• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.6
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• pp.726-732
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• 2013

It is required for UGV(Unmanned Ground Vehicle) to have a LPP(Local Path Plan) component which generate a local path via the center of road by analyzing binary map to travel autonomously unpaved road in rough environment. In this paper, we present the method of boundary estimation for unpaved road and a local path planning method based on RANGER algorithm using the estimated boundary. In specially, the paper presents an approach to estimate road boundary and the selection method of candidate path to minimize the problem of zigzag driving based on Bayesian probability reasoning. Field test is conducted with scenarios in rough environment in which bush, tree and unpaved road are included and the performance of proposed method is validated.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.1
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• pp.73-81
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• 2011

The performance of emission factor has been validated by comparison with on-road test data. Emission factor, which is a function of vehicle speed, has been acquired based on chassis dynamometer test with NIER driving pattern. Portable Emission Measurement System, PEMS has measured on-road emission. Test vehicle was operated on defined test routes under different driving conditions, and made ten trips along its route. Emission factors properly simulate on-road test result, although there is some drawback to consider variety of driving condition on real world. Vehicle specific power and acceleration have been used to explain the distributed on-road result within same vehicle speed range. The trend in carbon dioxide and nitrogen oxide emission with respect to specific power and acceleration is clear. It has been found that specific power is a good explanatory variable for microscopic analysis for modal test result. Acceleration is good for microscopic as well as macroscopic analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.605-613
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• 2010

In this study, Impact factors are represented and barrier height of compact car road of safety barrier is suggested through the investigation of applying problems of existed standard of general car road. For this, traffic accidents analysis is performed and based on the analysis, impact vehicle weight, impact Angle, crash velocity, and barrier height are investigated. For the decision of impact angle, analysis is carried out by comparison of RISER and 2-lines expressway accidents data. Through this, higher-impact angle is suggested. Vehicle weight data of sub-compact car, small vehicle, medium and large vehicle, SUV, small truck is surveyed and analyzed. Based on the accident accumulation rate, regression analysis of vehicle weight impact and impact velocity is performed. Also, based on the cumulative rate of vehicle weight on expressways near Seoul, barrier height of compact car road is calculated. It is noted that the results of this study will be contributed to the decision of barrier type.

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.52-57
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• 2006

One of the important functions of an Intelligent Transportation System (ITS) is to classify vehicle types using a vision system. We propose a method using machine-learning algorithms for this classification problem with 3-D object model fitting. It is also necessary to detect road lanes from a fixed traffic surveillance camera in preparation for model fitting. We apply a background mask and line analysis algorithm based on statistical measures to Hough Transform (HT) in order to remove noise and false positive road lanes. The results show that this method is quite efficient in terms of quality.

• Journal of Auto-vehicle Safety Association
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• v.3 no.2
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• pp.28-33
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• 2011

This paper presents driving path estimation algorithm for adaptive cruise control system and advanced emergency braking system using multi-sensor fusion. Through data collection, yaw rate filtering based road curvature and vision sensor road curvature characteristics are analyzed. Yaw rate filtering based road curvature and vision sensor road curvature are fused into the one curvature by weighting factor which are considering characteristics of each curvature data. The proposed driving path estimation algorithm has been investigated via simulation performed on a vehicle package Carsim and Matlab/Simulink. It has been shown via simulation that the proposed driving path estimation algorithm improves primary target detection rate.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.1
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• pp.205-215
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• 2001

In this study, modeling and analysis procedure for the dynamic analysis of a high mobility tracked vehicle system were studied. The vehicle model used in this investigation is assumed to be consist of two kinematically decoupled subsystems. The chassis subsystem consists of chassis frame, sprocket, support rollers, road wheels, idler wheel, road wheel arms and idle wheel arm, while the track subsystem is represented as a closed kinematic chain consisting of track links and end connectors interconnected by revolute joints with bushing. Nonlinear contact force module describing the interaction between track link, and sprocket, idler wheel, road wheel, support roller, ground was used. The effects of road wheel arms and idler wheel arm due to tension adjuster are also considered.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.4
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• pp.84-92
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• 1997

