• Journal of Platform Technology
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• v.10 no.3
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• pp.60-68
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• 2022

As AI-technology develops, interest in the safety of autonomous driving is increasing. Recently, autonomous vehicles have been increasing, but efforts to solve side effects have been sluggish. In particular, night autonomous vehicles have more problems. This is because the probability of accidents is higher in the night driving environment than in the day environment. There are more factors to consider for self-driving at night. Among these factors, reflection of light or reflected light of lighting may be a fundamental cause of night accidents. Therefore, this study proposes method to reduce accidents and improve safety by reducing reflected light generated by the headlights of opposite vehicles or various surrounding light that appear as an important problem in night autonomous vehicles. Therefore, first, in an image obtained by a sensor of a night autonomous vehicle, illumination reflected light is extracted using reflected light characteristic information, and a color of each pixel using a reflection coefficient is found to reduce a special area generated by geometric characteristics. In addition, we find a new area using only the brightness component of the specular area, define it as Illuminated Reflection Light (IRL), and finally present a method to reduce it. Although the illumination reflection light could not be completely reduce, generally satisfactory results could be obtained. Therefore, it is believed that the proposed study can reduce casualties by solving the problems of night autonomous driving and improving safety.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.17-31
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• 2020

In this study, a study was conducted to analyze the factors affecting the acceptability for autonomous vehicles. The previous studies were reviewed to sturdy the acceptance factors and The PLS Structral equation model was used to analyze the acceptance factors. While the existing research focused on technical safety, this study comprehensively analyze safety, convenience, economy, environment, and ethical factors. The PLS model was analyzed to significant the factors that affect the acceptability for autonomous vehicles in the order of safety, economy, convenience and environment.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1349-1354
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• 1990

This paper deals with the control of autonomous vehicle in the production systems. Presently, there is a significant interest in autonomous vehicles which are capable of intelligent motion (and action) without requiring a guide track to follow. This paper describes a PI-F adaptive control algorithm, which is used to drive an experimental autonomous vehicle along a given trajectory. The simulation results characterizing the accuracy og the algorithm are presented.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.120-132
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• 2019

As a key infrastructure for positioning autonomous vehicles, HD maps are making efforts to equip autonomous vehicles and connect them with services worldwide. Global companies like Here and TomTom have contracted an agreement with three German automobile companies(BMW, Audi, Daimler) by establishing systems including from the production of HD maps to loading autonomous vehicles. Japan has organized a DMP(Dynamic Map Platform) by collaborating public and private section and performing establishment of HD map on private section-oriented. Korean companies related with autonomous vehicles are also cooperating with various companies such as vehicles, sensors and maps. But public and private sections are establishing HD maps respectively. Accordingly, Ministry of Land, Infrastructure and Transport implemented and signed memorandum for private and public cooperation in April 2019, Joint establishment council of HD map has launched in August 2019. This study performed domestic and foreign trend analysis about HD map and interviewed to related companies. And analyzed solutions for interactive cooperation of private and public section in HD map industry, purposed step-by-step strategy for operation and operation plan for joint establishment council of HD map.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.2
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• pp.1-8
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• 2019

Autonomous vehicles operated in the rough terrain environment must satisfy various technical requirements in order to improve the speed. Therefore, in order to design and implement a technical architecture that satisfies the requirements for speed improvement of autonomous vehicles, it is necessary to consider the overall technology of hardware and software to be mounted. In this study, the technical architecture of the autonomous vehicle operating in the rough terrain environment is presented. In order to realize high speed driving in pavement driving environment and other environment, it should be designed to improve the fast and accurate recognition performance and collect high quality database. and it should be determined the correct running speed from the running ability analysis and the frictional force estimation on the running road. We also improved synchronization performance by providing precise navigation information(time) to each hardware and software.

• The Journal of Korea Robotics Society
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• v.6 no.2
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• pp.97-107
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• 2011

This paper describes efficient flight control algorithms for building a reconfigurable ad-hoc wireless sensor networks between nodes on the ground and airborne nodes mounted on autonomous vehicles to increase the operational range of an aerial robot or the communication connectivity. Two autonomous flight control algorithms based on adaptive gradient climbing approach are developed to steer the aerial vehicles to reach optimal locations for the maximum communication throughputs in the airborne sensor networks. The first autonomous vehicle control algorithm is presented for seeking the source of a scalar signal by directly using the extremum-seeking based forward surge control approach with no position information of the aerial vehicle. The second flight control algorithm is developed with the angular rate command by integrating an adaptive gradient climbing technique which uses an on-line gradient estimator to identify the derivative of a performance cost function. They incorporate the network performance into the feedback path to mitigate interference and noise. A communication propagation model is used to predict the link quality of the communication connectivity between distributed nodes. Simulation study is conducted to evaluate the effectiveness of the proposed reconfigurable airborne wireless networking control algorithms.

• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.61-69
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• 2020

As a sales volume of autonomous vehicle continually grows up, regulations on this new technology are being introduced around the world. For example, safety standards for the Level 3 automated driving system was promulgated in December 2019 by the Ministry of Land, Infrastructure and Transport of Korean government. In order to promote the development of autonomous vehicle technology and ensure its safety simultaneously, the regulations on the automated driving systems should be phased in to keep pace with technology progress and market expansion. However, according to SAE J3016, which is well known to classify the level of the autonomous vehicle technologies, the description for classification is rather abstract. Therefore it is necessary to describe the automated driving system in more detail in terms of the 'Level.' In this study, the functions and characteristics of automated driving system are carefully classified at each level based on the commentary in the Informal Working Group (IWG) of the UN WP29. In particular, regarding the Level 4, technical issues are characterized with respect to vehicle tasks, driver tasks, system performance and regulations. The important features of the autonomous vehicles to meet Level 4 are explored on the viewpoints of driver replacement, emergency response and connected driving performance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.2
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• pp.138-144
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• 2020

Currently, an autonomous vehicle studies are working to develop a four-level autonomous vehicle that can cope with emergencies. In order to flexibly respond to an emergency, the autonomous vehicle must move in a direction to minimize the damage, which must be conducted by judging all the states of the road, such as the surrounding pedestrians, road conditions, and surrounding vehicle conditions. Therefore, in this paper, we suggest a passenger detection and sharing system to detect the passenger situation inside the autonomous vehicle and share it with V2V to the surrounding vehicles to assist in the operation of the autonomous vehicle. Passenger detection and sharing system improve the weighting method that recognizes passengers in the current vehicle to identify the passenger's position accurately inside the vehicle, and shares the passenger's position of each vehicle with other vehicles around it in case of emergency. So, it can help determine the driving of a vehicle. As a result of the experiment, the body pressure sensor applied to the passenger recognition sub-module showed about 8% higher accuracy than the conventional resonant sensor and about 17% higher than the piezoelectric sensor.

• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.297-305
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• 2017

As the development of autonomous vehicles becomes realistic, many automobile manufacturers and components producers aim to develop 'completely autonomous driving'. ADAS (Advanced Driver Assistance Systems) which has been applied in automobile recently, supports the driver in controlling lane maintenance, speed and direction in a single lane based on limited road environment. Although technologies of obstacles avoidance on the obstacle environment have been developed, they concentrates on simple obstacle avoidances, not considering the control of the actual vehicle in the real situation which makes drivers feel unsafe from the sudden change of the wheel and the speed of the vehicle. In order to develop the 'completely autonomous driving' automobile which perceives the surrounding environment by itself and operates, ability of the vehicle should be enhanced in a way human driver does. In this sense, this paper intends to establish a strategy with which autonomous vehicles behave human-friendly based on vehicle dynamics through the reinforcement learning that is based on Q-learning, a type of machine learning. The obstacle avoidance reinforcement learning proceeded in 5 simulations. The reward rule has been set in the experiment so that the car can learn by itself with recurring events, allowing the experiment to have the similar environment to the one when humans drive. Driving Simulator has been used to verify results of the reinforcement learning. The ultimate goal of this study is to enable autonomous vehicles avoid obstacles in a human-friendly way when obstacles appear in their sight, using controlling methods that have previously been learned in various conditions through the reinforcement learning.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.683-686
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• 2018

Autonomous vehicles are the 4th industrial revolution that utilizes artificial intelligence(AI) and superconducting technology, and is a world-wide investment and research project. However, a Uber vehicle under test in Arizona, USA, was accidentally killed by pedestrians crossing the road in the dark night, and accidents occurred when the Tesla vehicle was exposedto the backlightof the sun. These problems were caused by misunderstandings and choice about sensors mounted on autonomous vehicles due to bad weather such as snow, rain, and sunlight. In this paper, we analyze the composition of the autonomous vehicle and the cause of the accident, and consider the criteria that should be judged in case of emergency in which human accidents may occur. This paper analyzes the composition of autonomous vehicles and causes of accidents, and considers the criteria that should be choice in an emergency where an accident may occur.