• Journal of Environmental Science International
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• v.16 no.3
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• pp.385-392
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• 2007

Currently, portable equipment for recycling of waste asphalt concrete (ASCON) has been used. However, any air pollution control devices are not attached in the simple portable one. Thus, a lot of air pollutants have been produced from recycling processes of waste ASCON which resulted from aging of paved roads or repavement of roads. This study deals with a preliminary result of concentration analysis of air pollutants obtained from a pilot and a real recycling processes of waste ASCON using simple portable recycling equipment. Air pollutants were taken from 4 steps of the pilot recycling process including an initial heating by liquid petroleum gas (LPG), intermediate heating and melting (H&M) process, final H&M process, and pavement processes using recycled ASCON at the recycling site. Also, air pollutants were taken front 4 steps of the real recycling processes including an initial H&M, final H&M and mixing, loading of recycled ASCON to dump trucks, and at the recycling site after leaving the loaded dump trucks for real pavement sites. The air pollutants measured in this study include volatile organic compounds (VOCs), aldehydes, particulate matter (PM: PM1, PM2.5, PM7, PM10, TSP (total suspended particulate)). The identified concentrations of VOCs increased with increasing time or degree for H&M of waste ASCON. In particular, very high concentrations of the VOCs at the status of complete melting, which is exposed to the air, of the waste ASCON just before paving tv the recycled ASCON at the recycling site. Also, considerable amount of VOCs were identified from the recycling equipment after the dump trucks leaded by recycled ASCON leaved the recycling site for the pavement sites. The relative level of formaldehyde exceeded 80% of the aldehydes Identified in the recycling processes. This is because the waste ASCON is exposed to direct flame of LPG during H&M processes. The PM concentrations measured in the winter recycling processes, such as the loading and rotation processes of waste ASCON into/in the recycling equipment for H&M, were much higher than those in the summer ones. In particular, the concentrations of coarse particles such as PM7 and PM10 during the winter recycling were very high as compared those during the summer one.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.173-188
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• 2024

With the advancement of autonomous vehicle (AV) technology, autonomous driving on real roads has become feasible. However, there are challenges in achieving complete autonomy due to perceptual blind areas, which occur when the AV's sensory range or capabilities are limited or impaired by surrounding objects or environmental factors. This study aims to analyze AV accident patterns and safety issues of perceptual blind area that may occur in urban areas, with the goal of developing test scenarios for Level 4+ autonomous driving. It utilized AV accident data from the California Department of Motor Vehicles (DMV) to compare accident patterns and characteristics between AVs and conventional vehicles based on activation status of autonomous mode. It also categorized AV disengagement data to identify types and real-world cases of disengagements caused by perceptual blind areas. The analysis revealed that AVs exhibit different accident types due to their safe driving maneuvers, and three types of perceptual blind area scenarios were identified. The findings of this study serve as crucial foundational data for developing Level 4+ autonomous driving test scenarios, enabling the design of efficient strategies to mitigate perceptual blind areas in various scenarios. This, in turn, is expected to contribute to the effective evaluation and enhancement of AV driving safety on real roads.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2619-2625
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• 2011

The GPS technique widely used recently in car navigation system has two problems that are unavailability in urban canyons and inherent positional error rate. The one has been studied and solved in many literatures. However, the other still leads to incorrect locational information in some area, especially parallel roads. This paper proposes and implements a system to recognize lane of moving vehicle based on images obtained from in-vehicle networks or other devices. The proposed system utilizes a real-time image matching algorithm which determines the direction of moving vehicle in parallel section of road. It also employs a method for accuracy improvement. The results obtained from experimental test on real-time navigation show that the proposed systems works well and the accuracy increases.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.2
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• pp.157-165
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• 2016

In wartime conditionsmilitary combat vehicles are required to be driven on rough roads that have significant obstacles. A wheel type dog-horse robot with a rotary suspension system was applied to overcome the obstacles. To achieve real-time analysis, a simplified model was proposed by using velocity transformations. Through comparison with the multi-body dynamics model, the efficiency and accuracy of the proposed modeling was proven.

• Journal of Applied Reliability
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• v.16 no.2
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• pp.90-97
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• 2016

Purpose: Majority of bridges and roads in Gangwon Province have been carrying loads associated with heavy materials such as rocks, mining products, and cement. This location-specific live loads have contributed to the present situation of overloading, compared to other provinces in Korea. However, the bridges in Gangwon province are designed by national bridge design specification, without considering the location-specific live load characteristics. Therefore, this study focuses on the real traffic data accumulated on regional weighing station to verify the live load characteristics, including actual live load gross vehicle weight, axle weight axle spacings, and number of trucks. Methods: In order to take into account the location specific live load, a governmental weigh station (38th national highway Miro) have been selected and the passing truck data are processed. Based on the truck survey, trucks are categorized into 3 different shapes, and each shape has been idealized into normal distribution. Then, the resulting survey data are processed to predict the target maximum live load values, including the axle loads and gross vehicle weights in 75 years service life span. Results: The results are compared to the nationally used DB-24 live loads, and the results show that nationally recognized DB-24 live load does not sufficiently represent real traffic in mountaineous region in Gangwon province. Conclusion: The comparison results in the recommendation of location-specific live load that should be taken into account for bridge design and evaluation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.4
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• pp.1203-1222
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• 2012

