• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.8
• /
• pp.633-642
• /
• 2016

It is important for advanced active safety systems and autonomous driving cars to get the accurate estimates of the nearby vehicles in order to increase their safety and performance. This paper proposes a sensor fusion method for radar and vision sensors to accurately estimate the state of the preceding vehicles. In particular, we performed a study on compensating for the lateral state error on automotive radar sensors by using a vision sensor. The proposed method is based on the Interactive Multiple Model(IMM) algorithm, which stochastically integrates the multiple Kalman Filters with the multiple models depending on lateral-compensation mode and radar-single sensor mode. In addition, a Probabilistic Data Association Filter(PDAF) is utilized as a data association method to improve the reliability of the estimates under a cluttered radar environment. A two-step correction method is used in the Kalman filter, which efficiently associates both the radar and vision measurements into single state estimates. Finally, the proposed method is validated through off-line simulations using measurements obtained from a field test in an actual road environment.

• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.7
• /
• pp.614-621
• /
• 2001

The controllers for a full car 7-DOF model with 4 active or semi-active suspension units are designed and evaluated in this research. The control algorithms for suspension systems, such as full state feedback active, full state feedback semi-active, sky-hook active, sky-hook semi-actvie, and on-off suspension systems, are analyzed and evaluated with respect to ride comfort. The vehicle dynamic performances are expressed by response curves to a bump input, performance indices for asphalt road input, and frequency characteristic curves. Heaving, rolling, and pitching inputs are applied to the vehicle dynamic system to evaluate frequency characteristics. The simulation results show that the ride quality of the sky-hook controller approaches that the full state feedback controller more closely in semi-active suspension system than in active suspension system. For the implementation of a vehicle with sky-hook suspension control systems in this paper, 7 velocity sensors are required to measure the states.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.4
• /
• pp.313-320
• /
• 2011

Multi-axle driving vehicles that are used in special environments require high driving performance, steering performance, and stability. Among these vehicles, 6WS/6WD vehicles with middle wheels have structural safety by distributing the load and reducing the pitch angle during rapid acceleration and braking. 6WS/6WD vehicles are favored for military use in off road operations because of their high maneuverability and mobility on extreme terrains and obstacles. 6WD vehicles that using in-wheel motor can generate the independent wheel torque without other mechanical parts. Conventional vehicles, however, cannot generate an opposite driving force at each side wheel. Using an independent steering and driving system, six-wheel vehicles can show better performance than conventional vehicles. Using of independent steering and driving system, the 6 wheel vehicle can improve a performance better than conventional vehicle. This vehicle enhances the maneuverability under low speed and the stability at high speed. This paper describes an independent 6WS/6WD vehicle, consists of three parts; Vehicle Model, Control Algorithm for 6WS/6WD and Simulation. First, vehicle model is application of TruckSim software for 6WS and 6WD. Second, control algorithm describes the optimum tire force distribution method in view of energy saving. Last is simulation and verification.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.8
• /
• pp.787-793
• /
• 2012

This paper introduces the autonomous vehicle Pharos, which participated in the 2010 Autonomous Vehicle Competition organized by Hyundai-Kia motors. PHAROS was developed for high-speed on/off-road unmanned driving avoiding diverse patterns of obstacles. For the high speed traveling up to 60 km/h, long range terrain perception, real-time path planning and high speed vehicle motion control algorithms are developed. This paper describes the major hardware and software components of our vehicle.

• Proceedings of the KIEE Conference
• /
• 2005.07c
• /
• pp.2019-2021
• /
• 2005

This paper describes the cut off time and the current characteristics of virgin RCDs and deteriorated ones in the seashore. The RCDs(Residual Current Protective Devices) are used for protecting the human body from electrical shock and for preventing facility accidents. According to the Korean standards, the RCDs are installed in panel boards. When RCDs are installed outside, they must be enclosed inside waterproof cases. In the case that RCOs are employed at temporary power sites and electrical facilities on the road, they are exposed to the external environment. As a result, the RCDs deteriorated in the seashore for 3 months showed high failure rate, while the virgin RCDs all complied with Korean Standard. Considering that the RCDs are used under exposed condition outside, the reliance of RCDs must be ensured by modifying the related regulations and codes and by developing Improved models advanced in their performance.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.8 no.2
• /
• pp.471-476
• /
• 2004

This paper presents an active vision system for on-line traffic sign recognition. The system is composed of two cameras, one is equipped with a wide-angle lens and the other with a telephoto lends, and a PC with an image processing board. The system first detects candidates for traffic signs in the wide-angle image using color, intensity, and shape information. For each candidate, the telephoto-camera is directed to its predicted position to capture the candidate in a large size in the image. The recognition algorithm is designed by intensively using built in functions of an off-the-shelf image processing board to realize both easy implementation and fast recognition. The results of on-road experiments show the feasibility of the system.

