• KIISE Transactions on Computing Practices
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• v.22 no.11
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• pp.576-582
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• 2016

Currently, every person possesses a smart phone due to the development of the IT industry. However, crosswalk pedestrian accidents have been sharply increasing due to smart phone use. If a traffic light can recognize smart phones when a smart-phone user approaches and arrives at a given sign, many accidents could be reduced by using beacon signals. Before the era of smart phones, the accident rate involving cell phone use was relatively low. Nevertheless, when considering the development of IT equipment that produces a threat to human life, government cannot regulate smart phone use outside. The purpose of this paper is to indirectly warn a smart phone user in order to reduce the accident rates.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.1-7
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• 2020

This study is a study on the development of AEBS test scenarios for traffic accidents in Korea, and was compared and analyzed using the Traffic Accident Analysis Program. To ensure the safety of passengers and pedestrians in traffic accidents, the number of cars equipped with ADAS is increasing rapidly at all car manufacturers in each country. For traffic accidents used in this study, the domestic traffic accident database (ACCC) produced by SAMSONG was used. Domestic traffic accidents differ from overseas traffic accidents in terms of road type, signal system, driver's seat location and number of vehicles. ACCC databases, which supplemented and reinforced these differences, built a database based on the PC-CRASH program. In the study, we analyze the types of accidents to develop comparative scenarios for each type of road and collision type of traffic accidents. When the road types of traffic accidents in Korea were divided into five types and the collision types were divided into six, it was confirmed that the most types of FRONT-SIDE crashes appeared at the intersection. It is expected that the frequency of possible traffic accidents and collision types can be predicted according to the road type in the accident database, we that it can be used as an AEBS test scenario development suitable for the domestic road environment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.97-105
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• 2020

Recently, for a smart city, there is a demand for a technology for acquiring traffic information using an intelligent road infrastructure and managing it. In the meantime, various technologies such as loop detectors, ultrasonic detectors, and image detectors have been used to analyze road traffic information but these have difficulty in collecting various informations, such as traffic density and length of a queue required for building a traffic information DB for moving vehicles. Therefore, in this paper, assuming a smart city built on the basis of a camera infrastructure such as intelligent CCTV on the road, a solution for calculating the traffic DB of moving vehicles using Vision Tracking of road CCTV cameras is presented. Simulation and verification of basic performance were conducted and solution can be usefully utilized in related fields as a new intelligent traffic DB calculation solution that reflects the environment of road-mounted CCTV cameras and moving vehicles in a variable smart city road environment. It is expected to be there.

• Smart Structures and Systems
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• v.5 no.1
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• pp.43-54
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• 2009

This study introduces a novel approach for locating damage in a structure using wireless sensor system with local level computational capability to alleviate data traffic load on the centralized computation. Smart wireless sensor systems, capable of iterative damage-searching, mimic an optimization process in a decentralized way. The proposed algorithm tries to detect damage in a structure by monitoring abnormal increases in strain measurements from a group of wireless sensors. Initially, this clustering technique provides a reasonably effective sensor placement within a structure. Sensor clustering also assigns a certain number of master sensors in each cluster so that they can constantly monitor the structural health of a structure. By adopting a voting system, a group of wireless sensors iteratively forages for a damage location as they can be activated as needed. Since all of the damage searching process occurs within a small group of wireless sensors, no global control or data traffic to a central system is required. Numerical simulation demonstrates that the newly developed searching algorithm implemented on wireless sensors successfully localizes stiffness damage in a plate through the local level reconfigurable function of smart sensors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.8
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• pp.667-673
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• 2014

In a smart shipyard area, it is possible to integrate a variety of ship modules from separate sites into a final ship construction by using mobile applications. In this paper, we proposed the LTE femtocell network configuration which is applicable to sub shipyard, the traffic exchange method with shipyard headquarter and offload method to separate the general traffic. We defined the mode change in a femtocell gateway for supporting offload for general traffic between the main server in shipyard headquarter and sub shipyard, the offload data managements and message definition. We check the transmitted/received message flow in the wireless link, and consider the performance of the proposed method using state the transition diagram. It is expected that our results can improve the productivity within a smart shipyard by mobile communications and LTE femtocell network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.2
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• pp.75-85
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• 2014

