The Ministry of Land, Infrastructure and Transport (MoLIT) and the Korean Automobile Testing and Research Institute (KATRI) are supporting the development of Lv.3 automated vehicle (hereinafter, AV) technology by constructing an automated driving pilot city (as known as K-City) equipped with total 5 evaluation environments (urban, motorway, suburban, community road, and autonomous parking facility) which is a test bed exclusively for AV (2017~2018). An upgrade project is in a progress to materialize harsh environments such as bad weather (rain, fog, etc.) and reproduction of communication jamming (GPS blocking, etc.) with the purpose of supporting the development of Lv.4 connected & automated vehicle (hereinafter, CAV) technology (2019~2022). We intend to proactively establish a national level standard for CAV test-bed and test road requirements, test method, etc. for establishment of a road map for the construction of the test bed which is being promoted step by step and analyze and, when required, benchmark the case of China that has announced and is utilizing it. Through this, we plan to define standardized requirements (evaluation facility, evaluation system, etc.) on the test bed for the development of Lv.4/4+ CAV technology and utilize the same for the design and construction of a test bed, establishment of a road map for the construction of a real car-based test environment related to the support for autonomous driving service substantiation, etc. through provision of an evaluation environment utilizing K-City, and the establishment of a K-City upgrade strategies, etc.

Recently, automobile industries have developed ADAS, smart cars, connected cars, automated driving systems, which communicate with outsides of a vehicle not only in uni-directional way but also in bi-directional way. It is necessary to examine the electromagnetic immunity of vehicles equipped with those communication systems. The electromagnetic immunity tests are carried out in an electromagnetic semi anechoic chamber, which is cut off from the outside electromagnetically. In this study, additional test environments were designed and tested and as a result they are shown to be effective to create test environments in an experimental chamber for electromagnetic immunity tests of vehicles equipped with communication systems.

This paper presents a development of simulation environment for validation of autonomous driving (AD) algorithm based on Robot Operating System (ROS). ROS is one of the commonly-used frameworks utilized to control autonomous vehicles. For the evaluation of AD algorithm, a 3D autonomous driving simulator has been developed based on LGSVL. Two additional sensors are implemented in the simulation vehicle. First, Lidar sensor is mounted on the ego vehicle for real-time driving environment perception. Second, GPS sensor is equipped to estimate ego vehicle's position. With the vehicle sensor configuration in the simulation, the AD algorithm can predict the local environment and determine control commands with motion planning. The simulation environment has been evaluated with lane changing and keeping scenarios. The simulation results show that the proposed 3D simulator can successfully imitate the operation of a real-world vehicle.

Changwon City has the second highest accident rate with 79.6 according to the city bus accident rate. In fact, 250,000 people use the city bus a day in Changwon, The number of accidents is increasing gradually. In addition, a recent fire accident occurred in the engine room of a city bus (CNG) in Changwon, which has gradually expanded the public's anxiety. In the case of business vehicles, the government conducts inspections with a short inspection cycle for the purpose of periodic safety inspections, etc., but it is not in the monitoring stage. In the case of city buses, the operation records are monitored using Digital Tacho Graph (DTG). As such, driving records, methods, etc. are continuously monitored, but inspections are conducted every six months to ascertain the safety and performance of automobiles. It is difficult to identify real-time information on automobile safety. Therefore, in this study, individual automobile management solutions are presented through machine learning techniques of inspection results based on driving records or habits by linking DTG data and Vehicle Inspection Management System (VIMS) data for city buses in Changwon from 2019 to 2020.

In the automobile industry, lamps are frequently used as a mean to emphasize each company's brand identity. Therefore, many detailed design models have emerged in order to realize a differentiated image in preparation for competitive vehicles. Among them, the design of a multi compartment lighting image concept that realizes light divided in multiple space also being introduced by various manufacturers. In this study, in order to solve the problem of cost and weight rise that the existing multi compartment image lamp has, using TRIZ method such as functional analysis modeling and trimming. Through this process, an idea to minimize cost and weight was derived. As the idea was designed in detail, the formation of light did not go as desired, and the diffusion of light also proceeded differently than intended. In order to overcome this problem, a new concept of corrosion and diffusion structure was applied. Eventually, it overcomes various problems and successfully applied it to a real vehicle. The idea was actually reflected in the "Santa Fe" model. Later, the media focused on the lamps to which the idea was applied, and contributed to the sale of a large number of vehicles by providing consumers with a new light sensibility. During the research process, it was possible to secure a number of patents and knowledge of new design concepts.

This paper presents a development of throttle and brake controller for autonomous vehicle simulation environment. Most of 3D simulator control autonomous vehicle by throttle and brake command. Therefore additional longitudinal controller is required to calculate pedal input from desired acceleration. The controller consists of two parts, feedback controller and feedforward controller. The feedback controller is designed to compensate error between the actual acceleration and desired acceleration calculated from autonomous driving algorithm. The feedforward controller is designed for fast response and the output is determined by the actual vehicle speed and desired acceleration. To verify the performance of the controller, simulations were conducted for various scenarios, and it was confirmed that the controller can successfully follow the target acceleration.

Recently, the introduction of Cooperative Intelligent Transport Systems (C-ITS) has been attempted to solve the limitation of only the sensor of the vehicle itself. For example, vehicles traveling at intersections can drive more safely through C-ITS. By using V2X communication of WAVE and LTE, the driver can receive the status and time of traffic lights. However, LTE has a larger transmission delay time than WAVE, so timimg data may not match in real time. In this paper, using the SPaT message, it was confirmed that LTE has a larger C-ITS service transmission delay time than WAVE. Finally, it was confirmed that the timing data of SPaT provided by LTE corrected by the algorithm is similar to SPaT provided by WAVE. It was confirmed that safer intersection driving is possible based on real-time.

Along with global environmental issues, the size of the electric vehicle market has recently skyrocketed. Various efforts have been made to extend mileage, one of the biggest problems of the electric vehicles, and development of batteries with high energy densities has led to exponential growth in mileage and performance. However, proper thermal management is essential because these high-performance batteries are affected by continuous heat generation and can cause fires due to thermal runaway phenomena. Therefore, thermal management of the battery is studied through the optimal design of the guide vanes, while utilizing the existing battery casing to ensure the safety of the electric vehicles. A battery from T-company, one of a manufacturer of the electric vehicles, was used for the research, and the commercial CFD software, ANSYS CFX V20.2, was used for analysis. The guide vanes were derived through optimal design based on a genetic algorithm with flow analysis. The optimized guide vanes show improved heat removal performance.

This study is to construct the simple estimating model for the HIC15 of the driver dummy using the frontal impact test results. Test results of 9 vehicles of Hyundai Sonata from the MY2002~MY2020 USNCAP are utilized for constructing the linear regression model. The average accelerations extracted from the vehicle crash pulses are handled as the main factors. The average accelerations of 10 ms interval within 0~100 ms are calculated from the crash pulse data of 9 vehicles. The present estimating model of the HIC15 using the average accelerations of 10 ms interval in the 0~80 ms range shows good agreement with the tested value within 2.4% maximum error.