• Journal of Korea Multimedia Society
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• v.20 no.4
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• pp.649-659
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• 2017

Typically, a smart car is equipped with access to the Internet and a wireless local area network. Moreover, a smart car is equipped with a global positioning system (GPS) based navigation system that presents a map to a user for recommending the shortest path to a desired destination. This paper presents the design and implementation of a real-time shortest path search system for directed and dynamic roads. Herein, we attempt to simulate real-world road environments, while considering changes in the ratio of directed roads and in road conditions, such as traffic accidents and congestions. Further, we analyze the effect of the ratio of directed roads and road conditions on the communication cost between the server and vehicles and the arrival times of vehicles. In this study, we compare and analyze distance-based shortest path algorithms and driving time-based shortest path algorithms while varying the number of vehicles to search for the shortest path, road conditions, and ratio of directed roads.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.123-140
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• 2022

Even though driving behaviors in underground roads can be significantly different from ground roads, existing underground roads follow the design guidelines of ground roads. In this context, this study investigates the driving behaviors of the exit-ramp terminal of urban underground roads using a driving simulator. Virtual driving experiments were performed by analyzing scenarios between the underground and ground road environments. The experiments' driving behavior data for each geometry section are compared and validated through a statistical significance test. This test showed that the speed in the underground road environment is relatively low, and the LPM tends to move away from the adjacent tunnel wall. Based on these findings, this study suggests implications and feasible solutions for improving driver's safety in the exit-ramp terminal of the underground roads.

• Journal of Drive and Control
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• v.19 no.3
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• pp.23-31
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• 2022

Traffic safety issues have recently been seriously magnified, due to child deaths in apartment complexes and parking lots. Accordingly, traffic safety technologies are being developed to recognize dangerous situations on living roads and to provide warning services. In this study, a collision detection algorithm was developed to prevent collision accidents between moving objects, by using object type and location information provided from CCTV monitoring devices. To determine the exact collision between moving objects, an object movement model was developed to predict the range of movement by considering the moving characteristics of the object, and a collision detection algorithm was developed to efficiently analyze the presence and location of the collision. The developed object movement model as well as the collision detection algorithm were simulated, in a virtual space of an actual living road to verify performance and derive supplementary matters.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.4
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• pp.44-54
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• 2011

Intelligent transport services on smart roads tend to have a problem at the stage of benefit-cost analysis that can not secure economic feasibility of the new services which increase early investment cost on building its infrastructure. It is expected that the number of road accidents, 'Incident/Accident', will decline through various safety services using intelligent safety facilities, intelligent transport management and so on, and that traffic congestion will also decrease. The effect of traffic congestion reduction could be the benefit by safety improvement, however current investment-analysis process in Korea does not appropriate it as a benefit. This study estimated road blocking time with 'Incident/Accident' classification and highway accident data of past three years. It also developed a generalized model by a regression analysis with a microscopical simulation. Furthermore, it suggested necessary units on quantitative analysis in order to make the developed model applicable to investment evaluation. As a result of applying the developed model to Smart-Highway Project, it showed that total safety improvement benefit is about 139 billion dollars over 30 years when it is supposed that accident decreasing rate by smart safety facilities is 10%.

• Journal of Drive and Control
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• v.18 no.1
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• pp.9-16
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• 2021

Overloaded vehicles increase the maintenance cost of road structures, and they are a major factor in causing damage to the roads and bridges. In addition, overloaded vehicles compromise the braking capability of the vehicle; thus, threatening the safety of the driver. In order to prevent overloading of vehicles, the government is cracking down on the roads by using a device that measures the weight of vehicles. But this process is inconvenient because the place where the equipment is installed is far away from where the cargo is loaded. Due to the limitations of these fixed weighing devices, there is a growing need for technology that can monitor vehicle weight distribution and overload conditions in real time. In this work, we develop an onboard scale that can measure the load (weight) of trucks in real time. The onboard scale consists of high sensors, a signal processing unit, and a display, and it measures the load using height-displacement of the vehicle's leaf spring suspension.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.2
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• pp.9-16
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• 2022

The nodes constituting the vehicle ad hoc network (VANET) are vehicles moving along the road and road side units (RSUs) installed around the road. The vehicle ad hoc network is used to collect the status, speed, and location information of vehicles driving on the road, and to communicate with vehicles, vehicles, and RSUs. Today, as the number of vehicles continues to increase, urban roads are suffering from traffic jams, which cause various problems such as time, fuel, and the environment. In this paper, we propose a method to solve traffic congestion problems on urban roads and demonstrate that the method can be applied to solve traffic congestion problems through performance evaluation using two typical protocols of vehicle ad hoc networks, AODV and GPSR. The performance evaluation used ns-2 simulator, and the average number of traffic jams and the waiting time due to the average traffic congestion were measured. Through this, we demonstrate that the vehicle ad hoc-based traffic congestion management technique proposed in this paper can be applied to urban roads in smart cities.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.67-72
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• 2019

The self-driving cars identify appropriate navigation paths and obstacles to arrive at their destinations without human control. The autonomous cars are capable of sensing driving environments to improve driver and pedestrian safety by sharing with neighbor traffic infrastructure. In this paper, we have focused on pedestrian protection and have designed an improved localization algorithm to track mobile users on roads by interacting with smart traffic lights in vehicle environments. We developed smart traffic lights with the RSSI sensor and built the proposed method by improving the Kalman filter algorithm to localize mobile users accurately. We successfully evaluated the proposed algorithm to improve the mobile user localization with deployed five smart traffic lights.

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.353-354
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• 2014

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.4
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• pp.10-19
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• 2014

Despite the movement of safe traffic by the Korean government to reduce deaths in traffic accidents, the casualties increase year by year. In particular, more and more accidents and casualties are reported from car collisions from the back of the vehicles parked for managing traffic accidents on the road, cleaning main roads and medial strips, repairing roads. In order to response to these accidents, the government should take protective measures for road users. In the last decade, seventy-one cases have been reported to occur during highway repair and maintenance. As a result, eight persons were killed and seventy-six were injured, showing the high death rate of 11.3 percent. Therefore, it seems urgent to take some actions against it. The United States and European countries legislate that vehicles of road repair and maintenance should be mandatorily equipped with shock absorber at the back. Korea, however, does not have such legislative measures, which are needed at this time to protect workers on the road. This study compares the performance of the traditional shock absorber for road maintenance vehicles with that of the rear safety guard using air bag, manufactured in accordance with related laws in Korea. Based on the results of the 60km/h rear collision test, this paper proposes improvements in related laws and regulations in an attempt to reduce casualties.

• Smart Media Journal
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• v.6 no.3
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• pp.57-63
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• 2017

The most important, essential prerequisite for the improvement of vehicle license plate recognition is the acquisition of high-quality vehicle images. Because typical images acquired from roads are affected by different environmental factors including the time of day, sunlight, and the weather, the brightness and the shape of the license plates in the images are inconsistent. To this end, many image corrections are performed, resulting in slower recognition and lower recognition rate. Therefore, in this study, we used the images acquired from roads to test the proposed method for fast capturing of vivid, high-quality vehicle images by measuring the brightness around license plates during real-time image capturing to control in real time the factors, such as shutter speed, brightness, and gain of the camera, that affect the brightness and the quality of the images.