• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.3
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• pp.147-155
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• 2022

The accumulated ice and snow during the operation of aircraft and railway vehicles can degrade aerodynamic performance or damage the major components of vehicles. Therefore, it is crucial to predict the temporal growth of ice for operational safety. Numerical simulation of ice is widely used owing to the fact that it is economically cheaper and free from similarity problems compared to experimental methods. However, numerical simulation of ice generally divides the analysis into multi-step and assumes the quasi-steady assumption that considers every time step as steady state. Although this method enables efficient analysis, it has a disadvantage in that it cannot track continuous ice evolution. The purpose of this study is to construct a surrogate model that can predict the temporal evolution of ice shape using reduced-order modeling. Reduced-order modeling technique was validated for various ice shape generated under 100 different icing conditions, and the effect of the number of training data and the icing conditions on the prediction error of model was analyzed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.85-100
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• 2022

Recently, with the widespread expansion of convergence based on digital connectivity, the transportation and mobility fields are rapidly changing, and research related to this is also diversifying. This study aims to analyze the research trends in the mobility field and identify key research areas and topics. Topic modeling analysis has been proved as a useful approach for analyzing the research trends. The abstracts of 142 research papers concerning mobility from the Korean academic citation index were analyzed, derived 9 research topics and linked to 6 key elements of research framework. The result showed that 'Advanced vehicle and transportaion technology' and 'Linkage and integrated services among means for mobility' were most actively studied research fields. It also found that research on insurance, law, regulation for securing user's safety and conflict-resolving with the existing industry has been conducted.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.331-345
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• 2021

Virtual testing is considered a major requirement for the safety verification of autonomous driving functions. For virtual testing, both the autonomous vehicle and the driving environment should be modeled appropriately. In particular, a realistic modeling of the perception sensor system such as the one having a camera and radar is important. However, research on modeling to consistently generate realistic perception results is lacking. Therefore, this paper presents a sensor modeling method to provide realistic object detection results in a MILS (Model in the Loop Simulation) environment. First, the key parameters for modeling are defined, and the object detection characteristics of actual cameras and radar sensors are analyzed. Then, the detection characteristics of a sensor modeled in a simulation environment, based on the analysis results, are validated through a correlation coefficient analysis that considers an actual sensor.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.17-22
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• 2022

To reduce the bump of bridge/earthwork transition area caused by the settlement of the soft ground during public use, the road agencies have been continuously overlay or repavement at those areas. In this study, the vehicle-mounted ground penetrating radar with 1GHz air-coupled antenna was used to estimate the settlement amount of those areas for nine bridges built in the soft ground. Results shows that it is possible to effectively measure the thickness of pavement up to a depth of 1 m on an asphalt road with ground penetrating radar technology that can inspect under the road surface. Distinctively deformation of the road surface, the variation in the thickness of the pavement measured at bridge/earth transition areas is equivalent to a minimum of 50 mm and a maximum of 600 mm, and there is a risk of cavity in the ground. The difference in the increased pavement thickness is 50~250 mm for each bridge connection, which may cause the differential settlement. In this study, by using the result of the ground penetration radar, a plan for improving drivability and maintenance of the settlement is suggested and applied to the field.

• The Journal of the Acoustical Society of Korea
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• v.40 no.6
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• pp.571-577
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• 2021

This study is a study on System On Chip (SOC) that implements virtual engine sound in electric vehicles without engines, and realizes vivid engine sound by combining Adaptive Difference PCM (ADPCM) method and frequency modulation method for satisfaction of driver's needs and safety of pedestrians. In addition, by proposing an electronic sound synthesis algorithm applying Musical Instrument Didital Interface (MIDI), an engine sound synthesis method and a constitutive model of an engine sound generation system are presented. In order to satisfy both drivers and pedestrians, this study uses Controller Area Network (CAN) communication to receive information such as Revolution Per Minute (RPM), vehicle speed, accelerator pedal depressed amount, torque, etc., transmitted according to the driver's driving habits, and then modulates the frequency according to the appropriate preset parameters We implemented an interaction algorithm that accurately reflects the intention of the system and driver by using interpolation for the system, ADPCM algorithm for reducing the amount of information, and MIDI format information for making engine sound easier.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.211-225
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• 2023

