• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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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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• v.11 no.2
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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.

• The Journal of Korea Robotics Society
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• v.14 no.2
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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.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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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.

• Convergence Security Journal
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• v.22 no.2
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• pp.77-90
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• 2022

Domestic and foreign automakers compete to lead the autonomous vehicle industry through continuously developing self-driving technologies. These self-driving technologies are evolving with dependencies on the connection between vehicles and other objects such as the environment of cars and roads. Therefore, cyber security vulnerabilities become more likely to occur in the self-driving environment, so it is necessary to prepare for them carefully. In this paper, we model the threats in autonomous vehicles and make the checklist to securely countermeasure them.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.246-248
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• 2017

Self-driving cars have three main functions. The first recognizes the surrounding environment, judge the risk, and lastly plans the drive path. Therefore, the driving operation is minimized. And it refers to a human friendly car capable of safe driving on its own. The reason for the need for self-driving car was to reduce traffic jams on limited roads and to reduce carbon dioxide emissions. Driving ahead of these self-driving car businesses can be expected to attract and expand the existing business and expand the new business and create new business opportunities for ICT firms. It is urgent for the concerned agencies to establish legal and institutional basis for self-driving cars. By doing so, new services could be provided to consumers. Therefore, this paper introduces the technological development trends for self-driving cars.

• Journal of Auto-vehicle Safety Association
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• v.15 no.1
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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.

• Journal of Auto-vehicle Safety Association
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• v.15 no.2
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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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• v.13 no.2
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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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• v.12 no.1
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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.