• 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.19 no.5
• /
• pp.162-177
• /
• 2020

The perception of traffic environment based on various sensors in autonomous driving system has a direct relationship with driving safety. Recently, as the perception model based on deep neural network is used due to the development of machine learning/in-depth neural network technology, a the perception model training and high quality of a training dataset are required. However, there are several realistic difficulties to collect data on all situations that may occur in self-driving. The performance of the perception model may be deteriorated due to the difference between the overseas and domestic traffic environments, and data on bad weather where the sensors can not operate normally can not guarantee the qualitative part. Therefore, it is necessary to build a virtual road environment in the simulator rather than the actual road to collect the traning data. In this paper, a training dataset collection process is suggested by diversifying the weather, illumination, sensor position, type and counts of vehicles in the simulator environment that simulates the domestic road situation according to the domestic situation. In order to achieve better performance, the authors changed the domain of image to be closer to due diligence and diversified. And the performance evaluation was conducted on the test data collected in the actual road environment, and the performance was similar to that of the model learned only by the actual environmental data.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.1
• /
• pp.26-41
• /
• 2024

To ensure safer road conditions, understanding the human factors influencing driving behavior is crucial. However, there are many difficulties in deriving the characteristics of individual human factors that affect actual driving behaviors. Therefore, this study analyzes self-reported dangerous-driving propensities in order to explore potential correlations with drivers' behaviors. The goal is to propose a method for assessing driving tendencies based on varying traffic scenarios. The study employed a questionnaire to gauge participants' propensity to drive dangerously, utilizing a simulator to analyze their driving behaviors. The aim is to determine any notable connections between dangerous-driving propensity and specific driving behaviors. Results indicate that individuals exhibiting a high propensity for reckless driving, as identified by the Korean DBQ, tend to drive at higher speeds and display more aggressive acceleration patterns. These findings contribute to a potential method for assessing reckless driving drivers.

• Journal of Cadastre & Land InformatiX
• /
• v.51 no.1
• /
• pp.39-51
• /
• 2021

Recently, there has been much interest in practical use of standardized HD map that can effectively define roads, lanes, junctions, road signs, and road facilities in autonomous driving. Various kinds of de jure or de facto standards such as ISO 22726-1, ISO 14296, HERE HD Live map, NDS open lane model, OpenDRIVE, and NGII HD map are currently being used. However, there are lots of differences in data modeling among these standards, it makes difficult to use them together in autonomous driving. Therefore, we propose a data model conversion method to enable an efficient use of various kinds of HD map standards in autonomous driving in this study. Specifically, we propose a conversion method between the NGII HD map model, which is easily accessible in the country, and the OpenDRIVE model, which is commonly used in the autonomous driving industry. The proposed method consists of simple conversion of NGII HD map layers into OpenDRIVE objects, new OpenDRIVE objects creation corresponding to NGII HD map layers, and linear transformation of NGII HD map layers for OpenDRIVE objects creation. Finally, we converted some test data of NGII HD map into OpenDRIVE objects, and checked the conversion results through Carla simulator. We expect that the proposed method will greatly contribute to improving the use of NGII HD map in autonomous driving.

• Proceedings of the ESK Conference
• /
• 1996.04a
• /
• pp.270-275
• /
• 1996

본 연구에서는 인공현실감 기술을 이용하여 일종의 시뮬레이터라고 할 수 있는 자동차 주행환경을 개발하였다. 이 시스템은 Pentium PC에서 구현되었고 운전을 위하여 스티어링 휠, 클러치, 브레이크, 액 셀을 사용하였으며 속도출력을 위하여 스피드메타를 사용하였다. 이러한 입출력 장치를 하나의 통합된 모듈로 만들어서 8255 인터페이스 카드를 통하여 컴퓨터와 접속시켰다. 음향효과를 위하여 MIDI 인터페 이스, 샘플러, 스피커를 사용하였고 효과음은 샘플링하여 사용하였다. 이 밖에도 3차원 그래픽 디스플레 이를 위하여 CrystalEyes가 사용되었다. 가상세게 모델링을 위한 소프트웨어로는 Superscape VRT4.0이 사용되었다. 그래픽으로는 도심 시내 주행환경을 구현하였고, 모든 객체들은 실물 크기 비율로 그렸다. 자동차의 운전 메카니즘은 자동차 동역학을 모델링하여 계산하였다. 이러한 시스템은 주행시 운전자의 자세 및 생리신호를 측정하기 위한 환경으로 사용될 수 있으며 또한 교통안전표지나 신호등과 같은 도로 환경의 인간공학적 평가를 위해서도 사용될 수 있다.

