• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.49-59
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• 2012

Recently, various alternatives for safety and efficiency of commercial vehicles have been considered, and one of the new alternatives is the application of a digital tachograph. In Korea, the installation of a digital tachograph to commercial vehicles was regulated from 2011 and Korea Transportation Safety Authority developed e-TAS to analyze the monitoring data from digital tachographs installed in the order of 100 commercial vehicles. This study performs the potential impact analysis of the DTG installation, which includes a trend of dangerous driving, a trend of traffic accidents and cost-effective analysis, a trend of fuel consumption and cost-effective analysis, a cost-effective analysis of social benefits using e-TAS data. Depending on the frequency of dangerous driving, the participants are divided into three groups; high-dangerous group, average-dangerous group and low-dangerous group. The high-dangerous driving group shows lower km/liter than the low-dangerous driving group by 15% for buses and taxis and by 30% for trucks. About $CO_2$ emission, the difference becomes bigger; 25%, 25% and 42% for buses, taxis and trucks, respectively. Although this study is a short-term period analysis, the methodology will be applicable for the long-term period analysis with larger data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.16-30
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• 2019

In this study, we calculated the driving duration of individual vehicles according to the availability of rest facility on highway, and suggested indicators indicating the potential risk of accidents caused by long-term driving with weights based on the number of vehicles by driving duration of individual links. Based on this, the methodology for estimating the appropriate location of the highway rest facility considering the driving duration of individual vehicles was presented. Using the DSRC individual vehicle data collected from the highways, the appropriate location of the rest facility was calculated by considering the driving duration by classifying weekdays and weekends for the Gyeongbu Expressway. The results showed that the weekly and weekend high risk indicators were different. In the case of weekdays, the risk indicators of Gimchun JC to Kumho JC for Busan were high, while for weekends, the risk indicators of Ansung JC to Dongtan JC for Seoul and Ansung IC to Bukchunan IC for Busan were high. This study has great significance in that it provides a framework for detailed analysis of link units by using non-aggregated data of individual vehicle units. In addition, it is significant that the reasonable driving duration reflecting the behavior of individual vehicles was calculated by analyzing the use of rest facilities.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.299-312
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• 2021

Autonomous vehicles using V2X can drive safely information on areas outside the sensor coverage of autonomous vehicles conventional autonomous vehicles. As V2X technology has emerged as a key component of autonomous vehicles, research on V2X security is actively underway research on risk analysis due to failure of V2X communication is insufficient. In this paper, the service scenario and function of autonomous driving system V2X were derived by presenting the intersection scenario of the autonomous vehicle, the malfunction was defined by analyzing the hazard of V2X. he ISO26262 Part3 process was used to analyze the risk of malfunction of autonomous vehicle V2X. In addition, a fault injection scenario was presented to verify the fail-safe of the simulation-based intersection scenario.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.143-160
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• 2023

It is important to secure the golden time of emergency vehicles for quick responses in disaster situations, such as fire, rescue, and first aid. This study proposes plans Emergency Vehicle Preemption (EVP) based on the analysis of emergency vehicle operation to secure the golden time of emergency vehicles and increase driving safety. The emergency vehicle dispatch statistics, emergency vehicle traffic accident statistics, and survey were used for the analysis. As a result of the analysis, the frequency of dispatch of emergency vehicles and traffic accidents are increasing gradually, but the rate of securing the golden time of emergency vehicles is approximately half, indicating that improvement measures are urgent. In the questionnaire survey, most citizens consent to the necessity of introducing EVP. In addition, the criteria for the range of emergency vehicles that could provide EVP and the allowable time for waiting were derived. These results could be used to prepare EVP operation strategies, and it is expected to contribute to improving emergency vehicle operation safety and increasing the golden time securing rate through a rapid expansion of EVP.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.200-215
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• 2023

