• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.147-152
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• 2005

This study firstly developed a tool for evaluating performance requirements of automatic vehicle identification (AVI) techniques. A microscopic traffic simulator, Paramics, was employed to investigate the effects of AVI performances on the accuracy of estimating section travel times. Mote Carlo simulation approach was incorporated into Paramics to conduct systematic evaluations of identifying required AVI performances. The proposed method in this study can serve as a logical and necessary precursor to field implementation of a variety of AVI techniques toward achieving more reliable traffic information.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.889-899
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• 2021

This paper proposes a reliable data sharing scheme on the internet of vehicles (IoV) by utilizing blockchain technology for constructing a decentralized system approach. In our model, to maintain the credibility of the information messages sent by the vehicles to the system, we propose a reputation rating mechanism, in which neighboring vehicles validate every received information message. Furthermore, we incorporate an incentive mechanism based on smart contracts, so that vehicles will get certain rewards from the system when they share correct traffic information messages. We simulated the IoV network using a discrete event simulator to analyze network performance, whereas the incentive model is designed by leveraging the smart contract available in the Ethereum platform.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.125-132
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• 2017

Vehicular safety service reduces traffic accidents and traffic congestion by informing drivers in advance of threats that may occur while driving using vehicle-to-vehicle (V2V) communications in a wireless environment. For vehicle safety services, every vehicle must broadcasts a Basic Safety Message(BSM) periodically. In congested traffic areas, however, network congestion can easily happen, reduce the message delivery ratio, increase end-to-end delay and destabilize vehicular safety service system. In this paper, to solve the network congestion problem in vehicle safety communications, we approximate the relationship between channel busy ratio and the number of vehicles and use it to estimate the total network congestion. We propose a new context-aware transmit power control algorithm which controls the transmission power based on total network congestion. The performance of the proposed algorithm is evaluated using Qualnet, a network simulator. As a result, the estimation of total network congestion is accurately approximated except in specific scenarios, and the packet error rate in vehicle safety communication is reduced through transmit power control.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.109-123
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• 2024

Research into vision-based end-to-end autonomous driving systems utilizing deep learning and reinforcement learning has been steadily increasing. These systems typically encode continuous and high-dimensional vehicle states, such as location, velocity, orientation, and sensor data, into latent features, which are then decoded into a vehicular control policy. The complexity of urban driving environments necessitates the use of state representation learning through networks like Variational Autoencoders (VAEs) or Convolutional Neural Networks (CNNs). This paper analyzes the impact of different image state encoding methods on reinforcement learning performance in autonomous driving. Experiments were conducted in the CARLA simulator using RGB images and semantically segmented images captured by the vehicle's front camera. These images were encoded using VAE and Vision Transformer (ViT) networks. The study examines how these networks influence the agents' learning outcomes and experimentally demonstrates the role of each state representation technique in enhancing the learning efficiency and decision- making capabilities of autonomous driving systems.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.1
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• pp.9-16
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• 2011

Research on ISA(Integrated Starter/Alternator) receives wide attention as system voltage is increased to 42V Based on requirement of starter and alternator for the conventional vehicle, system requirement and specification are determined. Also to control proposed system, suitable control methods are proposed. Main control issues with ISA are whether torque assist is required and if so how much torque is needed. In this paper, vehicle performance with various control methods and capacity are simulated and simulation results are analyzed. Vehicle performance is analyzed with vehicle simulator. For the simulation, suitable ISA model is also developed.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.133-142
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• 2008

AGV systems are widely used to increase the flexibility and the efficiency of the material handling systems. AGV systems are one of critical factors which determine the overall performance of the manufacturing systems. To this end, the optimal design for AGV systems is essential. Commercial simulation software is often used as an analysis tool during the design of AGV systems, however a series of procedures are desirable to simplify the analysis processes. In this paper, we present and develop the architecture for unidirectional AGV systems simulator which is able to consider approximate optimal unidirectional flow path and various operational parameters. The designed AGV systems simulator is based on JAVA, and it is developed to support designing approximate optimal unidirectional network by using Tabu search method. In addition, it enables users to design and evaluate AGV systems and to analyze alternative solutions easily. Simulation engine is consists of layout designer, AGV operation plan designer, and integrated AGVS layout designer. Users enter their system design/operation information into input window, then the entered information is automatically utilized for modeling and simulating AGV systems in simulation engine. By this series of procedures, users can get the feed back quickly.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.79-94
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• 2021

A GNSS receiver installed in autonomous vehicles is the most essential device for its navigation. However, if an intentional jamming signal is generated, there is a risk of exposure to an accident risk due to deterioration of the GNSS sensor's performance. Research is required to prevent this, and accordingly, a jamming generating device must be provided. However, according to the provisions of the law related to jamming, this is illegal. In this paper, we implement an in-vehicle jamming device that complies with the provisions of the law and does not affect the surrounding GNSS sensors. Driving simulation is used to evaluate the performance of the GNSS algorithm, and the malfunction of autonomous vehicles occurring in the interference environment and data errors output from the GNSS sensor are analyzed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.3
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• pp.169-179
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• 2014

For vehicle safety-related services using wireless communications, reliable collection of various driving informations transmitted periodically by neighbor vehicles is the most important. Every host vehicle analyses them to estimate a potential dangerous situation in a very short time and warns drivers to prevent an accident. However tremendous amount of periodic messages can cause the wireless communication in chaos and the services not in safe. In this paper, we propose a time-division broadcasting protocol to mitigate the communication congestion. It utilizes the received information of vehicle velocity and location, i.e. vehicle traffic density on a road to adjust the number of time slots in a given broadcasting period, and transmission power. The simulation results show that message reception ratio is changed to approximately 40% and channel access time also decreased from 10ms to 0.23ms.

• Journal of IKEEE
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• v.27 no.4
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• pp.379-385
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• 2023

Distributed congestion control (DCC) is a technology that mitigates channel congestion and improves communication performance in high-density vehicular networks. Traditional DCC techniques operate to reduce channel congestion without considering quality of service (QoS) requirements. Such design of DCC algorithms can lead to excessive DCC actions, potentially degrading other aspects of QoS. To address this issue, we propose a deep reinforcement learning-based QoS-adaptive DCC algorithm. The simulation was conducted using a quasi-real environment simulator, generating dynamic vehicular densities for evaluation. The simulation results indicate that our proposed DCC algorithm achieves results closer to the targeted QoS compared to existing DCC algorithms.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.468-469
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• 2008

항공기, 차량, 고속의 비행체 등과 같은 동적인 플랫폼에서 표적을 추적하기 위한 영상 추적 시스템은 시선을 안정화하는 외부의 추적루프와 내부의 안정화 루프를 포함하는 구조로 되어 있다. 2축 김발을 사용하는 영상 추적 시스템의 추적루프는 크게 영상 추적기, 추적 제어기, 안정화 루프 등으로 구성되어 있다. 본 논문에서는 영상 추적 시스템의 추적 제어기를 설계하여 성능을 분석하고, 또한 설계된 제어기를 적용하여 영상 추적기의 시간지연에 의한 추적 루프 특성을 분석하였다. 마지막으로 설계된 추적 제어기를 영상 추적 시스템 시뮬레이터에 적용하여 고기동 고속의 비행체 환경에서 추적 루프 성능을 분석하였다.