Recently, mobile SNS traffic has increased tremendously due to the deployment of smart devices such as smart phones and smart tablets. In this paper, mobile integrated SNS gateway is proposed to cope with massive SNS traffic. Most of mobile SNS applications update the information with individual connection to the corresponding servers. The proposed gateway integrates these applications. It is for reducing SNS traffic caused by continuous data request and improving the mobile communication performance. The key elements of the mobile integrated SNS gateway are the synchronization, cache and integrated certification. The proposed protocol and gateway system have implemented on the testbed which deployed on the real network to evaluate the performance of the proposed gateway. Finally, we present the caching performance of gateway system implementation.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.1
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• pp.1-7
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• 2012

This paper presents a system used to automatically recognize the road traffic control gestures of police officers. In this approach,the control gestures of traffic police officers are captured in the form of depth images.A human skeleton is then constructed using a kinematic model. The feature vector describing a traffic control gesture is built from the relative angles found amongst the joints of the constructed human skeleton. We utilize Support Vector Machines (SVMs) to perform the gesture recognition. Experiments show that our proposed method is robust and efficient and is suitable for real-time application. We also present a testbed system based on the SVMs trained data for real-time traffic gesture recognition.

• Journal of Information Processing Systems
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• v.4 no.2
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• pp.41-52
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• 2008

In this paper, we discuss a novel reservation-based, asynchronous MAC protocol called 'Multi-rate Multi-hop MAC Protocol' (MMMP) for multi-hop ad hoc networks that provides QoS guarantees for multimedia traffic. MMMP achieves this by providing service differentiation for multirate real-time traffic (both constant and variable bit rate traffic) and guaranteeing a bounded end-to-end delay for the same while still catering to the throughput requirements of non real time traffic. In addition, it administers bandwidth preservation via a feature called 'Smart Drop' and implements efficient bandwidth usage through a mechanism called 'Release Bandwidth'. Simulation results on the QualNet simulator indicate that MMMP outperforms IEEE 802.11 on all performance metrics and can efficiently handle a large range of traffic intensity. It also outperforms other similar state-of-the-art MAC protocols.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.501-509
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• 2004

The frequency of car accidents is very high at the intersection. Because of the state of a traffic signal, quarrels happen after accidents. At night many cars run away after causing an accident. In this case, accident analyses have been conducted by investigating evidences such as eyewitness accounts, tire tracks, fragments of the car or collision traces of the car. But these evidences that don't have enough objectivity cause an error in judgment. In the paper, when traffic accidents happen, the traffic accident detection system that stands on the basis of images and sounds detects traffic accidents to acquire abundant evidences. And, this system transmits 10 seconds images to the traffic center through the wired net and stores images to the Smart Media Card. This can be applied to various ways such as accident management, accident DB construction, urgent rescue after awaring the accident, accident detection in tunnel and in inclement weather.

• ETRI Journal
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• v.44 no.2
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• pp.194-207
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• 2022

In the last decade, substantial progress has been achieved in intelligent traffic control technologies to overcome consistent difficulties of traffic congestion and its adverse effect on smart cities. Edge computing is one such advanced progress facilitating real-time data transmission among vehicles and roadside units to mitigate congestion. An edge computing-based deep reinforcement learning system is demonstrated in this study that appropriately designs a multiobjective reward function for optimizing different objectives. The system seeks to overcome the challenge of evaluating actions with a simple numerical reward. The selection of reward functions has a significant impact on agents' ability to acquire the ideal behavior for managing multiple traffic signals in a large-scale road network. To ascertain effective reward functions, the agent is trained withusing the proximal policy optimization method in several deep neural network models, including the state-of-the-art transformer network. The system is verified using both hypothetical scenarios and real-world traffic maps. The comprehensive simulation outcomes demonstrate the potency of the suggested reward functions.