• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.6
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• pp.774-780
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• 2017

The techniques for driving trajectory calculation and driving trajectory distribution calculation are proposed to analyze the durability of ground vehicles effectively. To achieve this aim, the driving trajectory of a vehicle and the driving trajectory distribution of that are needed, in addition to road profile. The road profiles can be measured by a profilometer but a driving trajectory of a vehicle cannot be acquired effectively due to a large position error from a conventional GPS sensor. Therefore two techniques are proposed to reduce the position error of a vehicle and achieve the distribution of driving trajectory of that. The driving trajectory calculation technique produces relative positions by using the velocity, time and heading of a vehicle. The driving trajectory distribution calculation technique produces distributions of the driving trajectory by using axis transformation, estimating reference line, dividing sectors and plotting a histogram of the sectors. As a results of this study, we can achieve the considerably accurate driving trajectory and driving trajectory distribution of a vehicle.

• Journal of ILASS-Korea
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• v.24 no.2
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• pp.73-81
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• 2019

It is expected that the introduction of real-driving emission will strengthen the exhaust emission. However, various researches have been reported that real-driving emission has been influenced by factors such as characteristics of the test routes and driving characteristics for drivers. In order to reflect this effect, European Commission applied the concept of driving dynamics to prevent deliberately driving of excessive and acceleration over RDE test. The purpose of this study is to analyze the characteristics of exhaust emissions according to real-driving test in three test routes and driving style. As a result of the test, it was confirmed that when the same driver tested real-driving test under three test routes, it depends on the driving characteristics of the route. Also, RDE-NOx for driving style was that severe driving has been about 16 times higher than normal driving in KNUT route.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.717-722
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• 2003

A driving simulator is a computer-controlled tool to study an interface between a driver and vehicle response by enabling the driver to participate in judging vehicle characteristics. Using the driving simulator, human factor study, vehicle system development and other research can be effectively done under controllable, reproducible and non-dangerous conditions. An Adaptive Cruise Control (ACC) system is generally regarded as a system that can be achieved in the near future without the demanding infrastructure components and technologies. ACC system is an automatic vehicle following system with no human engagement in the longitudinal vehicle direction. And the influence of the driver is substantial in developing the system. Driving characteristic is very different according to the accident riskiness, gender, age and so on. In this research, experiments have been carried out to investigate driving characteristics with the ACC system, using a driving simulator. Participants are 21 male and 19 female. Driving characteristics such as preferred headway-time, lane keeping ability, eye direction, and head movement have been observed and compared between the driving with ACC and the driving without ACC.

• Journal of the Korean Society of Safety
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• v.28 no.5
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• pp.66-70
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• 2013

This study examined the relative effects of education and eco-IVIS(in-vehicle information system) to reduce fuel consumption and greenhouse gas emissions. Also the study investigated the increasing of driving workload when drivers interact with intervention technique. Thirty participants randomly assigned into two groups(training and eco-IVIS) and conducted driving before and after the each intervention technique. While driving, we observed three driving behaviors: Frequency of excessive RPM, percent of speeding, and mean fuel efficiency. Also the Driver Activity Load Index was used to rate participants' subjective ratings of driving workload. Although the results showed positive impact of both education and eco-IVIS to increasing the eco-driving behaviors, eco-IVIS was more effective than education. However, we found comparable level of driving workload in the education and eco-IVIS.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.1
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• pp.41-45
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• 2012

Until now, most studies of foot moving or driving posture have been performed under laboratory driving conditions. But there are many different things between actual driving conditions and laboratory driving conditions because, in laboratory conditions, it is hard to consider vehicle's noise, vibration and people's psychology state while driving. Thus this study is performed through actual driving conditions. And while driving test, we recorded driver's foots with 2 cameras to investigate foots(left and right) heel point and how human foots move to control the three pedals : accel, brake and footrest.. Through driving test, the results of this study show that the position of driver's heel point isn't related to stature and tends to be generalized.

