• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.143-148
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• 2024

Traffic congestion has caused issues in various forms such as the environment and economy. Recently, an intelligent transport system (ITS) using artificial intelligence (AI) has been focused so as to alleviate the traffic congestion problem. In this paper, we propose a reinforcement learning-based traffic signal control algorithm that can smooth the flow of traffic while reducing discomfort levels of drivers and pedestrians. By applying the proposed algorithm, it was confirmed that the discomfort levels of drivers and pedestrians can be significantly reduced compared to the existing fixed signal control system, and that the performance gap increases as the number of roads at the intersection increases.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.3
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• pp.413-418
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• 2015

As the elderly are increasing, traffic accidents which are related to the elderly are one of major issues in aged society. In this paper, we analyze traffic accident statistics for the elderly. Based on the analyzed data, safety message transmission system for the elderly pedestrians is introduced. The proposed system is based on the P2V(Pedestrian-to-Vehicle) communication which combines ICT(Information and Communication Technology) with vehicles and pedestrians. We introduce the concept and principle of the proposed system and discuss implementation issues for realizing the proposed system.

• Journal of Integrative Natural Science
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• v.12 no.4
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• pp.105-115
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• 2019

In this paper, a prediction system is proposed to control the brightness of smart street lamps by predicting the moving path through the reduction of consumption power and information of pedestrian's past moving direction while meeting the function of existing smart street lamps. The brightness of smart street lamps is adjusted by utilizing the walk tracking vector and soft hand-off characteristics obtained through the motion sensing sensor of smart street lamps. In addition, the motion vector is used to analyze and predict the pedestrian path, and the GPU is used for high-speed computation. Pedestrians were detected using adaptive Gaussian mixing, weighted difference imaging, and motion vectors, and motions of pedestrians were analyzed using the extracted motion vectors. The preprocessing process using linear interpolation is performed to improve the performance of the proposed prediction system. Fuzzy prediction system and neural network prediction system are designed in parallel to improve efficiency and rough set is used for error correction.

• ETRI Journal
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• v.45 no.5
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• pp.836-846
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• 2023

Mobile robots are used in modern life; however, object recognition is still insufficient to realize robot navigation in crowded environments. Mobile robots must rapidly and accurately recognize the movements and shapes of pedestrians to navigate safely in pedestrian-rich spaces. This study proposes real-time, accurate, three-dimensional (3D) multi-pedestrian detection and tracking using a 3D light detection and ranging (LiDAR) point cloud in crowded environments. The pedestrian detection quickly segments a sparse 3D point cloud into individual pedestrians using a lightweight convolutional autoencoder and connected-component algorithm. The multi-pedestrian tracking identifies the same pedestrians considering motion and appearance cues in continuing frames. In addition, it estimates pedestrians' dynamic movements with various patterns by adaptively mixing heterogeneous motion models. We evaluate the computational speed and accuracy of each module using the KITTI dataset. We demonstrate that our integrated system, which rapidly and accurately recognizes pedestrian movement and appearance using a sparse 3D LiDAR, is applicable for robot navigation in crowded spaces.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1556-1567
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• 2009

The death rate of pedestrian in car accidents in Korea is 2.5 times higher than the average of OECD countries'. If a system that can detect pedestrians and send alarm to drivers is built and reduces the rate, it is worth developing such a pedestrian detection system (PDS). Since the accident rate in which pedestrians are involved is higher at nighttime than in daytime, the adoption of nighttime PDS is being standardized by big auto companies. However, they are usually using night visions or multiple sensors, which are usually expensive. In this paper we suggest a method for nighttime PDS using single wide dynamic range (WDR) monochrome camera in visible spectrum band. In our experiments, pedestrians were accurately detected if only most edges of pedestrians could be obtained.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2280-2289
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• 2009

The death rate of pedestrians in car accidents in Korea is about 2.5 times higher than the average of OECD countries'. If a system that can detect pedestrians and send alarm to driver is built and reduces the rate, it is worth developing such a pedestrian detection system (PDS). Since the accident rate in which pedestrians are involved is higher at nighttime than in daytime, the adoption of nighttime PDS is being standardized by big auto companies. However, they are usually using expensive night visions or multiple sensors for their PDS. In this paper we propose a method for nighttime PDS using a monochrome visible spectrum camera. We could verify its superiority in both performance and real?time operation to existing algorithm through tests against video data taken in several different environments.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1973-1978
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• 2011

The almost existing automated pedestrian systems are not well suited to the task of counting pedestrians in outdoor environments, and little is known about their effectiveness and accuracy. In this paper, we proposed a system to count pedestrians in crowds from a outdoor camera. And we describes pedestrian counting which detects and count moving people based pixel counting. This method is intended to estimates the number of people in outdoor environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.641-647
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• 2018

Recently, CCTV, which provides video information for multiple purposes, has been transformed into an intelligent, and the range of automation applications increased using the computer vision. A highly reliable detection method must be performed for accurate recognition of pedestrians and vehicles and various methods are being studied for this purpose. In such an object detection system. In this paper, we propose a method to detect a large number of pedestrians by acquiring three characteristic information that features of color information using HSI, motion vector information and shaping information using HOG feature information of a pedestrian in a situation where a large number of pedestrians are moving. The proposed method distinguishes each pedestrian while minimizing the failure or confusion of pedestrian detection and tracking. Also when pedestrians approach or overlap, pedestrians are identified and detected using stored frame feature data.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.8
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• pp.101-109
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• 2019

Korea's transportation paradigm is shifting from a vehicle-oriented transportation plan to a pedestrian-friendly environment that emphasizes walking safety. However, the level of pedestrian traffic accidents in Korea is still high and serious. The purpose of this study is to investigate factors affecting the severity of pedestrians traffic accidents using the multilevel logistic regression model based on 2015-2017 pedestrian accidents data provided by the Traffic Accident Analysis System(TAAS). The main results of the multilevel logistic regression model showed that 89% of pedestrian traffic accidents in Seoul were explained by individual characteristics such as drivers and pedestrians, and 11% were explained by neighborhood environmental characteristics. The results are as follows : In the individual characteristics such as pedestrians and drivers, the older the pedestrians and the drivers, the higher the traffic accident severity. The severity of traffic accidents was high when the pedestrians were female and the drivers were male. In the case of accident types, traffic accidents were more serious in the cases of heavy vehicles, inclement weather, and occurring at intersections and crosswalks. The results of the neighborhood environmental characteristics are as follows. The intersection density and the crosswalk density tended to reduce the severity of traffic accidents. On the other hand, the traffic light density and the school zones were founded to related to the higher level of traffic accident severity. This study suggests that both individual and neighborhood environmental characteristics should be considered together to prevent and reduce the severity of pedestrian traffic accidents.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.564-566
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• 2015

Red traffic light indicates a different meaning, the green one. Motorists and pedestrians in the crosswalk must stop or move in accordance with a signal light. However, the probability of an accident is high if you do not see or ignore these signals. In addition to the curved pedestrian crossing installed the announcement system using an infrared sensor is difficult. In this paper, we design and implement methods of detecting pedestrians using the camera. A camera installed on the pontoon walking up the pedestrian and the pedestrian detection range is set through the image. With the proposed system it is effective in detecting pedestrians in the crosswalk curved.