• Journal of information and communication convergence engineering
• /
• v.11 no.2
• /
• pp.95-102
• /
• 2013

This paper presents a stochastic driver behavior modeling framework which takes into account both individual and general driving characteristics as one aggregate model. Patterns of individual driving styles are modeled using a Dirichlet process mixture model, as a non-parametric Bayesian approach which automatically selects the optimal number of model components to fit sparse observations of each particular driver's behavior. In addition, general or background driving patterns are also captured with a Gaussian mixture model using a reasonably large amount of development data from several drivers. By combining both probability distributions, the aggregate driver-dependent model can better emphasize driving characteristics of each particular driver, while also backing off to exploit general driving behavior in cases of unseen/unmatched parameter spaces from individual training observations. The proposed driver behavior model was employed to anticipate pedal operation behavior during car-following maneuvers involving several drivers on the road. The experimental results showed advantages of the combined model over the model adaptation approach.

• Translational and Clinical Pharmacology
• /
• v.26 no.4
• /
• pp.155-159
• /
• 2018

For regulatory approval of a new drug, the most preferred and reliable source of evidence would be randomized controlled trials (RCT). However, a great number of drugs, being developed as well as already marketed and being used, usually lack proper indications for children. It is imperative to develop properly evaluated drugs for children. And expanding the use of already approved drugs for other indications will benefit patients and the society. Nevertheless, to get an approval for expansion of indications, most often with off-label experiences, for drugs that have been approved or for the development of pediatric indications, either during or after completing the main drug development, conducting RCTs may not be the only, if not right, way to take. Extrapolation strategies and modelling & simulation for pediatric drug development are paving the road to the better approval scheme. Making the use of data sources other than RCT such as EHR and claims data in ways that improve the efficiency and validity of the results (e.g., randomized pragmatic trial and randomized registry trial) has been the topic of great interest all around the world. Regulatory authorities should adopt new methodologies for regulatory approval processes to adapt to the changes brought by increasing availability of big and real world data utilizing new tools of technological advancement.

• Journal of Auto-vehicle Safety Association
• /
• v.11 no.3
• /
• pp.30-36
• /
• 2019

This paper suggests a car-following algorithm for urban environment, with multiple target candidates. Until now, advanced driver assistant systems (ADASs) and self-driving technologies have been researched to cope with diverse possible scenarios. Among them, car-following driving has been formed the groundwork of autonomous vehicle for its integrity and flexibility to other modes such as smart cruise system (SCC) and platooning. Although the field has a rich history, most researches has been focused on the shape of target trajectory, such as the order of interpolated polynomial, in simple single-lane situation. However, to introduce the car-following mode in urban environment, realistic situation should be reflected: multi-lane road, target's unstable driving tendency, obstacles. Therefore, the suggested car-following system includes both in-lane preceding vehicle and other factors such as side-lane targets. The algorithm is comprised of three parts: path candidate generation and optimal trajectory selection. In the first part, initial guesses of desired paths are calculated as polynomial function connecting host vehicle's state and vicinal vehicle's predicted future states. In the second part, final target trajectory is selected using quadratic cost function reflecting safeness, control input efficiency, and initial objective such as velocity. Finally, adjusted path and control input are calculated using model predictive control (MPC). The suggested algorithm's performance is verified using off-line simulation using Matlab; the results shows reasonable car-following motion planning.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.24 no.3
• /
• pp.293-301
• /
• 2021

LTV(Light Tactical Vehicle) operating in our military requires higher levels of performance and durability to withstand harsher conditions than general vehicles, as they must travel on both rough-train and off-road as well as on public roads. Recently, LTV development is demanded a variety of test evaluations in order to satisfy ROC (Required Operational Capability) by the military requirement. However, there is no informations of driving test course for satisfying the durability performance of Korean tactical vehicle. Therefore, this study aims to provide basic data to establish reliable drive test conditions by analyzing the main maneuvering test site at the domestic and foreign country in order to select the representative drive course. These studies will provide a more scientific and systematic evaluation solution for the development of tactical vehicles, and can be effectively used to establish a certified system for military vehicle test evaluation in the future