• Journal of Auto-vehicle Safety Association
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• v.10 no.1
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• pp.38-44
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• 2018

This paper presents an analysis on driving safety in lane change situation based on road driving data. Autonomous driving is a global trend in vehicle industry. LKAS technologies are already applied in commercial vehicle and researches about lane change maneuver have been actively studied. In autonomous vehicle, not only safety control issue but also imitating human driving maneuver is important. Driving data analysis in lane change situation has been usually dealt with ego vehicle information such as longitudinal acceleration, yaw rate, and steering angle. For this reason, developing safety index according to surrounding vehicle information based on human driving data is needed. In this research, driving data is collected from perception module using LIDAR, radar and RT-GPS sensors. By analyzing human driving pattern in lane change maneuver, safety index that considers both ego vehicle and surrounding vehicle state by using relative velocity and longitudinal clearance has been designed.

• Proceedings of the Safety Management and Science Conference
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• 2008.11a
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• pp.569-578
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• 2008

The aim of this study is to propose economical safety driving speed index which those are geometric road status; examine the levels of which those cost-benefit of driving fuel expenditure; are search road safety design and operational technology for driving simulators. For the objective, we analyzed the current status of driving fuel expenditure and driving scenarios by the road alignments, and reviewed driving and technical specifications by the geometric types of road according to the implementation, and extended completion. Throughout the result of this study, diverse related driving information provision service, efficiently driving system is expected to be implemented in the national highway design system.

• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.60-69
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• 2022

Recently, the importance of simulation validation in a virtual environment for autonomous driving system validation is increasing. At the same time, interest in the advancement of the virtual driving environment is also increasing. To develop autonomous driving technology, a simulation environment similar to the real-world environment is needed. For this reason, not only the road model is configured in the virtual driving environment, but also the driving environment configuration that includes the surrounding environments -traffic, object, etc- is necessary. In this article, FMTC, which is a test bed for autonomous vehicles, is implemented in a virtual environment and advanced to form a virtual driving environment similar to that of real FMTC. In addition, the similarity of the virtual driving environment is verified through comparative analysis with the real FMTC.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.39-47
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• 2023

The development of autonomous driving and Advanced Driver Assistance System (ADAS) technology has grown rapidly in recent years. As most traffic accidents occur due to human error, self-driving vehicles can drastically reduce the number of accidents and crashes that occur on the roads today. Obviously, technical advancements in autonomous driving can lead to improved public driving safety. However, due to the current limitations in technology and lack of public trust in self-driving cars (and drones), the actual use of Autonomous Vehicles (AVs) is still significantly low. According to prior studies, people's acceptance of an AV is mainly determined by trust. It is proven that people still feel much more comfortable in personalized ADAS, designed with the way people drive. Based on such needs, a new attempt for a customized ADAS considering each driver's driving style is proposed in this paper. Each driver's behavior is divided into two categories: assertive and defensive. In this paper, a novel customized ADAS algorithm with high classification accuracy is designed, which divides each driver based on their driving style. Each driver's driving data is collected and simulated using CARLA, which is an open-source autonomous driving simulator. In addition, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) machine learning algorithms are used to optimize the ADAS parameters. The proposed scheme results in a high classification accuracy of time series driving data. Furthermore, among the vast amount of CARLA-based feature data extracted from the drivers, distinguishable driving features are collected selectively using Support Vector Machine (SVM) technology by comparing the amount of influence on the classification of the two categories. Therefore, by extracting distinguishable features and eliminating outliers using SVM, the classification accuracy is significantly improved. Based on this classification, the ADAS sensors can be made more sensitive for the case of assertive drivers, enabling more advanced driving safety support. The proposed technology of this paper is especially important because currently, the state-of-the-art level of autonomous driving is at level 3 (based on the SAE International driving automation standards), which requires advanced functions that can assist drivers using ADAS technology.

• Korean Journal of Culture and Social Issue
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• v.20 no.2
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• pp.107-131
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• 2014

This driving simulation study examined relative differences in driving anger as the functions of drivers' gender and driving experiences, and actor-observer perspectives when they were exposed in two anger-provoking driving scenarios(cutting-in and sudden stop). The results showed the followings. First, neither drivers' gender nor driving experience, when they were considered independently of the driving situation types and actor-observer perspectives, yielded significant difference in driving anger. Second, actor-observer effect on driving anger was observed only in the cutting-in condition where other driver's intension was emphasized. Third, the female drivers of low driving experience tended to show the strongest tendency of actor-observer bias in the cutting-in condition. These results suggested that the levels of driving anger as the functions of drivers' gender and driving experience can be differed by types of driving situation as well as perspectives of drivers' interpreting the situations.