• Journal of the HCI Society of Korea
• /
• v.14 no.2
• /
• pp.21-29
• /
• 2019

Take-over requests in semi-autonomous cars must be handled properly in the case of road obstacles or curved roads in order to avoid accidents. In these situations, situation awareness and appropriate decision making are essential for distracted drivers. This study used a driving simulator to investigate the components of auditory-visual information systems that affect safety, workload, and trust. Auditory information consisted of either voice guidance providing situation awareness for the take-over or a beep sound that only alerted the driver. Visual information consisted of either a screen showing how to maneuver the vehicle or only an icon indicating a take-over situation. By providing auditory information that increased situation awareness and visual information that aided decision making, trust and safety increased, while workload decreased. These results suggest that the levels of situation awareness and decision making ability affect trust, safety, and workload for drivers.

• Journal of Korean Society of Transportation
• /
• v.23 no.3 s.81
• /
• pp.73-84
• /
• 2005

Highway design criteria are considering roadway safety and smooth driving maneuver. However, a certain highway alignment within design criteria often leads drivers to undesirable situation due to the differences between the original intention of design criteria and the unintended result of drivers' cognition. The differences between them often result in traffic accidents. In order to reduce accident process, highway safety facilities are installed on those roadway sections. However, the relationship between highway environments and human factors has not been deeply studied in Korea. In this study. vertical roadway sections are constructed with 3-D graphical tools. This vertical roadway sections are simulated on a driving simulator in order to identify the differences of drivers' cognition on different roadway environments. Based upon the collected data from the driving simulator, canonical correlation analysis and canonical discriminant analysis of quantification theory II have been performed in order to figure out impacting factors on the degree of roadway safety. Also, based upon quantification theory I. the relationship between roadway safety facilities and the degree of safety has been analyzed.

• Journal of Korean Society of Transportation
• /
• v.30 no.4
• /
• pp.43-59
• /
• 2012

Assuming a completed Smart Highway road & communication environment that allows real-time information collection and transmission of road traffic condition ahead, the purpose of this study is to develop a plan for inducing a network-level safe driving pattern by providing road traffic condition and safety information to multiple drivers through a road information provision device. In this study, the device with a function that displays different colors according to the hazard level to the existing delineator has been named 'Smart Delineator'. Smart Delineator is a device that provides not only alignment information but also safety information for drivers to receive real-time warning information and intuitively recognize road traffic condition ahead so that drivers can respond. To examine the effects of safety driving inducement level on drivers, a simulation test was conducted using driving simulator as well as a satisfaction survey. The result showed that the Smart Delineator was able to identify the location of occurrence and affecting driving according pattern, either adhering to recommended speed or reducing speed according to the pre-defined hazard level.

• Korean Journal of Occupational Therapy
• /
• v.26 no.4
• /
• pp.127-143
• /
• 2018

Objective : The purpose of this study was to compare with the effects of driving simulator and Dynavision training after stroke through the test of cognitive ability and driving performance. Methods : Twenty-one stroke patients were randomly classified to the driving simulator training group (N=11) and Dynavision training group (N=10), and were carried out respectively training for 15 times. The driving performances was measured by the driving simulator test, and cognitive-perceptive abilities was measured by the DriveABLE Cognitive Assessment Tool, Trail Making Test-A, Trail Making Test-B and Mini Mental State Examination-K. Results : The driving simulator training group showed significant changes in all cognitive tests and most of driving performances. The Dynavision training group also showed significant changes in all cognitive tests except for Trail Making Test-A and some driving performances. The significant differences on both groups were found regarding the estimated degree of results on the on-road evaluation, the number of off road accidents and collisions. In addition, the causal influence of the two training methods on these variables was analyzed to be more than 20%. Conclusion : The driving simulator and Dynavision training were found to be effective intervention in the driving rehabilitation after stroke. In particular, it was confirmed that the driving simulator is an effective training to improve overall driving ability of stroke patients. In addition, the difference in training effect between the two training methods was found to be more than 20%.

• Journal of Korean Society of Transportation
• /
• v.27 no.5
• /
• pp.145-153
• /
• 2009

Although an interest in higher design speeds continues to increase to promote more efficient travel on expressways, the current Korean design guidelines do not provide criteria for design values. An arising issue associated with higher design speeds is how to effectively ensure traffic safety under such high speed traffic conditions. In particular the safety issue would become more significant in determining the interchange spacing. This study proposes a methodology for determining freeway interchange spacing under higher speed traffic conditions. A microscopic traffic simulator, VISSIM, was used to evaluate the effects of various interchange spacings on traffic conditions in terms of safety. In this study, the acceleration noise was used as an index to represent the stability of traffic conditions, which is a potential indicator to quantify the level of safety. It was found based on simulation evaluations that 5-km interchange spacing would be a feasible alternative under higher speed traffic conditions (around 160 km/h).