• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.4
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• pp.180-189
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• 2009

Currently, most automobile companies are interested in research on intelligent autonomous vehicle. They are mainly focused on driver's intelligent assistant and driver replacement. In order to develop an autonomous vehicle, lateral and longitudinal control is necessary. This paper presents a lateral and longitudinal control system for autonomous vehicle that has only mono-vision camera. For lane detection, we present a new lane detection algorithm using clothoid parabolic road model. The proposed algorithm in compared with three other methods such as virtual line method, gradient method and hough transform method, in terms of lane detection ratio. For adaptive control, we apply a vanishing point estimation to fuzzy control. In order to improve handling and stability of the vehicle, the modeling errors between steering angle and predicted vanishing point are controlled to be minimized. So, we established a fuzzy rule of membership functions of inputs (vanishing point and differential vanishing point) and output (steering angle). For simulation, we developed 1/8 size robot (equipped with mono-vision system) of the actual vehicle and tested it in the athletics track of 400 meter. Through the test, we prove that our proposed method outperforms 98 % in terms of detection rate in normal condition. Compared with virtual line method, gradient method and hough transform method, our method also has good performance in the case of clear, fog and rain weather.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.3
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• pp.79-84
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• 2011

In this paper, we analyzed performance of vehicle detection for ITS (Intelligent Transport System) applications. We simulated the vehicle detection at Hi-Pass System is based on DSRC (Dedicated Short Range Communication). DSRC is a wireless network using ITS, including GPS (Global Positioning System) satellites in conjunction with the national transportation system. The system performance is evaluated in terms of bit error probability. In the simulation, the vehicle speed is set at 60 km/h and carrier frequency is 5.8 GHz. Wireless channel is modeled as the Rician fading channel. In the transmitter, the ASK (amplitude shift keying) modulation scheme is applied. From simulation results, we confirmed that performance of applied Alamouti scheme is better than other systems.

• Journal of Sensor Science and Technology
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• v.18 no.5
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• pp.385-392
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• 2009

This paper describes the algorithm development of a new body pressure detection sensor for occupant classification system. U.S. Government has required that advanced airbag system should be installed to every automobiles after 2006 according to FMVSS 208 regulation. Therefore, Occupant Classification System should be provided the passenger with safety in order to protect the infants or children that sit in the front passenger seat. When an occupant sits on the chair of the vehicle, deployment of the airbag depends on passenger's weigh distribution and postures. Authors have been developed a new pattern recognition of passenger and weight distribution at the same time by Force Sensing Resistor for the safety.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2209-2221
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• 2023

As the supply of electric vehicles increases, research on wireless charging methods for convenience has been increasing. Because the electric vehicle wireless transmission device is installed on the ground and the electric vehicle battery is installed on the floor of the vehicle, the transmission and reception antennas are approximately 15-30 cm away, and thus strong magnetic fields are exposed during wireless charging. When a metallic foreign object is placed in the magnetic field area, an eddy current is induced to the metallic foreign object, and heat is generated, creating danger of fire and burns. Therefore, this study proposes a method to detect metallic foreign objects in the magnetic field area of a wireless electric vehicle charging system. An active detection-only coil array was used, and an LC resonance circuit was constructed for the frequency of the supply power signal. When a metallic foreign object is inserted into the charging zone, the characteristics of the resonance circuit are broken, and the magnitude and phase of the voltage signal at both ends of the capacitor are changed. It was confirmed that the proposed method has about 1.5 times more change than the method of comparing the voltage magnitude at one node.

• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.30-39
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• 2007

This paper is concerned with development of system to detect an obstructive vehicle which is an essential prerequisite for autonomous driving system of ASV(Advanced Safety Vehicle). First, the boundary of driving lanes is detected by a Kalman filter through the front image obtained by a CCD camera. Then, lanes are recognized by regression analysis of the detected boundary. Second, parameters of road curvature within the detected lane are used as input in error-BP algorithm to recognize the driving direction. Finally, an obstructive vehicle that enters into the detection region can be detected through setting detection fields of the front and lateral side. The experimental results showed that the proposed system has high accuracy more than 90% in the recognition rate of driving direction and the detection rate of an obstructive vehicle.

• International Journal of Highway Engineering
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• v.10 no.3
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• pp.19-31
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• 2008

Video image processing systems(VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on wide-area detection, i.e., multi-lane surveillance algorithm provide traffic parameters with single camera such as flow and velocity, as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. The objective of this research was to relate traffic safety to VIPS tracking and this paper has developed a computer vision system of monitoring individual vehicle trajectories based on image processing, and offer the detailed information, for example, volumes, speed, and occupancy rate as well as traffic information via tripwire image detectors. Also the developed system has been verified by comparing with commercial VIP detectors.

• Journal of information and communication convergence engineering
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• v.18 no.3
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• pp.147-154
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• 2020

In this study, we created a system that can determine the number of vehicles entering and departing a charging station in real time for solving waiting time problems during refueling. Accordingly, we use the You Only Look Once object detection algorithm to detect and count the number of vehicles in the charging station and send the data to the Firebase Realtime Database. The result is shown using an Android application that provides a map function with the Kakao Maps API at the user interface side. Our system has an accuracy of 91% and an average response time of 3.1 s. Therefore, this system can be used by drivers to determine the availability of a charging station and to identify the charging station with the least waiting time for charging their vehicle.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.178-185
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• 1999

Recently, Collision Warning System is developed to improve vehicle safety. This system chiefly uses radar. But the detected vehicle from radar must be decide whether it is the vehicle in the same lane of my vehicle or not. Therefore, Vision System is needed to detect traffic lane. As a preparative step, this study presents the development of algorithm to recognize traffic lane curve direction. That is, the Neural Network that can recognize traffic lane curve direction is constructed by using the information of short distance, middle distance, and decline of traffic lane. For this procedure, the relation between used information and traffic lane curve direction must be analyzed. As the result of application to sampled 2,000 frames, the rate of success is over 90%.t text here.

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.1
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• pp.32-39
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• 2016

Intelligent Transport Systems (Intelligent Transportation System: ITS) is a system for inducing a flow of ideal car for using the most advanced technology, it is determined the status of the road, and take appropriate action. In order to be measured at various time points, and is managed, the information about the traffic situation is used image using a computer mainly. The image processing using a computer, it is an easy way to collect parameters of the various traffic in real time, technology has developed more and more. Vehicle detection of transport parameters of intelligent transportation system is a very important technology basically. Therefore, technology detection method using car background images and the contour line extraction method using an edge is used, however, problems have been raised on the accuracy of the detection rate.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.11-16
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• 2019

This paper suggests an algorithm for detecting fault of longitudinal controller in autonomous vehicles. Guaranteeing safety in fault situation is essential because electronic devices in vehicle are dependent each other. Several methods like alarm to driver, ceding control to driver, and emergency stop are considered to cope with fault. This research investigates the fault monitoring process in fail-safe system, for controller which is responsible for accelerating and decelerating control in vehicle. Residual is computed using desired acceleration control command and actual acceleration, and detection of its abnormal increase leads to the decision that system has fault. Before computing residual for controller, health monitoring process of acceleration signal is performed using hardware and analytic redundancy. In fault monitoring process for controller, a process model which is fitted using driving data is considered to improve the performance. This algorithm is simulated via MATLAB tool to verify performance.