• International journal of advanced smart convergence
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• v.12 no.2
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• pp.47-55
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• 2023

The automotive industry is undergoing a paradigm shift due to the convergence of IT and rapid digital transformation. Various components, including embedded structures and systems with complex architectures that incorporate IC semiconductors, are being integrated and modularized. As a result, there has been a significant increase in vehicle defects, raising expectations for the quality of automotive parts. As more and more data is being accumulated, there is an active effort to go beyond traditional reliability analysis methods and apply machine learning models based on the accumulated big data. However, there are still not many cases where machine learning is used in product development to identify factors of defects in performance and durability of products and incorporate feedback into the design to improve product quality. In this paper, we applied a prediction algorithm to the defects of automotive door devices equipped with automatic responsive sensors, which are commonly installed in recent electric and hydrogen vehicles. To do so, we selected test items, built a measurement emulation system for data acquisition, and conducted comparative evaluations by applying different machine learning algorithms to the measured data. The results in terms of R² score were as follows: Ordinary multiple regression 0.96, Ridge regression 0.95, Lasso regression 0.89, Elastic regression 0.91.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.4
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• pp.256-265
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• 2023

This paper describes the results of the development of the submarine Free Running Model (FRM). First, the goal of development was set based on the test conditions and the test environment, and the system was obtained accordingly. The target submarine, Joubert BB2 submarine, was selected with a scale of 18.35 in accordance with the development goal. In order to conduct a submarine FRM test underwater, where communication is impossible, the FRM must operate at least semi-autonomously. For this purpose, an Extended Kalman Filter (EKF) based underwater integrated navigation system and control system using a sailplane and an X-shaped sternplane were designed respectively. In addition, a ballast system was designed to enable the model to float to the water surface in case of an emergency. To verify its propulsion, navigation, and control performance, the FRM tests were conducted in both indoor and outdoor basins. As a result, the relationship between propeller RPM and vehicle speed was derived, and it was confirmed that the navigation and control performance met the target value.

• Smart Structures and Systems
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• v.31 no.3
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• pp.301-309
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• 2023

Tilt is a key indicator of structural safety. Real-time monitoring of tilt responses helps to evaluate structural condition, enable cost-effective maintenance, and enhance lifetime resilience. This paper presents a prototype wireless sensing system for structural tilt measurement. Long range (LoRa) technology is adopted by the sensing system to offer long-range wireless communication with low power consumption. The sensor integrates a gyroscope and an accelerometer as the sensing module. Although tilt can be estimated from the gyroscope or the accelerometer measurements, these estimates suffer from either drift issue or high noise. To address this challenging issue and obtain more reliable tilt results, two sensor fusion algorithms, the complementary filter and the Kalman filter, are investigated to fully exploit the advantages of both gyroscope and accelerometer measurements. Numerical simulation is carried out to validate and compare the sensor fusion algorithms. Laboratory experiment is conducted on a simply supported beam under moving vehicle load to further investigate the performance of the proposed wireless tilt sensing system.

• 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.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.346-350
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• 2023

Trajectory prediction is an essential element for driving autonomous vehicles, and various trajectory prediction models have emerged with the development of deep learning technology. Convolutional neural network (CNN) is the most commonly used neural network architecture for extracting the features of visual images, and the latest models exhibit high performances. This study was conducted to identify an efficient CNN backbone model among the components of deep learning models for trajectory prediction. We changed the existing CNN backbone network of multiple-trajectory prediction models used as feature extractors to various state-of-the-art CNN models. The experiment was conducted using nuScenes, which is a dataset used for the development of autonomous vehicles. The results of each model were compared using frequently used evaluation metrics for trajectory prediction. Analyzing the impact of the backbone can improve the performance of the trajectory prediction task. Investigating the influence of the backbone on multiple deep learning models can be a future challenge.

