• Journal of Auto-vehicle Safety Association
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• v.15 no.2
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• pp.42-48
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• 2023

In recent years, automated vehicles have garnered attention in the multidisciplinary research field, promising increased safety on the road and new opportunities for passengers. High-Definition (HD) maps have been in development for many years as they offer roadmaps with inch-perfect accuracy and high environmental fidelity, containing precise information about pedestrian crossings, traffic lights/signs, barriers, and more. Demonstrating autonomous driving requires verification of driving on actual roads, but this can be challenging, time-consuming, and costly. To overcome these obstacles, creating HD maps of real roads in a simulation and conducting virtual driving has become an alternative solution. However, existing HD maps using high-precision data are expensive and time-consuming to build, which limits their verification in various environments and on different roads. Thus, it is challenging to demonstrate autonomous driving on anything other than extremely limited roads and environments. In this paper, we propose a new and simple method for implementing HD maps that are more accessible for autonomous driving demonstrations. Our HD map combines the CARLA simulator and OpenStreetMap (OSM) data, which are both open-source, allowing for the creation of HD maps containing high-accuracy road information globally with minimal dependence. Our results show that our easily accessible HD map has an accuracy of 98.28% for longitudinal length on straight roads and 98.42% on curved roads. Moreover, the accuracy for the lateral direction for the road width represented 100% compared to the manual method reflected with the exact road data. The proposed method can contribute to the advancement of autonomous driving and enable its demonstration in diverse environments and on various roads.

• Journal of the Korea Society of Computer and Information
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• v.17 no.4
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• pp.31-39
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• 2012

On rainy days, water films form on wet road surfaces and reduce the braking force of vehicles, which often ends up in accidents. For safe driving, the road information signage provides information on road and weather conditions warning drivers of wet road conditions. Still, current information on road conditions is neither localized nor detailed but universal. The present study used the images on CCTVs installed on roads to compare the images of road surfaces in an attempt to suggest a mechanism determining factors that hamper safe driving based on the images. In the image comparison, a normal road image taken on a sunny day is used as an original image, against which road conditions occurring on rainy days are categorized and determined on a case-by-case basis to provide drivers with early warning for the sake of safe driving.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.4
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• pp.94-109
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• 2024

As autonomous vehicles are allowed to drive on public roads, there is an increasing amount of on-road data available for research. It has therefore become possible to analyze impacts of autonomous vehicles on traffic safety using real-world data. It is necessary to use indicators that are well-representative of the driving behavior of autonomous vehicles to understand the implications of them on traffic safety. This study aims to derive indicators that effectively reflect the driving stability of autonomous vehicles by analyzing the driving behavior using the Waymo Open Dataset. Principal component analysis was adopted to derive indicators with high explanatory capability for the dataset. Driving stability indicators were separated into longitudinal and lateral ones. The road segments on the dataset were divided into four based on the characteristics of each, which were signalized and unsignalized intersections, tangent road section, and curved road section. The longitudinal driving stability was 35.48% higher in the curved road sections compared to the unsignalized intersections. With regard to the lateral driving stability, the driving stability was 76.08% higher in the signalized intersections than in the unsignalized intersections. The comparison between curved and tangent road segments showed that tangent roads are 146.87% higher regarding lateral driving stability. The results of this study are valuable for the further research to analyze the impact of autonomous vehicles on traffic safety using real-world data.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.6
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• pp.562-572
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• 2015

$NO_x$ emissions from diesel vehicles have been regarded as a main cause of high $NO_2$ concentration in metropolitan area. Recent studies have shown that the on-road $NO_x$ emissions of diesel vehicles are quite higher than the emission limits specified with the pre-defined test method for emission certification. To reduce air pollutants effectively, the discrepancy of emissions in certification and real-driving conditions should be tackled. In this study, the real-driving emissions have been estimated with portable emission measurement system (PEMS). The results of this study have shown that the on-road $NO_x$ emissions from diesel vehicles have been decreased as the introduction of stricter emission regulation, EURO-6, but additional reduction should be still required and robust technologies should be applied to control $NO_x$ in real-driving conditions. RDE-LDV (Real Driving Emission - Light Duty Vehicles) test method being developed in the European Union can represent excessive on-road $NO_x$ emissions of diesel vehicles as applied emission technologies and can be a solution to remove discrepant $NO_x$ emissions between certification and Korean real-driving conditions. Among the $NO_x$ reduction technologies for EURO-6 diesel vehicles, selective catalytic reduction (SCR) system has shown the better performance than lean $NO_x$ trap (LNT) system to control on-road $NO_x$ emissions. Implementing RDE-LDV will require vehicle manufacturers to adopt the more effective $NO_x$ reduction technology in real driving conditions.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.3
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• pp.16-22
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• 2011

This paper presents the potential of in-vehicle data recorder system for monitoring aggressive driving patterns and providing feedback to drivers on their on road behaviour. This system can detect 10 risky types of drivers' driving patterns such as aggressive lane change, sudden brakes and turns with acceleration etc. Vehicle dynamics simulation and vehicle road test have been performed in order to develop driving pattern recognition algorithms. Recorder systems are installed to 50 buses in a single company. Drivers' driving behaviour are monitored for 1 month. The drivers' risky driving data collected by the system are analyzed. Aggressive lane change in 50km/h below is a cause in overwhelming majority of risky driving pattern.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.31-43
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• 2012

