitoring and prediction for unexpected underground hazards such as abrupt road-side subsidence and urban sinkholes due to a leak in water pipeline. For the development of successful assessment technology, the PSU(Water Pipeline Safety Unit) which detects the leakage and movement of water pipes. Then, the IoT-based underground risk assessment system surrounding water pipeline will be proposed. The system consists of early detection tools for underground events and correspondence services, by analyzing leakage and movement data collected from PSU. These methods must be continuous and reliable, and cover certain block area ranging a few kilometers, for properly applying to regional water supply changes.

• Spatial Information Research
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• v.10 no.3
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• pp.407-419
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• 2002

In this study, the design of 4S-Van system is discussed fur the implementation of laser mapping system. Laser device is fast and accurate sensor that acquires 3D road and surface data. The orientation laser sensor is determined by loosely coupled (D)GPS/INS Integration. Considering current system architecture, (D)GPS/INS integration is performed far performance analysis of direct georeferencing and self-calibration is performed for interior and exterior orientation and displacement. We utilized 3 laser sensors for compensation and performance improvement. 3D surface data from laser scanner and texture image from CCD camera can be used to implement 3D visualization.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.6
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• pp.74-80
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• 2009

Path tracking of unmanned vehicle is a basis of autonomous driving and navigation. For the path tracking, it is very important to find the exact position of a vehicle. GPS is used to get the position of vehicle and a direction sensor and a velocity sensor is used to compensate the position error of GPS. To detect path lines in a road image, the bird's eye view transform is employed, which makes it easy to design a lateral control algorithm simply than from the perspective view of image. Because the driving speed of vehicle should be decreased at a curved lane and crossroads, so we suggest the speed control algorithm used GPS and image data. The control algorithm is simulated and experimented from the basis of expert driver's knowledge data. In the experiments, the results show that bird's eye view transform are good for the steering control and a speed control algorithm also shows a stability in real driving.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.203-210
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• 2011

The current sensor network analyzes the data collected by the sensing of fixed sensor nodes and provides a service. However, this method cannot actively handle the state and the change in the position of people, 'the target for sensing and the change in the environment', including home automation, building automation and real-time road & weather information, and healthcare environment, etc. To support a dynamic situation which is appropriate for an individual in this diverse environment, it is necessary to provide actively differentiated specific information according to the movement of people and the changes in the environment. In this study, a individualized sensor mobile agent middleware which provides the individualized information (the location of fire incidence and the trace for the path of spread), has been realized through the sensor network environment constructed by the installation of wireless sensor nodes mounted with mobile agent middlewares in buildings.