• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.14 no.12
• /
• pp.6090-6097
• /
• 2013

A pneumatically-driven driving simulator that provides a realistic representation of the driving environment was developed. The motion platform for the driving simulator is a mechatronic device that gives a driver the realistic feeling of an actual vehicle. The cost of the motion platform comprises the largest part of the expenses in developing a driving simulator. In this project, to develop a low-cost motion platform, the self-built motion platform based on the Stewart platform configuration that is constructed by six pneumatic cylinders was used as its actuator. The Stewart platform that moves in response to the operating signals of the joystick showed satisfactory tracking performance. We confirmed the possibility of the driving simulator using rFactor that is a commercially available racing game software.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.2
• /
• pp.278-287
• /
• 2022

With the development of technology, driving simulators have been used in various ways. In driving simulator experiments, scenario creation is essential to increase fidelity, achieve research aims, and provide an immersive experience to the driver. However, challenges remain when creating realistic scenarios, such as developing a database and the execution of scenarios in real-time. Therefore, to create realistic scenarios, it is necessary to acquire real-time data. This study intends to develop a method of acquiring real-time weather and traffic speed information for actual, specific roads. To this end, this study suggests the concatenator for dynamic data obtained from Arduino sensors and public open APIs. Field tests are then performed on actual roads to evaluate the performance of the proposed solution. Such results may give meaningful information for driving simulator studies and for creating realistic scenarios.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.1
• /
• pp.167-181
• /
• 2024

Utilization of a driving simulator in the development of autonomous driving technology allows us to perform various tests effectively in criticial environments, thereby reducing the development cost and efforts. However, there exists a serious drawback that the driving simulator has a big difference from the real environment, so a problem occurs when the autonomous driving algorithm developed using the driving simulator is applied directly to the real vehicle system. This is defined as so-called Sim2Real problem and can be classified into scenarios, sensor modeling, and vehicle dynamics. This Paper presensts on a method to solve the Sim2Real problem in autonomous driving simulator focusing on IMU sensor. In order to reduce the difference between emulated virtual IMU sensor real IMU sensor, IMU sensor emulation techniques through precision error modeling of IMU sensor are introduced. The error model of IMU sensors takes into account bias, scale factor, misalignmnet, and random walk by IMU sensor grades.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.6
• /
• pp.242-263
• /
• 2021

This paper presents a method to implement a low-cost driving simulator for developing autonomous driving algorithms. This is implemented by using GTA V, a physical engine-based commercial game software, containing a function to emulate output and data of various sensors for autonomous driving. For this, NF of Script Hook V is incorporated to acquire GT data by accessing internal data of the software engine, and then, various sensor data for autonomous driving are generated. We present an overall function of the developed driving simulator and perform a verification of individual functions. We explain the process of acquiring GT data via direct access to the internal memory of the game engine to build up an autonomous driving algorithm development environment. And, finally, an example applicable to artificial neural network training and performance evaluation by processing the emulated sensor output is included.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2011.11a
• /
• pp.65-67
• /
• 2011

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.44 no.1
• /
• pp.63-73
• /
• 2024

Autonomous vehicles at Levels 3 to 5, currently under global research and development, seek to replace the driver's perception, judgment, and control processes with various sensors integrated into the vehicle. This integration enables artificial intelligence to autonomously perform the majority of driving tasks. However, autonomous vehicles currently obtain temporary driving permits, allowing them to operate on roads if they meet minimum criteria for autonomous judgment abilities set by individual countries. When autonomous vehicles become more widespread in the future, it is anticipated that buyers may not have high confidence in the ability of these vehicles to avoid hazardous situations due to the limitations of temporary driving permits. In this study, we propose a method for grading the judgment abilities of autonomous vehicles based on a driving simulator experiment comparing and evaluating drivers' abilities to avoid hazardous situations. The goal is to derive evaluation criteria that allow for grading based on specific scenarios and to propose a framework for grading autonomous vehicles. Thirty adults (25 males and 5 females) participated in the driving simulator experiment. The analysis of the experimental results involved K-means cluster analysis and independent sample t-tests, confirming the possibility of classifying the judgment abilities of autonomous vehicles and the statistical significance of such classifications. Enhancing confidence in the risk-avoidance capabilities of autonomous vehicles in future hazardous situations could be a significant contribution of this research.

• 한국ITS학회:학술대회논문집
• /
• v.2006 no.10
• /
• pp.230-235
• /
• 2006

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.4
• /
• pp.31-43
• /
• 2019

Take-overs occur in autonomous vehicles at levels 3 and 4 based on SAE. For safe take-over, it is necessary to set the time required for diverse drivers to complete take-over in various road conditions. In this study, take-over time and stabilization characteristics were measured to secure safety of take-over in autonomous vehicle. To this end, a virtual driving simulator was used to set up situations similar to those on real expressways. Fifty drivers with various sexes and ages participated in the experiment where changes in traffic volume and geometry were applied to measure change in takeover time and stabilization characteristics according to various road conditions. Experimental results show that the average take-over time was 2.3 seconds and the standard deviation was 0.1 second. As a result of analysis of stabilization characteristics, there was no difference in take-over stabilization time due to the difference of traffic volume, and there was a significant difference by curvature changes.

• Proceedings of the Safety Management and Science Conference
• /
• 2008.11a
• /
• pp.561-567
• /
• 2008

The objectives of this study is to: (1) develop how applications for driving simulator of national highway safety designs when those are appeared; (2) examine the degree to which those geometric designs of the horizontal and vertical profile; and (3) search positive safety and passive highway safety design of the point at which highway alignment factors initiate driving safety to facility or highway design.

• Journal of Korean Society of Transportation
• /
• v.32 no.2
• /
• pp.106-118
• /
• 2014

The objective of this study is to develop a methodology for evaluating the effectiveness of in-vehicle pedestrian warning systems. Driving Simulator-based experiments were conducted to collect data to represent driver's responsive behavior. The braking frequency, lane change duration, and collision speed were used as measure of effectiveness (MOE) to evaluate the effectiveness. Collision speed data obtained from the simulation experiments were further used to predict pedestrian injury severity. Results demonstrated the effectiveness of warning information systems by reducing the pedestrian injury severity. It is expected that the proposed evaluation methodology and outcomes will be useful in developing various vehicular technologies and relevant policies to enhance pedestrian safety.