In the future, infotainment systems are expected to play a pivotal role in mobility ecosystems connecting users and vehicles. This study draws user-experience factors from reviews of Android Auto, a car infotainment application, and analyzes factors that affect satisfaction. The user-experience factors of infotainment have been redefined based on previous studies. To analyze actual user-experience factors, topics are obtained, applied, and interpreted from user discourse through topic modeling. Sentiment analysis and logistic regression are used to determine positive and negative user-experience factors that affect satisfaction. Results of the empirical analysis show that Ease of Use and Understandability are factors that have the greatest impact on satisfaction, and Flexibility, Safety, and Playfulness are factors that have the most critical effect on dissatisfaction. Therefore, this paper suggests ways to improve the satisfaction level of the infotainment system, and establishes a strategy accordingly.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.436-446
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• 2023

In the field of safety-critical systems, analyzing the effects of various failure factors (failure modes) is essential through Failure Mode and Effects Analysis (FMEA). However, with the increasing importance of software in systems, applying FMEA analysis to the design phase has become challenging. This paper proposes the use of Automatic FMEA, which can automatically perform FMEA using model-based design techniques, and presents a case study of FMEA for automotive engines. A comparison is made between the model-based Automatic FMEA analysis tool and existing FMEA tools. The study aims to demonstrate the performance of the Automatic FMEA analysis tool and propose future research plans.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.265-275
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• 2023

The purpose of this paper is to devise an optimal route allocation algorithm for automated vehicle(AV) in monitoring quality of road infrastructure to support the road safety. The tasks of an AV in this paper include visiting node-links at least once during its operation and checking status of road infrastructure, and coming back to its depot.. In selecting optimal route, its priority goal is visiting the node-links with higher risks while reducing costs caused by operation. To deal with the problem, authors devised reward maximizing algorithm for AVs. To check its validity, the authors developed simple toy network that mimic node-link networks and assigned costs and rewards for each node-link. With the toy network, the reward maximizing algorithm worked well as it visited the node-link with higher risks earlier then chinese postman route algorithm (Eiselt, Gendreau, Laporte, 1995). For further research, the reward maximizing algorithm should be tested its validity in a more complex network that mimic the real-life.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.17-28
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• 2023

Potholes that occur on paved roads can have fatal consequences for vehicles traveling at high speeds and may even lead to fatalities. While manual detection of potholes using human labor is commonly used to prevent pothole-related accidents, it is economically and temporally inefficient due to the exposure of workers on the road and the difficulty in predicting potholes in certain categories. Therefore, completely preventing potholes is nearly impossible, and even preventing their formation is limited due to the influence of ground conditions closely related to road environments. Additionally, labeling work guided by experts is required for dataset construction. Thus, in this paper, we utilized the Mean Teacher technique, one of the semi-supervised learning-based knowledge distillation methods, to achieve robust performance in pothole image classification even with limited labeled data. We demonstrated this using performance metrics and GradCAM, showing that when using semi-supervised learning, 15 pre-trained CNN models achieved an average accuracy of 90.41%, with a minimum of 2% and a maximum of 9% performance difference compared to supervised learning.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.258-272
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• 2022

The technology implementation method was diversified into an 'autonomous cooperative driving' method to overcome the limitations of a stand-alone autonomous vehicle with vehicle sensor-based autonomous driving. The autonomous cooperative driving method involves exchanging information between roadside infrastructure and autonomous vehicles. In this process, the concept of dynamic information (LDM), a target of cooperation, was established. But, evaluation methods and standards for dynamic information have not been established. Therefore, this study, a dynamic information evaluation method based on information on pedestrians within the moving objects. In addition, autonomous cooperative driving was demonstrated, and dynamic information was also verified through the evaluation method. The significance of this study is that it established the dynamic information evaluation methodology for autonomous cooperative driving for the first time. Based on this, this study is expected to contribute to the application of safe autonomous cooperative driving technology to the field.