• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.9
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• pp.1416-1423
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• 2017

Lane detection technology is one of the most important issues on car safety and self-driving capability of autonomous vehicle. This paper introduces an accurate lane detection scheme based on OCC(Optical Camera Communication) for moving vehicles. For lane detection of moving vehicles, the streetlights and the front camera of the vehicle were used for a transmitter and a receiver, respectively. Based on the angle information of multiple streetlights in a captured image, the distance from sidewalk can be calculated using non-linear regression analysis. Simulation results show that the proposed scheme shows robust performance of accurate lane detection.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06d
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• pp.428-431
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• 2008

Recently, people have been interested in new intelligent transport system (ITS) architecture, so that vehicular networks are becoming an attractive research area. When vehicles try to access data through a roadside unit (RSU), data scheduling of RSU needs to improve service ratio due to limited bandwidth and service time. In this paper, we propose a service scheduling algorithm based on transmission delays and service deadlines of vehicles in order to improve the service ratio. In our algorithm, we assume the promiscuous operation of wireless nodes and it can make a single transmission of RSU serve multiple requests. We evaluated the performance of our scheme via simulations, and results show that our schemes have better performance than existing algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.468-471
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• 2005

The Air Quality Sensor(AQS), located near the fresh air inlet, serves to reduce the amount of pollution entering the vehicle cabin through the HVAC(heating, ventilating, and air conditioning) system by sending a signal to close the fresh air inlet door/ventilation flap when the vehicle enters a high pollution area. One chip sensor module which include above two sensing elements, humidity sensor and bad odor sensor was developed for AQS (air quality sensor) in automobile. With this sensor module, PIC microcontroller was designed with back propagation neural network to reduce detecting error when the motor vehicles pass through the dense fog area. The signal from neural network was modified to control the inlet of automobile and display the result or alarm the situation. One chip microcontroller, Atmega128L (ATmega Ltd., USA) was used. For the control and display. And our developed system can intelligently detect the bad odor when the motor vehicles pass through the polluted air zone such as cattle farm.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.213-219
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• 2010

MCU(Micro Controller Unit) used for the automobiles has been required for improving of the safety and high reliability. Also, the necessity of high performance MCU equipped with high fuel-efficiency has been risen according to increased requests of high fuel-efficiency and improving the occupants safety with the development of intelligent vehicles and future vehicles. The MPC5554 32-bit embedded controller, made by Freescale Semiconductor, specialized in the part of the power train provides the high reliability, fast interrupt process and real-time control. In This paper, the investigation on IPMSM using MPC5554 has been performed. Also SVPWM(Space Vector Pulse Width Modulation) is implemented to the servo system.

• 한국ITS학회:학술대회논문집
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• 2005.11a
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• pp.83-88
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• 2005

A transportation problem in Korea is a serious issue that has to be solved urgently in the motor era of 15 million vehicles. Recently ITS has been introduced to improve efficiency of the current roads because an excessive budget and a long term construction are needed to build new roads. Therefore the government enacted the law as of ITS and the in architecture. However, these ITS information services were oriented to mainly vehicles and drivers, not public entities such as bus driver, passengers and so on. Nowadays lots of local autonomous city introduced a public transportation information system (PTIS), and providing useful information for the public. For this PTIS, important design issues are to be focused on detecting and tracking technology of moving bus, and a wireless communication link to transmit the location information. This paper presents design models using several wireless communication methods, and an implementation case using a Wireless packet Data communication Network (WDN) to transmit bus location information at Seoul, Korea.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.7
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• pp.202-213
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• 1999

Adaptive Cruise Control (ACC) is one of key features on intelligent Transportation System(ITS). In ACC, the steering is done by a driver, but the engine throttle valve and the brake are controlled electronically. The relative velocity and distance from the preceeding vehicle are measured by radars or image processing units and relevant vehicular spacing is maintained in ACC control systems. In this study, vehicle longitudinal dynamics are modeled to simulate vehicle longitudinal maneuver and to design longtitudinal controllers for ACC vehicles. The control algorithm is designed based on the modeled vehicle longitudinal dynamics using a non-linear sliding mode control method. To verity the performance of the control algorithm, a real time numerical simulation program is developed on a Silicon Graphics workstation using C-language . A real time graphic program is alos develpe and integrated with the numerical simulation program.

• Journal of Ocean Engineering and Technology
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• v.8 no.2
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• pp.131-140
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• 1994

Dynamics of AUV has heavy nonlinearities and many unknown parameters due to its bluff shape and low cruising speed. Intelligent algorithms, therefore, are required to overcome these nonlinearities and unknown system dynamics. Several identification techniques have been suggested for the application of control of underwater vehicles during last decade. This paper applies the neural network to identification and motion control problem of AUVs. Nonlinear dynamic systems of an AUV are identified using feedforward neural network. Simulation results show that the learned neural network can generate the motion of AUV. This paper, also, suggest an adaptive control scheme up-dates the controller weights with reference model and feedforward neural network using error back propagation.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.24.2-24
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• 2001

In this paper, the authors present a row dynamic route planning by Q-learning. The proposed algorithm is executed in a cellular automation based traffic simulator, which is also newly created. In Vehicle Information and Communication System(VICS), which is an active field of Intelligent Transport System(ITS), information of traffic congestion is sent to each vehicle at real time. However, a centralized navigation system is not realistic to guide millions of vehicles in a megalopolis. Autonomous distributed systems should be more flexible and scalable, and also have a chance to focus on each vehicles demand. In such systems, each vehicle can search an own optimal route. We employ Q-learning of the reinforcement learning method to search an optimal or sub-optimal route, in which route drivers can avoid traffic congestions. We find some applications of the reinforcement learning in the "static" environment, but there are ...

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1126-1130
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• 2004

This paper describes the design, development, and performance testing of an autonomous ground vehicle that was developed to participate in the DARPA Grand Challenge that was held in March 2004. The authors of this paper are members of Team CIMAR which was one of twenty five teams selected by DARPA to participate in a competition to develop an autonomous vehicle that can navigate from near Los Angeles to near Las Vegas at speeds averaging twenty miles per hour. Most of the event was held on open terrain and trails in a rocky desert environment. This paper describes the overall system design and the performance of the system at the event.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.327-330
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• 2000

In this paper, we describe an intelligent method to detect types of vehicles using Support Vector Machines focused to the Intelligent Transportation System (ITS) applications such as in the CCD based Electronic Toll Collection System (ETCS). This algorithm can be used the various fields of ITS applications. Support Vector Machines employed in this paper has been recently proposed as a very effective method for 3D image recognition. And our proposed feature extraction method using the singluar values that directly come from pixels at input images. Consequently, The low calculation load and the high recognition rate in spite of image rotation and various noises are one of merits of proposed method.