Domestic road type-and period-specific driving pattern measurement was required as Korea's participation in developing "Worldwide harmonized light-duty vehicle emission test procedure (WLTP/DHC)" studied by UN WP29. This study measured road driving data reflecting road and traffic conditions of Korea, and analyzed seven types of representative road type-and period-specific driving patterns with driving pattern standardization methodology proposed by WP29. PAMS (Portable Activity Monitoring Systems) equipment was used to collect enormous (35,410km) road driving data. There are significant difference among seven derived driving patterns.

• Journal of the Ergonomics Society of Korea
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• v.29 no.1
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• pp.17-24
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• 2010

There has been recent interest in intelligent vehicle technologies, such as advanced driver assistance systems (ADASs) or in-vehicle information systems (IVISs) that offer a significant enhancement of safety and convenience to drivers and passengers. However, unsuitable design of HMI (Human Machine Interface) must increase driver distraction and workload, which in turn increase the chance of traffic accidents. Distraction in particular often occurs under a heavy driving workload due to multitasking with various electronic devices like a cell phone or a navigation system while driving. According to the 2005 road traffic accidents in Korea report published by the ROad Traffic Authority (ROTA), more than 60% of the traffic accidents are related to driver error caused by distraction. This paper suggests the structure of vehicle environment for real-time driving behavior monitoring system while driving which is can be used the driver workload management systems (DWMS). On-road experiment results showed the feasibility of the suggested vehicle environment for driving behavior monitoring system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.145-154
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• 1998

The effects of secondary task on driving performance and subjective workload were investigated during a simulated driving. The driving performance was determined by the appropriateness of break timing. The driving simulator was provided by the Korea Road Traffic Safety Association. The subjective workload was tested by using a multidimensional measure such as NASA-TLX. Road was categorized into two types: narrow alley and wide street. The secondary task included pushing the number on the cellular phone, pushing radio channel, and conversing with a passenger. Seventeen subjects volunteered in the study. The data were analyzed by using SAS. Results showed that using the cellular phone and pushing channel during driving caused 3∼22% decline of driving performance and 42∼59% increase of subjective workload respectively. These results indicated that the secondary task could be potentially dangerous although there was not a significant performance decrease due to the notable increase of mental workload. In the future, if we can use a more sensitive and realistic driving simulator, the effects of secondary task under a dynamic driving situation can be investigated.

• Journal of Biomedical Engineering Research
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• v.38 no.1
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• pp.32-42
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• 2017

The aim of this study was to evaluate driving performance of Healthy and disabled groups (with or without driver's license) to control steering wheel by using steering assistive devices in the driving simulator. The persons with partial loss of use of all four limbs have problems in operation of the motor vehicle because of functional loss to operate steering wheel. Therefore, if steering assistive devices for grasping the steering wheel are used to control the vehicle on the road in persons with disabilities, the disabled persons can improve mobility in their community life by driving a motor vehicle safely. Ten healthy subjects (with or w/o driver's license) and ten subjects with physical disabilities (with or w/o driver's license) were involved in this study to evaluate driving performance to operate steering wheel by using four types of steering assistive devices (Single-pin, V-grip, Palm-grip, Tri-pin) in driving simulator. STISim Drive 3 software was used to test the steering performance in four scenarios: straight road at low and high speed of vehicle (40 km/h and 80 km/h), curved road at low and high speed of vehicle (40 km/h and 80 km/h). This study used two-way ANOVA in order to compare the effects of two factors (type of steering assistive device and subject group) in the three dependent variables of driving performance (the lateral position of vehicle, standard deviation of lateral position representing the variation of the left and right movement of the vehicle and the number of line crossing). The mean values of the three dependent variables (lateral position, standard deviation of lateral position, the number of line crossing) of steering performance were statistically significantly smaller for the healthy or disabled groups with driver's license than the other groups without driver's license on the curved road at high speed of vehicle compared to low speed of vehicle.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.208-214
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• 2014

Vehicle dynamic states used in various advanced driving safety systems are influenced by road geometry. Among the road geometry information, the vehicle pitch angle influenced by road slope and acceleration-deceleration is essential parameter used in pose estimation including the navigation system, advanced adaptive cruise control and others on sag road. Although the road slope data is essential parameter, the method measuring the parameter is not commercialized. The digital map including the road geometry data and high-precision DGPS system such as DGPS(Differential Global Positioning System) based RTK(Real-Time Kinematics) are used unusually. In this paper, low-cost cascade extended Kalman filter(CEKF) based road slope estimation method is proposed. It use cascade two EKFs. The EKFs use several measured vehicle states such as yaw rate, longitudinal acceleration, lateral acceleration and wheel speed of the rear tires and 3 D.O.F(Degree Of Freedom) vehicle dynamics model. The performance of proposed estimation algorithm is evaluated by simulation based on Carsim dynamics tool and T-car based experiment.