• Journal of Institute of Control, Robotics and Systems
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• v.20 no.3
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• pp.298-312
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• 2014

This paper describes control applications in automobiles. Many aspects of automotive applications of advanced control methods, which include suspension systems, stability control systems, engines, hybrid vehicle control systems, electric vehicle controls systems, advanced driver assistance systems and automated driving control systems, are reviewed. The control methods used in each area are briefly reviewed to help readers understand the applicability and effectiveness of these methods. In addition, some new trends in the research of automotive applications are described.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.856-864
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• 2008

This paper describes a vehicle low speed driving assistant (VLDA) system that is composed of laser scanner. This vehicle is designed for following lead vehicle (LV) without driver's operation. The system is made up several component systems that are based on unmanned ground vehicle (UGV). Each component system is applied to use advanced safety vehicle developed to complete UGV system. VLDA system was divided into vehicle control system and obstacle detecting system. The obstacle detecting system calculate distance and angle of LV and transmit these data to vehicle control system using front, left and right laser scanners. Vehicle control system makes vehicle control values such as steering angle, acceleration and brake position and control vehicle's movement with steering, acceleration and brake actuators. In this research, we designed VLDA system like as low speed cruise control system and test it on real road environments.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.218-218
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• 2000

Advanced Vehicle Control Systems(AVCS) is one of the key elements in Intelligent Transportation Systems(ITS). This paper considers the problem of longitudinal control in vehicle platoon on a straight lane of a highway. In a very simplified situation, longitudinal vehicle dynamics contains many nonlinear elements. The nonlinear characteristics are mainly composed of an engine, a torque converter, and a drag force. In this paper, sliding control, one of nonlinear control methods, is applied to longitudinal automated vehicle control for platooning. Output feedback linearization is also simulated for comparison with the sliding control. Simulations for comparative study for the adopted controllers such as sliding control and output feedback linearization are peformed under the same conditions. This Paper aims at clarifying the characteristics of sliding control and output feedback linearization.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.181-184
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• 1999

Leading vehicle states are useful and essential elements in adaptive cruise control (ACC) system, collision warning (CW) and collision avoidance (CA) system, and automated highway system (AHS). There are many approaches in ACC using Kalman filter. Mostly only distance to leading vehicle and velocity difference are estimated and used for the above systems. Applications in road vehicle in curved road need to obtain more informations such as yaw angle, steering angle which can be estimated using vision system. Since vision system is not robust to environment change, we used Kalman filter to estimate distance, velocity, yaw angle, and steering angle. Application to active tracking of target vehicle is shown.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1130-1133
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• 2003

The goal of this research is developing advanced lane detecting algorithm for unmanned vehicle. Previous lane detecting method to bring on error become of the lane loss and noise. Therefore, new algorithm developed to get exact information of lane. This algorithm can be used to AGV(Autonomous Guide Vehicle) and LSWS(Lane Departure Warning System), ACC(Adapted Cruise Control). We used 1/10 scale RC car to embody developed algorithm. A CCD camera is installed on top of vehicle. Images are transmitted to a main computer though wireless video transmitter. A main computer finds information of lane in road image. And it calculates control value of vehicle and transmit these to vehicle. This algorithm can detect in input image marked by 256 gray levels to get exact information of lane. To find the driving direction of vehicle, it search line equation by curve fitting of detected pixel. Finally, author used median filtering method to removal of noise and used characteristic part of road image for advanced of processing time.

• Journal of Power Electronics
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• v.11 no.4
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• pp.471-478
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• 2011

This paper addresses the establishment of a kVA-range plug-in hybrid electrical vehicle (PHEV) integration test platform and associated issues. Advancements in battery and power electronic technology, hybrid vehicles are becoming increasingly dependent on the electrical energy provided by the batteries. Minimal or no support by the internal combustion engine may result in the vehicle being occasionally unable to recharge the batteries during highly dynamic driving that occurs in urban areas. The inability to sustain its own energy source creates a situation where the vehicle must connect to the electrical grid in order to recharge its batteries. The effects of a large penetration of electric vehicles connected into the grid are still relatively unknown. This paper presents a novel methodology that will be utilized to study the effects of PHEV charging at the sub-transmission level. The proposed test platform utilizes the power hardware-in-the-loop (PHIL) concept in conjunction with high-fidelity PHEV energy system simulation models. The battery, in particular, is simulated utilizing a real-time digital simulator ($RTDS^{TM}$) which generates appropriate control commands to a power electronics-based voltage amplifier that interfaces via a LC-LC-type filter to a power grid. In addition, the PHEV impact is evaluated via another power electronic converter controlled through $dSPACE^{TM}$, a rapid control systems prototyping software.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.531-538
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• 2011

This paper describes a novel sensor system for 3D world modeling of an autonomous vehicle in large-scale outdoor environments. When an autonomous vehicle performs path planning and path following, well-constructed 3D world model of target environment is very important for analyze the environment and track the determined path. To generate well-construct 3D world model, we develop a novel sensor system. The proposed novel sensor system consists of two 2D laser scanners, two single cameras, a DGPS (Differential Global Positioning System) and an IMU (Inertial Measurement System). We verify the effectiveness of the proposed sensor system through experiment in large-scale outdoor environment.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.1002-1011
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• 2006

In this paper, a lateral vehicle control using the concept of control configured vehicle(CCV) is presented. The control objectives for the lateral dynamics of a vehicle include the ability to commend a chosen variable without significant motion change in other specified variables. The analysis techniques fur decoupling of the aircraft motions are utilized to develop vehicle lateral control with advanced mode. Vehicle lateral dynamic is determined to have the steering input and control torque input. The additional vehicle modes are also defined to using CCV concept. We use right eigenstructure assignment techniques and command generator tracker to design a control law for an lateral vehicle dynamics. The desired eigenvectors are chosen to achieve the desired decoupling(i.e., lateral direction speed and yaw rate). The command generator tracker is used to ensure steady-state tracking of the driver's command. Finally, the developed design is utilized by using the lateral vehicle dynamic with four wheel.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.815-818
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• 1997

In this paper, an intelligent control strategy for a mobile vehicle, based on the technology of the artificial neural network in a Neurocomputer, is presented. The mobile vehicle learned recognizing and driving knowledge by a neurocomputer. Moment Invariants computation was used to extract the shape of objects. The technologies of both neurocomputer and Neumann-type computer are applied into the control system, and make the mobile vehicle be capable of tracking designated objects and avoiding obstacles.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1181-1188
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• 2014

In this paper, we propose a novel concept foran unmanned delivery service using a cooperative heterogeneous unmanned system consisting of a self-driving car and an unmanned aerial vehicle (UAV). The proposed concept is suitable to deliver parcels in high-density and high-rise urban or residential areas. In order to achieve the proposed concept, we will develop acooperative heterogeneous unmanned system. Customers can order goods using a smartphone application and the order information, including the position of the customer and the order time, and the package is transported automatically by the unmanned systems. The system assigns the tasks suitable for each unmanned vehicle by analyzing it based on map information. Performance is validated by experiments consisting of autonomous driving and flight tests in a real environment. For more evaluation, the landing position error analysis is performed using circular error probability (CEP).