To provide active notification and enhance drivers'awareness of their surroundings, a vision-based collision warning system that detects and monitors surrounding vehicles is proposed in this paper. The main objective is to prevent possible vehicle collisions by monitoring the status of surrounding vehicles, including the distance to the other vehicles in front, behind, to the left and to the right sides. In addition, the proposed system collects and integrates this information to provide advisory warnings to drivers. To offer the correct notification, an algorithm based on features of edge and morphology to detect vehicles is also presented. The proposed system has been implemented in embedded systems and evaluated on real roads in various lighting and weather conditions. The experimental results indicate that the vehicle detection ratios were higher than 97% in the daytime, and appropriate for real road applications.

• Journal of Electrical Engineering and Technology
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• v.4 no.1
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• pp.143-148
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• 2009

About 70% of Korea consists of mountainous areas, and during the construction of many roads and railroads, cut slopes are inevitably formed. The rainy season, frost heaving in winter, and thawing in spring can all cause rockfalls and landslides. The failure of these slopes is increasing every year, causing damage to vehicles, personal injury and even death. To protect people and property from such damage, a real-time monitoring system is needed to detect the early stages of slope failures. The GMG placed TRS sensor units in the slopes to monitor them in real-time. But due to its reliance on data lines and power lines, the system is vulnerable to lightning damage. The whole system can be damaged by a single lighting strike. Consequently, for the purposes of this paper we propose the use of the Ubiquitous Sensor Network (USN) which follows the IEEE 802.1.4. By using the USN system we can minimize lightning damage and can monitor the movement of the slopes consistently.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.405-408
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• 2008

Up to now, a lot of houses, roads and other urban facilities have been damaged by natural disasters such as flash floods and landslides. It is reported that the size and frequency of disasters are growing greatly due to global warming. In order to mitigate such disaster, flood forecasting and alerting systems have been developed for the Han river, Geum river, Nak-dong river and Young-san river. These systems, however, do not help small municipal departments cope with the threat of flood. In this study, a real-time urban flood forecasting service (U-FFS) is developed for ubiquitous computing city which includes small river basins. A test bed is deployed at Tan-cheon in Gyeonggido to verify U-FFS. It is found that U-FFS can forecast the water level of outlet of river basin and provide real-time data through internet during heavy rain. Furthermore, it is expected that U-FFS presented in this study can be applied to ubiquitous computing city (u-City) and/or other cities which have suffered from flood damage for a long time.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.39-52
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• 2021

This paper presents a longitudinal acceleration controller that can be applied to real vehicles (nonlinear and time-varing systems) with only a simple experiment regardless of the type of vehicle and the control interface structure. The controller consists of a feedforward term for fast response, a zero-throttle acceleration compensation term, and a feedback term (P gain) to compensate for errors in the feedforward term, and another feedback term (I gain) to respond to disturbances such as slope. In order to easily apply it to real vehicles, there are only two tuning parameters, feedforward terms of throttle and brake control. And the remaining parameters can be calculated immediately when the two parameters are decided. The tuning procedure is also unified so that it can be quickly and easily applied to various vehicles. The performance of the controller was evaluated using MATLAB/Simulink and Truksim's European Ben model. In addition, the controller was successfully implemented to 3 medium-sized vehicle (HMC Solati), which is composed of different control interface characteristic. Vehicle driving performance was evaluated on the test track and on the urban roads in Siheung and Seoul.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.121-129
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• 2015

This paper presents a multiple vehicle recognition algorithm based on radar and vision sensor fusion for lane change assistance. To determine whether the lane change is possible, it is necessary to recognize not only a primary vehicle which is located in-lane, but also other adjacent vehicles in the left and/or right lanes. With the given sensor configuration, two challenging problems are considered. One is that the guardrail detected by the front radar might be recognized as a left or right vehicle due to its genetic characteristics. This problem can be solved by a guardrail recognition algorithm based on motion and shape attributes. The other problem is that the recognition of rear vehicles in the left or right lanes might be wrong, especially on curved roads due to the low accuracy of the lateral position measured by rear radars, as well as due to a lack of knowledge of road curvature in the backward direction. In order to solve this problem, it is proposed that the road curvature measured by the front vision sensor is used to derive the road curvature toward the rear direction. Finally, the proposed algorithm for multiple vehicle recognition is validated via field test data on real roads.