With the rapid advance of autonomous driving technology, the related vehicle market is experiencing explosive growth, and it is anticipated that the era of fully autonomous vehicles will arrive in the near future. However, along with the development of autonomous driving technology, questions regarding its safety and reliability continue to be raised. Concerns among technology adopters are increasing due to media reports of accidents involving autonomous vehicles. To promote the improvement of the safety of autonomous vehicles, it is essential to analyze previous accident cases and identify their causes. Therefore, in this study, we aimed to analyze the factors influencing the severity of autonomous vehicle accidents using previous accident cases and related data. The data used for this research primarily comprised autonomous vehicle accident reports collected and distributed by the California Department of Motor Vehicles (CA DMV). Spatial information on accident locations and additional traffic data were also collected and utilized. Given that the primary data used in this study were accident reports, a Poisson regression analysis was conducted to model the expected number of accidents. The research results indicated that the severity of autonomous vehicle accidents increases in areas with low lighting, the presence of bicycle or bus-exclusive lanes, and a history of pedestrian and bicycle accidents. These findings are expected to serve as foundational data for the development of algorithms to enhance the safety of autonomous vehicles and promote the installation of related transportation infrastructure.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.157-165
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• 2017

Intelligent transportation systems are currently being developed for elemental technology development of cooperative intelligent transport systems, which enable vehicles to communicate with each other or reduce the risk of traffic accidents, We have been defining and standardizing services according to the purpose of solving traffic safety problems depending on countries. Therefore, in this study, the developed countries of V2X(vehicle-to-everything) based on USA, Europe, Japan, etc., analyzed the service cases selected in the field demonstration stage after completion of the element technology devanalyzed the service cases selected in the field demonstration stage after completion of the element technology development, and to suggest the direction of futureelopment, and to suggest the direction of future policy direction.

• ETRI Journal
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• v.43 no.4
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• pp.603-616
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• 2021

Over the last few years, autonomous vehicles have progressed very rapidly. The odometry technique that estimates displacement from consecutive sensor inputs is an essential technique for autonomous driving. In this article, we propose a fast, robust, and accurate odometry technique. The proposed technique is light detection and ranging (LiDAR)-based direct odometry, which uses a spherical range image (SRI) that projects a three-dimensional point cloud onto a two-dimensional spherical image plane. Direct odometry is developed in a vision-based method, and a fast execution speed can be expected. However, applying LiDAR data is difficult because of the sparsity. To solve this problem, we propose an SRI generation method and mathematical analysis, two key point sampling methods using SRI to increase precision and robustness, and a fast optimization method. The proposed technique was tested with the KITTI dataset and real environments. Evaluation results yielded a translation error of 0.69%, a rotation error of 0.0031°/m in the KITTI training dataset, and an execution time of 17 ms. The results demonstrated high precision comparable with state-of-the-art and remarkably higher speed than conventional techniques.

• Journal of Multimedia Information System
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• v.9 no.1
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• pp.33-42
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• 2022

In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

• ETRI Journal
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• v.44 no.2
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• pp.183-193
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• 2022

Smart cities are expected to provide residents with convenience via various agents such as CCTV, delivery robots, security robots, and unmanned shuttles. Environmental data collected by various agents can be used for various purposes, including advertising and security monitoring. This study suggests a surveillance map data framework for efficient and integrated multimodal data representation from multi-agents. The suggested surveillance map is a multilayered global information grid, which is integrated from the multimodal data of each agent. To confirm this, we collected surveillance map data for 4 months, and the behavior patterns of humans and vehicles, distribution changes of elevation, and temperature were analyzed. Moreover, we represent an anomaly detection algorithm based on a surveillance map for security service. A two-stage anomaly detection algorithm for unusual situations was developed. With this, abnormal situations such as unusual crowds and pedestrians, vehicle movement, unusual objects, and temperature change were detected. Because the surveillance map enables efficient and integrated processing of large multimodal data from a multi-agent, the suggested data framework can be used for various applications in the smart city.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.1
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• pp.25-37
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• 2024

The objective of this study was to create intelligent rail robots that are optimized for facility management and implement digital twin systems for smart road tunnel management. An autonomous surveillance system is formed by combining the sensing platform consisting of railing robots, fixed cameras and environmental detection sensors with the digital twin data platform technology for tunnel monitoring and early fire suppression. In order to develop mobile rail robots for fire extinguishing, we also designed and manufactured robots for extinguishing & monitoring and fire extinguishing devices, and then we examined the optimization of all parts. Our next step was to build a digital twin for road tunnel management by developing continuous image display system and implementing 3D modeling. After constructing prototypes, we attempted simulations by configuring abnormal symptom scenarios, such as vehicles fires. This study's proposal proposes high-accuracy risk prediction services that will enable intelligent management of risks in the tunnel with early response at each stage, using the data collected from the intelligent rail robots and digital twin systems.