• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.15-26
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• 2013

This paper proposes a classification method of parallel, vertical parking states and pillars for parking assist system using ultrasonic sensors. Since, in general parking space detection module, the compressed amplitude of ultrasonic data are received, the analysis of them is difficult. To solve these problems, in preprocessing state, symmetric transform and noise removal are performed. In feature extraction process, four features, standard deviation of distance, reconstructed peak, standard deviation of reconstructed signal and sum of width, are proposed. Gaussian fitting model is used to reconstruct saturated peak signal and discriminability of each feature is measured. To find the best combination among these features, multi-class SVM and subset generator are used for more accurate and robust classification. The proposed method shows 92 % classification rate and proves the applicability to parking space detection modules.

• The Journal of Korea Robotics Society
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• v.15 no.2
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• pp.147-159
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• 2020

Over the last years, a number of different path following methods for the autonomous parking system have been proposed for tracking planned paths. However, it is difficult to find a study comparing path following methods for a short path length with large curvature such as a parking path. In this paper, we conduct a comparative study of the path following methods for perpendicular parking. By using Monte-Carlo simulation, we determine the optimal parameters of each controller and analyze the performance of the path following. In addition, we consider the path following error occurred at the switching point where forward and reverse paths are switched. To address this error, we conduct the comparative study of the path following methods with the one thousand switching points generated by the Monte-Carlo method. The performance of each controller is analyzed using the V-rep simulator. With the simulation results, this paper provides a deep discussion about the effectiveness and limitations of each algorithm.

• International Journal of High-Rise Buildings
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• v.3 no.2
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• pp.155-165
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• 2014

This study measured and compared the variation of ventilation rate and fan energy consumption according to various control strategies after installing wireless sensor-based pilot ventilation system in order to verify the applicability of demand-controlled ventilation (DCV) strategy that was efficient ventilation control strategy for underground parking lot. The underground parking lot pilot ventilation system controlled the ventilation rate by directly or indirectly tracking the traffic load in real-time after sensing data, using vehicle detection sensors and carbon monoxide (CO) and carbon dioxide ($CO_2$) sensor. The ventilation system has operated for 9 hours per a day. It responded real-time data every 10 minutes, providing ventilation rate in conformance with the input traffic load or contaminant level at that time. A ventilation rate of pilot ventilation system can be controlled at 8 levels. The reason is that a ventilation unit consists of 8 high-speed nozzle jet fans. This study proposed vehicle detection sensor based demand-controlled ventilation (VDS-DCV) strategy that would accurately trace direct traffic load and CO sensor based demand-controlled ventilation (CO-DCV) strategy that would indirectly estimate traffic load through the concentration of contaminants. In order to apply DCV strategy based on real-time traffic load, the minimum required ventilation rate per a single vehicle was applied. It was derived through the design ventilation rate and total parking capacity in the underground parking lot. This is because current ventilation standard established per unit floor area or unit volume of the space made it difficult to apply DCV strategy according to the real-time variation of traffic load. According to the results in this study, two DCV strategies in the underground parking lot are considered to be a good alternative approach that satisfies both energy saving and healthy indoor environment in comparison with the conventional control strategies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.591-598
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• 2016

The final step of driving a car is parking, which is the most difficult part for people learning to drive. Parking in narrow parking spaces is difficult for both ordinary drivers and beginners. To solve this problem, the development of SPAS (Smart Parking Assist System), ACC (Automatic Control System) improves the convenience of drivers. In addition, parking assistance systems have been developed to recognize more accurately the surrounding environment to the driver using the ultrasound, camera, thermal camera, and radar. This paper proposes the reverse turning radius to process images as if the camera is located in the center of the vehicle regardless of the actual camera position. In addition, it generates the parking guidelines through verification using the vehicle.

• Proceedings of the KSR Conference
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• 1999.11a
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• pp.280-287
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• 1999

An automatic train operation(ATO) system executes the operation of constant speed travelling and fixed point parking by using microprocessors instead of drivers manual operation. This paper describes the mathematical model for the train considering unknown disturbances which consist of start resistance, travelling resistance, slope resistance, curve resistance, and so on. The speed controller of ATO system is designed by considering the disturbances. The simulation is executed to verify the speed control and fixed point parking performance and to compare its performance with that of a PID-type ATO control system under disturbances. Simulation results show that the control performance of gain scheduled control scheme fur ATO system is better than that of the conventional PID controller.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.483-484
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• 2008

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.10
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• pp.259-268
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• 2018

Due to the development of cities and the increase of vehicles, effective control of parking space management service in cities is needed. However, the existing parking lot management system does not provide limited or convenient service in terms of space and time. In this paper, we propose distributed parking space management service based on large scale LPWA (Low-Power Wide-Area). The parking sensor collects parking space information from the parking lot and is transmitted over a low-power wide network. All parking data is processed and analyzed in the IoT cloud. Through a parking space management service system in all cities, users are given the temporal convenience of determining the parking space and the area efficiency of the parking space.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.434-443
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• 2008

This paper develops a novel automatic parking algorithm based on a fuzzy logic controller with the vehicle pose for the input and the steering rate for the output. It localizes the vehicle by using only external sensors - a vision sensor and ultrasonic sensors. Then it automatically learns an optimal fuzzy if-then rule set from the training data, using an evolutionary fuzzy system. Furthermore, it also finds the green zone for the ready-to-reverse position in which parking is possible just by reversing. It has been tested on a 4-wheeled Pioneer mobile robot which emulates the real vehicle.

• KIISE Transactions on Computing Practices
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• v.22 no.12
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• pp.654-662
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• 2016

With the advent of autonomous cars, we explored the problems which will soon arise while parking in car parks. These include structure of parking lot suitable for autonomous cars, finding the closest parking slot available, and navigation to the location. We provide an initial solution, wherein we use a central server and the graph of the parking lot to guide cars to the closest parking slots available. Our experiments have shown that the proposed method is effective for the controlled parking for self-driving cars.