• Journal of the Korea Safety Management & Science
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• v.26 no.2
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• pp.55-64
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• 2024

As the distribution of vehicles and logistics increases due to the development of human civilization and the increase in population, various roads play an important role in domestic traffic and transportation. However, the recent emergence of large cities and new cities is causing traffic problems, and the increase in roads is inevitable for the smooth distribution of vehicles and logistics. In Korea, mountainous regions occupy 70% of the country, so tunnels are used to open roads. Without this, it is difficult to open the road. Currently, there are 3,720tunnels (as of December 31, 2023) installed on high-speed national highways, general national highways, and local roads nationwide, with a length of 2.499 and increasing every year. Accordingly, fire accidents in tunnels will also increase, and due to the nature of tunnel fire accidents, there is a high probability that they will escalate into large-scale disasters, resulting in casualties and property damage, as well as significant social losses due to the disruption of logistics transportation, etc. As the possibility of potential hazards is increasing, the purpose of this study is to build a safe and efficient tunnel system by optimizing maintenance and management for fire and disaster accidents in tunnels.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.6
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• pp.48-56
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• 2008

This study provides to car driver with car exhaust gas and sensor information which are car trouble code in engine and many sensors when the car has some problems. This is to provide car manager with many information of car sensors when we go to vehicle maintenance. For example, information of engine RPM, fuel system, intake air temperature, air flow sensors and oxygen sensors can provide to owner or garage, and also add to multimedia system for mp3 files and video files. This system consists of embedded linux system of low power while driving the car which uses OBD-II protocols and zigbee communication interface from CAN communication of car system to self-diagnosis embedded system of car. Finally, low power embedded system has a lot of application and OBD-II protocols for embedded linux system and CAN communication which get sensor informations of car control sensor system while driving the car.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1207-1214
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• 2014

Recently it has become easier to figure out cargo positional information by using GPS(Global Positioning System) and wireless communication technology. The acceleration of globalization in the shipping logistics is ever more increasing the need to provide visibility, traceability and real time informations of entry, departure of vessel including cargo and status of logistic vehicle entry into each logistic base. Providing such positional information to logistics party by using wireless communication technology can bring effective operation of supply chain and reduction in logistics costs. In the previous paper, I suggested a global location tracking system based on GPS data in global shipping logistics by means of software using GPS data. However, the previous system had a problem of being inadequate to figure out a real time location movement information and was unsatisfactory on quickly searching and checking the location of global logistics hubs according to the longitude and latitude coordinates. Hence, in this paper, I suggest a real-time location tracking system that provided real-time location of the container cargos and logistics hubs can be searched quickly according to the GPS coordinates in global shipping logistics.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.31-40
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• 2016

In vehicular ad-hoc networks (VANETs), vehicles sense information on emergency incidents (e.g., accidents, unexpected road conditions, etc.) and propagate this information to following vehicles and a server to share the information. However, this process of emergency message propagation is based on multiple broadcast messages and can lead to broadcast storms. To address this issue, in this work, we use a novel approach to detect the vehicles that are farthest away but within communication range of the transmitting vehicle. Specifically, we discuss a signal-to-noise ratio (SNR)-based linear back-off (SLB) scheme where vehicles implicitly detect their relative locations to the transmitter with respect to the SNR of the received packets. Once the relative locations are detected, nodes that are farther away will set a relatively shorter back-off to prioritize its forwarding process so that other vehicles can suppress their transmissions based on packet overhearing. We evaluate SLB using a realistic simulation environment which consists of a NS-3 VANET simulation environment, a software-based WiFi-IP gateway, and an ITS server operating on a separate machine. Comparisons with other broadcasting-based schemes indicate that SLB successfully propagates emergency messages with latencies and hop counts that is close to the experimental optimal while reducing the number of transmissions by as much as 1/20.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.11
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• pp.1217-1223
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• 2007

Advanced microwave absorbers for wide oblique incidence angles are required in many applications including wireless communication or vehicle identification in ITS(Intelligent Transport System) where 5.8 GHz DSRC(Dedicated Short Range Communication) system is applied. In this study, two-layered microwave absorber(with a laminate structure of dielectric/magnetic composites) has been designed for the achievement of low reflection coefficient over wide incidence angles at 5.8 GHz. Iron flake particles are used as the filler in the absorbing layer, and the magnetic composite sheet exhibits high magnetic loss due to ferromagnetic resonance in gigahertz frequencies. The surface layer of low dielectric constant containing small amount of carbon black is used as the impedance transformer. On the basis of transmission line theory, the reflection loss has been calculated for the two-layer structure with variation of incident angles for both TE(Transverse Electric) and TM(Transverse Magnetic) polarizations. At the optimum thickness of the composite layers, a low value of reflection loss(less than -10 dB) has been predicted for wide incidence angles up to $55^{\circ}$ which is in good agreement with the measured value determined by free-space measurement.