• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권11호
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• pp.5299-5320
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• 2019

Interest in self-driving vehicle research has been rapidly increasing, and related research has been continuously conducted. In such a fast-paced self-driving vehicle research area, the development of advanced technology for better convenience safety, and efficiency in road and transportation systems is expected. Here, we investigate research in self-driving vehicles and analyze the main technologies of driverless car software, including: technical aspects of autonomous vehicles, traffic infrastructure and its communications, research techniques with vision recognition, deep leaning algorithms, localization methods, existing problems, and future development directions. First, we introduce intelligent self-driving car and road infrastructure algorithms such as machine learning, image processing methods, and localizations. Second, we examine the intelligent technologies used in self-driving car projects, autonomous vehicles equipped with multiple sensors, and interactions with transport infrastructure. Finally, we highlight the future direction and challenges of self-driving vehicle transportation systems.

• Journal of Positioning, Navigation, and Timing
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• 제11권2호
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• pp.119-126
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• 2022

This paper presents a method to reduce the vibration-induced noise effect of an inertial measurement device mounted on a self-driving vehicle. The inertial sensor used in the GNSS/INS integrated navigation system of a self-driving vehicle is fixed directly on the chassis of vehicle body so that its navigation output is affected by the vibration of the vehicle's engine, resulting in the degradation of the navigational performance. Therefore, these effects must be considered when mounting the inertial sensor. In order to solve this problem, this paper proposes to use an in-house manufactured vibration suppression device and analyzes its impact on reducing the vibration effect. Experimental test results in a static scenario show that the vibration-induced noise effect is more clearly observed in the lateral direction of the vehicle, but can be effectively suppressed by using the proposed vibration suppression device compared to the case without it. In addition, the dynamic positioning test scenario shows the position, speed, and posture errors are reduced to 74%, 67%, and 14% levels, respectively.

• 로봇학회논문지
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• 제14권2호
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• pp.122-130
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• 2019

Collecting a rich but meaningful training data plays a key role in machine learning and deep learning researches for a self-driving vehicle. This paper introduces a detailed overview of existing open-source simulators which could be used for training self-driving vehicles. After reviewing the simulators, we propose a new effective approach to make a synthetic autonomous vehicle simulation platform suitable for learning and training artificial intelligence algorithms. Specially, we develop a synthetic simulator with various realistic situations and weather conditions which make the autonomous shuttle to learn more realistic situations and handle some unexpected events. The virtual environment is the mimics of the activity of a genuine shuttle vehicle on a physical world. Instead of doing the whole experiment of training in the real physical world, scenarios in 3D virtual worlds are made to calculate the parameters and training the model. From the simulator, the user can obtain data for the various situation and utilize it for the training purpose. Flexible options are available to choose sensors, monitor the output and implement any autonomous driving algorithm. Finally, we verify the effectiveness of the developed simulator by implementing an end-to-end CNN algorithm for training a self-driving shuttle.

• 자동차안전학회지
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• 제13권4호
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• pp.81-91
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• 2021

Last year, the Autonomous Vehicle Act was enacted to respond to deployment of autonomous vehicles. But the Act stipulates the operation of autonomous vehicle pilot zones, In addition, in order to analyze autonomous vehicle accidents and establish a reasonable damage compensation system, the Automobile Damage Compensation Guarantee Act was revised. But, It is necessary to seek plans for institutional development such as detailed concepts of self-driving cars and driving, a security certification system for securing safety of autonomous cooperative driving, and enhancement of the effectiveness of special cases related to personal information processing. I would like to seek ways to improve the legal system to respond reasonably to the deployment of autonomous vehicles.

• 융합보안논문지
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• 제22권2호
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• pp.77-90
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• 2022

현재 국내외 자동차 기업들은 꾸준한 기술 개발을 통해 자율 주행 자동차 산업을 선도하고자 경쟁하고 있다. 이러한 자율 주행 기술은 자동차와 주행 도로 환경과 같이 사물 간의 다양한 연결 의존성을 가지면서 발전하고 있다. 따라서 자동차를 포함한 전체 자율 주행 환경 내에서 사이버 보안 취약점이 발생하기 쉬워지고 있으며, 이에 대한 대비책의 중요성이 커지고 있다. 본 논문에서는 자율 주행 자동차에서 발생할 수 있는 위협을 모델링하고, 자율 주행 자동차의 안전한 보안을 위해 점검이 필요한 요소들을 체크리스트로써 제안한다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 춘계학술대회
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• pp.246-248
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• 2017

자율주행자동차는 자동차 스스로 주변 환경을 인식하여 위험을 판단하고 주행경로를 계획하여 운전자 주행조작을 최소화하며 스스로 안전주행이 가능한 인간 친화형 자동차를 말한다. 자율주행자동차가 필요한 이유는 한정된 도로 상에서의 교통체증을 감소와 탄소 저감을 목적으로 시작되었다. 이러한 관련 자율주행자동차 사업 추진은 자동차 업체의 기존 사업 유지 및 확대와 ICT 기업의 신규사업 창출과 진입효과를 기대 할 수 있다. 관련 인증기관은 자율주행자동차에 대한 법적과 제도적 기반 마련이 시급하다. 그럼으로써 소비자에게 새로운 서비스가 제공될 수 있을 것이다. 따라서 본 논문에서는 자율주행자동차에 대한 기술개발 동향을 소개한다.

