• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.10
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• pp.17-26
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• 2010

This is concerned with the technology to monitor the vehicle operation, failure and disorder by using WiBro portable device. More precisely, the technology makes it possible that the information collection device is connected to both ECU(Electronic Control Unit) which is the device for controlling engine, transmission, brake, air-bag, etc that are connected to in-vehicle network and OBD-II connector that is for data collection from various sensors. In addition, with a WiBro portable device (cell phone, PDA, PMP, UMPC, etc). equipped with a vehicle diagnostic programs, information for operation, failure and malfunction can be obtained and analyzed in real-time, and alarm is alerted when the vehicle is in abnormal status, which makes the early reactions to the status. Furthermore, the collected data can be sent through WiBro network to the server managed by the company specialized in managing the vehicles, thus the technology could help the drivers who have less knowledge about their auto-vehicles have safe and economic driving. There is always a possibility of malfunction due to various types of noise that are caused by wring-harness when the device is wired-connected. In this research, in order to overcome this problem, we propose a system configuration that can do monitoring and diagnosis with a device for collecting data from vehicle and a personal WiBro device. Also, we performed research on data acquisition and interlock for the system defined by the definition for information and data sharing platform.

• Advances in nano research
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• v.13 no.6
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• pp.587-597
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• 2022

In the present study, a novel optimization method in formation control of multi -system vehicles based on the trajectory of the nearest neighbor trajectory is presented. In this regard, the state equations of each vehicle and multisystem is derived and the optimization scheme based on minimizing the differences between actual positions and desired positions of the vehicles are conducted. This formation control is a position-based decentralized model. The trajectory of the nearest neighbor are optimized based on the current position and state of the vehicle. This approach aids the whole multi-agent system to be optimized on their trajectory. Furthermore, to overcome the cumulative errors and maintain stability in the network a semi-centralized scheme is designed for the purpose of checking vehicle position to its predefined trajectory. The model is implemented in Matlab software and the results for different initial state and different trajectory definition are presented. In addition, to avoid collision avoidance and maintain the distances between vehicles agents at a predefined desired distances. In this regard, a neural fuzzy network is defined to be utilized in conjunction with the control system to avoid collision between vehicles. The outcome reveals that the model has acceptable stability and accuracy.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.584-593
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• 2012

This paper introduces an AVP (Automated Valet Parking) system which applies an autonomous driving concept into the current PAS (Parking Assistant System). The present commercial PAS technology is limited into vehicle. It means vehicle only senses and controls by and for itself to assist the parking. Therefore, the present PAS is restricted to simple parking events. But AVP includes wider parking events and planning because it uses infra-sensor network as well as vehicle sensor. For the realization of AVP, the commercial steering system of a compact vehicle was modified into steer-by-wire structure and various sensors like LRF (Long Range Finder) and camera were installed in a parking area. And local & global server decides where and when the vehicle can go and park in the testing area after recognized the status of environment and vehicle from those sensors. GPS solution was used to validate the AVP performance. More various parking situations, vehicles and obstacles will be considered in the next research stages based on these results. And we expect this AVP solution with more intelligent vehicles can be applied in a big parking lot like a market, an amusement park, etc.

• The KIPS Transactions:PartB
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• v.15B no.1
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• pp.1-8
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• 2008

Generally, moving objects in surveillance video are extracted by background subtraction or frame difference method. However, moving cast shadows on object distort extracted figures which cause serious detection problems. Especially, analyzing vehicle information in video frames from a fixed surveillance camera on road, we obtain inaccurate results by shadow which vehicle causes. So, Shadow Elimination is essential to extract right objects from frames in surveillance video. And we use shadow removal algorithm for vehicle classification. In our paper, as we suppress moving cast shadow in object, we efficiently discriminate vehicle types. After we fit new object of shadow-removed object as three dimension object, we use extracted attributes for supervised learning to classify vehicle types. In experiment, we use 3 learning methods {IBL, C4.5, NN(Neural Network)} so that we evaluate the result of vehicle classification by shadow elimination.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.641-647
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• 2009

