• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.14-19
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• 2022

This paper presents motion planning algorithm that yields to intervening side lane vehicles in a congested traffic flow based on vehicle to vehicle (V2V) communication. Autonomous driving in dense traffic situation requires advanced driving performance in terms of vehicle interaction and risk mitigation. One of the most important functions necessary for congested traffic autonomous driving is to predict the lane change intention of the side lane target vehicle. However, implementing this function by using only environmental sensors has limitations. In this study, V2V communication is used to overcome the limitations and determine the intention of cut-in vehicles. Lane change intention of the intervening side lane vehicle is inferred by its longitudinal speed, steering angle, and turn signal light information received by the on-board-unit (OBU). Once the yield decision is made, the subject vehicle decelerates to generate sufficient clearance for the target vehicle to enter. Validation of the algorithm was conducted with actual autonomous test vehicles.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.7-13
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• 2022

This paper presents a yaw moment control based on estimated mass for manual-shift commercial vehicles. In yaw moment controller, parameter uncertantiy of vehicle mass is important because the desired yaw moment depends on vehicle parameter. However, in the case of commercial vehicle, the weight of the loaded vehicle is more than twice as much as compared to the unloaded vehicle. The proposed algorithm estimates the vehicle mass by using the longitudinal dynamic and gear shifting characteristics. The estimated mass is used to adaptively modify the vehicle parameters. In addition, this paper estimates the chamber pressure of a pneumatic brake and generates the target yaw moment through on/off valve control. MATLAB/Simulink and Trucksim were performed under sine with dwell test. The results demonstrate that the proposed algorithm improves the lateral and rollover stability.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.70-74
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• 2022

This paper describes the development of a target vehicle state estimation algorithm using vehicle-to-vehicle (V2V) communication. Perceiving the state of the target vehicle has great importance for successful autonomous driving and has been studied using various sensors and methods for many years. V2V communication has advantage of not being constrained by surrounding circumstances relative to other sensors. In this paper, we adopt the V2V signal for estimating the target vehicle state. Since applying only the V2V signal is improper by its low frequency and latency, the signal is used as additional measured data to improve the estimation accuracy. We estimate the target vehicle state using Extended Kalman filter (EKF); a point mass model was utilized in process update to predict the state of next step. The process update is followed by measurement update when ego vehicle receives V2V information. The proposed study evaluated state estimation by comparing input V2V information in an experiment where the ego vehicle follows the target vehicle behind it.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.263-266
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• 2011

Drivers check always vehicle state for own safety and is necessary to understand about vehicle state. If driver know vehicle state, because driver request vehicle state at vehicle specialty company, driver pay a lot of money and waste a lot of time. Now, drivers have checked vehicle state by using variety features of smart phone due to progress of IT(Information Technology). but existing smartphone vehicle diagnostic system learned professional knowledge of vehicle and know vehicle state. drives not need vehicle diagnostic. to overcome these disadvantages, there use easily drivers by using smartphone and request system to know own all vehicle state. In this paper, there implement vehicle diagnostic system with smartphone based on android OS to use easily this system and know check information of vehicle supplies replacement cycles, vehicle internal problems, Eco driving by using OBD-II data to receive by OBD-II Protocol convert Bluetooth connector.

• Journal of Korea Multimedia Society
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• v.7 no.1
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• pp.35-43
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• 2004

In this paper, we proposed a vehicle recognition and electronic toll collection system with detection and classification of vehicle identification mark and emblem as well as recognition of vehicle license plate to unman toll fee collection system or incoming/outcoming vehicles to an institution. In the proposed algorithm, we first process pre-processing step such as noise reduction and thinning from the rear side input image of vehicle and detect vehicle mark, emblem and license plate region using intensity variation informations, template masking and labeling operation. And then, we classify the detected vehicle features regions into vehicle mark and emblem as well as recognize characters and numbers of vehicle license plate using hybrid and seven segment pattern vector. To show the efficiency of the proposed algorithm, we tested it on real vehicle images of implemented vehicle recognition system in highway toll gate and found that the proposed method shows good feature detection/classification performance regardless of irregular environment conditions as well as noise, size, and location of vehicles. And also, the proposed algorithm may be utilized for catching criminal vehicles, unmanned toll collection system, and unmanned checking incoming/outcoming vehicles to an institution.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.55-61
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• 2009

In order to observe the impact of a type of vehicles for traffic flows and pavement, vehicle classifications is conducted. Korean Ministry of Land, Transport and Maritime Affairs provides 12-type vehicle classifications on National expressways, National highways, and Provincial roads. Current AVC (Automatic Vehicle Classification) devices decide vehicle types comparing measurements of vehicle lengths, wheelbases, overhangs etc. to a reference table including those of all types of models. This study developed an algorithm for macroscopic vehicle classification which is less sensitive to tuning sensors and updating the reference table. For those characteristics, trend lines in vehicle lengths and wheelbases are employed. To assess the algorithm developed, vehicle lengths and wheelbases were collected from an AVC device. In this experiment, this algorithm showed the accuracy of 88.2 % compared to true values obtained from video replaying. Our efforts in this study are expected to contribute to developing devices for macroscopic vehicle classification.

• Journal of the Ergonomics Society of Korea
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• v.30 no.5
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• pp.651-657
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• 2011

Objective: The aim of this study is to investigate the system to integrate and manage the in-vehicle interactions between the drivers and the in-vehicle mobile IT devices. Background: As the mobile IT technology is being used anywhere, the drivers are interacting with the mobile IT device on driving situations. The distraction of the driver's attention causes the car accidents. It is necessary to develop the HVI(Human Vehicle Interface System) to integrate and manage the in-vehicle interactions with IT devices. Method: The HVI System is designed not as the interfacing subject but as the supervising system to monitor the driver's status and support the driver to concentrate on the primary tasks. The HVI system collects the status information of the car and driver and estimate the driving workload. Results: The HVI system controls how to provide the output information based on the driving workload. We implemented the HVI system prototype and applied in the real vehicle with the HVI cell phone and the HVI car navigation system. Conclusion: Depending on the driving situations, the HVI system prevented the information output in dangerous situation and diversified the modality and the intensity of the output information. Application: We will extend the HVI system to be connected the other various IT devices and verity the effectiveness of the system through various experiments.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.3
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• pp.123-129
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• 2002

This paper proposes a vehicle trajectory prediction method far application to vehicle-to-vehicle distance control. This method is based on 2-dimensional kinematics and a Kalman filter has been used to estimate acceleration of the object vehicle. The simulation results using the proposed control method show that the relative distance characteristics can be improved via the trajectory prediction method compared to the customary intelligent cruise control algorithm.

• Journal of the Society of Disaster Information
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• v.2 no.1
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• pp.39-52
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• 2006

In this paper, an analytical and experimental study was performed in order to determine the effects of interaction between vehicle and structure. Results presented in the paper show that analytical method including moving load effect can investigate the trend of structural response due to dynamic interaction between vehicle and structure. The wheel tracking machine fitted with 2-axle test vehicle can demonstrate more accurate dynamic interaction between vehicle and structure than the wheel tracking machine fitted without 2-axle test vehicle.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.3
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• pp.256-263
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• 2002

This paper addresses a planning problem in a pickup-delivery transportation' system under dynamic vehicle dispatching. We present a procedure to determine a fleet size in which stochastic characteristics of vehicle travels are considered. Statistical approach and queueing theory are applied to estimate vehicle travel time and vehicle waiting time, based on which an appropriate fleet size is determined. Simulation experiments are performed to verify the proposed procedure.