Among the various sources of vehicle interior noise, this paper concerns the road induced noise ; the identification of its transfer path by using experimental method. Multiple input and single output model is taken as a noise generation model. Because it is impossible to measure the road imput forces directly, the acceleration signals are measured on four axle;three directions for each point. By considering the cross correlations of input signals, four uncorrelated source groups are taken. Multiple coherence function is employed to investigate the contribution of each group. In addtion, to identify the detailed path through the suspension systems, the contributions of all possible paths are ranked by using the coherence functions between interior noise and the relative accelerations of connections such as bushings and mountings. Measurements are performed with passenger vehicle traveling on concrete and asphalt roads at 60㎞/h.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.170.3-170
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• 2001

Antilock brake system(ABS) prevent the wheels of road vehicle from locking up and skidding so that the braking force is from static friction instead of kinetic friction. Therefore ABS helps drivers maintain steering control during breaking situation particularly at an emergency stopping situation. So when trying to stop the road vehicle it is best to have the most friction possible for faster deceleration ABS keep the wheels turning which means there is more friction between the tires of vehicles and the road surface. Because of this advantage, ABS are now a commonly installed feature for passenger's safety in road vehicles. In this study, hydraulic system of ABS of vehicle is composed of 3port-2position solenoid valve. In order to minimize ...

• Journal of Sensor Science and Technology
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• v.10 no.2
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• pp.134-141
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• 2001

This paper describes a method to steer an autonomous electric vehicle using magnetic fields. Magnets are embeded along the center of the road and a magneto-resistive sensor is mounted beneath the front bumper of the vehicle. As the vehicle moves along the road neural network controller controls the vehicle using measured magnetic field variation. Based on a single magnets modeling equation, we analyzed three dimensional magnetic field distributions of embeded magnets in series on the center of the road and performed a computer simulation using this results. In simulation study, straight and curved road was configured. The steering controller for the vehicle was designed using neural network and experiment was performed on the real embeded magnets using real autonomous electric vehicle. At the experiment we compensated the earth's magnetic fields and showed a good result driving an autonomous vehicle using proposed method.

• International Journal of Automotive Technology
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• v.7 no.1
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• pp.25-34
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• 2006

For decades, simulation technique has been well validated in areas such as computer and communication systems. Recently, the technique has been much used in the area of transportation and traffic forecasting. Several methods have been proposed for investigating complex traffic flows. However, the dynamics of vehicles and diversities of driver characteristics have never been considered sufficiently in these methods, although they are considered important factors in traffic flow analysis. In this paper, we propose a traffic simulation tool called Multi-Agent for Traffic Simulation with Vehicle Dynamics Model (MATDYMO). Road transport consultants, traffic engineers and urban traffic control center managers are expected to use MATDYMO to efficiently simulate traffic flow. MATDYMO has four sub systems: the road management system, the vehicle motion control system, the driver management system, and the integration control system. The road management system simulates traffic flow for various traffic environments (e.g., multi-lane roads, nodes, virtual lanes, and signals); the vehicle motion control system constructs the vehicle agent by using various vehicle dynamic models; the driver management system constructs the driver agent capable of having different driving styles; and lastly, the integrated control system regulates the MATDYMO as a whole and observes the agents running in the system. The vehicle motion control system and driver management system are described in the companion paper. An interrupted and uninterrupted flow model were simulated, and the simulation results were verified by comparing them with the results from a commercial software, TRANSYT-7F. The simulation result of the uninterrupted flow model showed that the driver agent displayed human-like behavior ranging from slow and careful driving to fast and aggressive driving. The simulation of the interrupted flow model was implemented as two cases. The first case analyzed traffic flow as the traffic signals changed at different intervals and as the turning traffic volume changed. Second case analyzed the traffic flow as the traffic signals changed at different intervals and as the road length changed. The simulation results of the interrupted flow model showed that the close relationship between traffic state change and traffic signal interval.