• International Journal of Automotive Technology
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• v.8 no.4
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• pp.513-520
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• 2007

In this paper, we propose an approach to identify the driving environment for intelligent highway vehicles by means of image processing and computer vision techniques. The proposed approach mainly consists of two consecutive computational steps. The first step is the lane marking detection, which is used to identify the location of the host vehicle and road geometry. In this step, related standard image processing techniques are adapted for lane-related information. In the second step, by using the output from the first step, a four-stage algorithm for vehicle detection is proposed to provide information on the relative position and speed between the host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenarios. Herein, experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.1
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• pp.23-31
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• 2020

It is essential to estimate the vehicle localization for an autonomous safety driving. In particular, since LIDAR provides precise scan data, many studies carried out to estimate the vehicle localization using LIDAR and pre-generated map. The road marking always exists on the road because of provides driving information. Therefore, it is often used for map information. In this paper, we propose to generate the Gaussian mixture map based on road-marking information and localization method using this map. Generally, the probability distributions map stores the single Gaussian distribution for each grid. However, single resolution probability distributions map cannot express complex shapes when grid resolution is large. In addition, when grid resolution is small, map size is bigger and process time is longer. Therefore, it is difficult to apply the road marking. On the other hand, Gaussian mixture distribution can effectively express the road marking by several probability distributions. In this paper, we generate Gaussian mixture map and perform vehicle localization using Gaussian mixture map. Localization performance is analyzed through the experimental result.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.2
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• pp.76-82
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• 2014

In this paper, an optimal power distribution algorithm is proposed for the small electric vehicle with front in-line and rear in-wheel motors. First, it is assumed that the vehicle driving torque and velocity are given conditions. And, an optimal problem is defined that finding the front and rear motor torques which minimizes the battery power. From the above optimization problem, the optimized front-rear motor torque distribution map is obtained. And, the vehicle simulations are performed to verify the performance of the optimal power distribution algorithm which is proposed in this study. The simulations are performed based on the federal urban driving schedule for two cases which are constant ratio power distribution, and optimal power distribution. From the simulation results, it is found that the optimal power distribution shows the 6.3% smaller battery energy consumption than the constant ratio power distribution.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.262-266
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• 2014

Military vehicle equipped with an antenna and a shelter for operating radar has a vibration exposure during driving time. This vibration would have influence on structure of military vehicle critically. In this paper, driving stability of the military vehicle is obtained through the vibration response analysis. And, vibration level of the military vehicle satisfied the military vibration specification through analysis and comparing the MIL-STD-810G. PSD and Grms data obtained by road test can be used for vibration test specification of cabinets and electronic equipment in shelter.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.364-369
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• 2012

The vehicle sound classified into driving sound due to power-train, operating sound due to electric motor like sunroof, door lock and electronic sound. These vehicle sound has various features depend on the characteristic of sound that user required. And it based on cultural and regional difference of user. In this study, the user required vehicle sound characteristics for luxury sedan was investigated in overall viewpoint. And virtual target sound was developed through the result of user preference investigation. Next, Jury test was carried out in Germany, USA and Korea for evaluating the target sound. And the regional and individual difference of preference was analyzed through the result of jury test. This result of research will be contributed to design of vehicle sound quality and target sound setting.

• Journal of the Korean Society of Mechanical Technology
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• v.13 no.3
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• pp.17-23
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• 2011

To estimate fuel consumption of a vehicle, a car can be tested on chassis dynamometer. In this case, test causes a lot of time and money. To predict the fuel efficiency of vehicles in the design stage or early stage of development, the development of computer simulation model is necessary. Using simulation to predict the fuel consumption, the driving model which consists of time-velocity profile and time-grade profile is necessary In this study, vehicle model is developed in MatLab/simulink to estimate real driving fuel consumption rate with time-velocity profile, time-shift gear profile and time-grade profile. Vehicle model consists of driver model, engine model, power train model, and so on. On-road vehicle tests to verify the vehicle model are carried out for analyzing the result of simulation and comparing with those of the experiments.

• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.48-53
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• 2020

This paper describes in work which is currently underway to the minimum safety performance requirements and test methods of V2V based on IEEE 802.11p in vehicle level like below. - The ranges and positions at static and driving condition of vehicle for BSM (Basic safety message) - Various road conditions such as straight road, crossroad, slope-way Based on this study, We will define the minimum safety performance requirements and test methods of V2V in vehicle considering various road conditions.

• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.35-42
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• 2022

This paper presents a stochastic model predictive control (SMPC) for stop maneuver of autonomous vehicles considering perception uncertainty of stopped vehicle. The vehicle longitudinal motion should achieve both driving comfortability and safety. The comfortable stop maneuver can be performed by mimicking acceleration profile of human driving pattern. In order to implement human-like stop motion, we propose a reference safe inter-distance and velocity model for the longitudinal control system. The SMPC is used to track the reference model which contains the position uncertainty of preceding vehicle as a chance constraint. We conduct simulation studies of deceleration scenarios against stopped vehicle in urban environment. The test results show that proposed SMPC can execute comfortable stop maneuver and guarantee safety simultaneously.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.351-358
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• 2023

This study designed a model-based Vehicle Control Unit (VCU) software for electric vehicles. Electric vehicles have transitioned from conventional powertrains (e.g., engines and transmissions) to electric powertrains. The primary role of the VCU is to determine the optimal torque for driving control. This decision is based on the driver's power request and current road conditions. The determined torque is then transmitted to the electric drive system, which includes motors and controllers. The VCU employs an Artificial Neural Network (ANN) and calibrated reference torque to enhance the electric vehicle's performance. The designed VCU software further refines the final reference torque by comparing the control logic with the torque calculation functions and ANN-generated reference torque. Vehicle tests confirmed the effective optimization of vehicle performance using the model-based VCU software, which includes an ANN.

• Journal of Auto-vehicle Safety Association
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• v.15 no.4
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• pp.23-31
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• 2023

In recent years, the technology for autonomous driving has been advancing rapidly, ADAS (Advanced Driver Assistance System) functions, which improve driver convenience and safety performance, are mostly equipped in recently released vehicles and range from level 0 to level 2 in autonomous driving technology. Among the various functions of ADAS, AEBS (Autonomous Emergency Braking System), which analyzes traffic accidents, is the most closely related to the vehicle's braking. This study developed a simulation technique for reproducing accidents related to AEBS based on real vehicle experimental data, and it was applied to the analysis of actual ADAS vehicle accidents to identify the causes of accidents.