• 자동차안전학회지
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• 제15권1호
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• pp.45-54
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• 2023

In the commercialization stage of level 4 or higher autonomous driving, the need for new legal system related to drive safely has increased in order to meet the improved level of technological development. Especially human drivers should not be legally accountable for road safety in the era of autonomous vehicles and thus safety standards for operation of autonomous vehicles are significant. To address this issue, the German Road Traffic Act was revised in 2021, adding provisions corresponding to the commercialization of self-driving vehicle of level 4 and in the similar context the Japanese Road Traffic Ac was amended in 2022. This Article draws implications for legislative discussions on driving-related responsibilities of driverless autonomous vehicle to ensure driving safety in Korea through recent amendments in Germany and Japan.

• 자동차안전학회지
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• 제15권2호
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• pp.42-48
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• 2023

In recent years, automated vehicles have garnered attention in the multidisciplinary research field, promising increased safety on the road and new opportunities for passengers. High-Definition (HD) maps have been in development for many years as they offer roadmaps with inch-perfect accuracy and high environmental fidelity, containing precise information about pedestrian crossings, traffic lights/signs, barriers, and more. Demonstrating autonomous driving requires verification of driving on actual roads, but this can be challenging, time-consuming, and costly. To overcome these obstacles, creating HD maps of real roads in a simulation and conducting virtual driving has become an alternative solution. However, existing HD maps using high-precision data are expensive and time-consuming to build, which limits their verification in various environments and on different roads. Thus, it is challenging to demonstrate autonomous driving on anything other than extremely limited roads and environments. In this paper, we propose a new and simple method for implementing HD maps that are more accessible for autonomous driving demonstrations. Our HD map combines the CARLA simulator and OpenStreetMap (OSM) data, which are both open-source, allowing for the creation of HD maps containing high-accuracy road information globally with minimal dependence. Our results show that our easily accessible HD map has an accuracy of 98.28% for longitudinal length on straight roads and 98.42% on curved roads. Moreover, the accuracy for the lateral direction for the road width represented 100% compared to the manual method reflected with the exact road data. The proposed method can contribute to the advancement of autonomous driving and enable its demonstration in diverse environments and on various roads.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.25-34
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• 2024

The paper investigates how the semiconductor and electric vehicle industries are addressing safety and security concerns in the era of autonomous driving, emphasizing the prioritization of safety over security for market competitiveness. Collaboration between these sectors is deemed essential for maintaining competitiveness and value. The research suggests solutions such as advanced autonomous driving technologies and enhanced battery safety measures, with the integration of AI chips playing a pivotal role. However, challenges persist, including the limitations of big data and potential errors in semiconductor-related issues. Legacy automotive manufacturers are transitioning towards software-driven cars, leveraging artificial intelligence to mitigate risks associated with safety and security. Conflicting safety expectations and security concerns can lead to accidents, underscoring the continuous need for safety improvements. We analyzed the expansion of electric vehicles as a means to enhance safety within a framework of converging security concerns, with AI chips being instrumental in this process. Ultimately, the paper advocates for informed safety and security decisions to drive technological advancements in electric vehicles, ensuring significant strides in safety innovation.

• Journal of Platform Technology
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• 제12권1호
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• pp.12-31
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• 2024

Today, many countries around the world recognize the development of autonomous vehicles as a national growth engine, support technology development through various projects, and promote it as national policy. China and Korea are representative countries that are strongly promoting autonomous vehicle policies. The Chinese government's policy direction for self-driving cars focuses on support for fostering new industries. Korea has established mid- to long-term goals and plans to foster the future mobility industry as a key growth engine and is promoting these as a national task. Recently, China and Korea have established national pilot areas to test autonomous vehicle operation and are actively pursuing policies. We aim to compare and analyze the operation status of self-driving cars in China's Xiong'an New Area and South Korea's Sejong City and derive policy implications regarding self-driving cars, which are emerging as a key industry of the future. According to the analysis results, it was found that China's Xiong'an New District is ahead of Korea's Sejong City in terms of leader leadership. As a result, autonomous driving is being operated at the government-wide and national level in Xiong'an New Area. In terms of the driving force, in the case of Xiongan New Area, the policy is being promoted by companies centered on Baidu, and in the case of Sejong City, the policy is being promoted by the local government. As a result, it is estimated that Xiongan New Area will be able to reach commercialization before Sejong City. In the final policy proposal, it was proposed to break away from the existing government-led method and switch to a collaboration with the private sector and a private-led method.