In this paper, a new filtering scheme for adaptive cruise control (ACC) system is presented. In the proposed scheme, the identification of the mode of the preceding vehicle is considered as a classification problem and it is done by a neural network classifier. The neural network classifier outputs a posterior probability of the mode of the preceding vehicle and the probability is directly used in the IMM framework. Finally, ten scenarios are made and the proposed NIMM is tested on them to show its validity.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.915-919
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• 2005

It is materialized an unmanned vehicle system as a part of Intelligent Transportation System (ITS) which is a fundamental constituent for unmanned vehicle. Remote control system, monitoring system and remote operating system which are consisted of unmanned vehicle system. Network program by TCP/IP socket, and real-time control & operating controlled by servo-motors from a remote place, those are used to verify safety and stability of the unmanned vehicle system in this research. This unmanned vehicle is divided into two major sections which are an unmanned vehicle part and control station part. The server PC is installed on the unmanned vehicle and a client PC is installed at a remote place, which can control the u manned vehicle. In this research work, main theme is that we experimented and tested to check the speed and utilization of the wireless LAN communication.

• Korean System Dynamics Review
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• v.8 no.2
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• pp.5-23
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• 2007

According to the system dynamics model of this study, if there is a significant network effect on vehicle operating costs, it is difficult to achieve the shift to AFV even in the long term without a policy intervention because the car market is locked in to the current structure. Network effect can be caused by an increasing return to scale in fuel supply sector as well as in maintenance service sector. It is also related to the fact that the reliability and awareness of consumers on new products increases with the growth of the market share of the new products. There are several possible policy options to break the 'locked in' structure of car market, such as subsidy on vehicle price (capital cost), subsidy on fuel (operating cost) and niche management policy. Combined policy options would be more effective than relying on a single policy option to increase the market share of AFV.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.5098-5115
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• 2017

A number of automotive electronics-safety, driver assistance, and infotainment devices-have been deployed in recent vehicles. This raises new challenges regarding in-vehicular network arbitration. A performance analysis of non-destructive arbitration has revealed a fairness issue. The arbitration prioritizes without collisions, despite multiple simultaneous transmissions; however, the performances of the highest priority node and the lowest priority node are very different. In this paper, an ID-rotation arbitration method to solve the arbitration-fairness problem is proposed. The proposed algorithm was applied to several engine control units (ECUs), including a controller area network (CAN) controller. Experimental results showed that the algorithm improved the fairness as well as the total throughput within a specific performance constraint.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.741-746
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• 2001

This paper presents an investigation of a vehicle-to-vehicle distance control using a Hardware-in-the-Loop Simulation(HiLS) system. Since vehicle tests are costly and time consuming, how to establish a efficient and low cost development tool is an important issue. The HiLS system consists of a stepper motor, an electronic vacuum booster, a controller unit and two computers which are used to form real time simulation and to save vehicle parameters and signals of actuator through a CAN(Controller Area Network). Adoption of a CAN for communication is a trend in the automotive industry. Since this environment is the same as that of a real vehicle, a distance control logic verified in laboratory can be easily transfered to a test vehicle.

• Journal of the Korea Institute of Military Science and Technology
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• v.4 no.2
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• pp.30-41
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• 2001

In Underwater Flight Vehicle depth control system, the followings must be required. First, It needs a robust performance which can get over the nonlinear characteristics due to hull shape. Second, It needs an accurate performance which has the small overshoot phenomenon and steady state error to avoid colliding with ground surface and obstacles. Third, It needs a continuous control input to reduce the acoustic noise. Finally, It needs an effective interpolation method which can reduce the dependency of control parameters on speed. To solve these problems, we propose a Intelligence depth control method using Fuzzy Sliding Mode Controller and Neural Network Interpolator. Simulation results show the proposed control scheme has robust and accurate performance by continuous control input and has no speed dependency problem.