• Title/Summary/Keyword: Road Environment

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A Study on the Safety Policies of Truck Traffic Using Fuzzy-AHP (Fuzzy-AHP를 이용한 화물자동차의 교통안전 대책에 관한 연구)

  • Chen, Maowei;Zhou, Lele;Lee, Hyangsook
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.2
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    • pp.44-61
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    • 2022
  • With the increase of truck traffic, roads are becoming more congested and the risk of accidents is also increasing. Since the fatality rate of traffic accidents caused by trucks is about 2 to 3 times higher than that of passenger cars and buses, it is urgent to prepare policies for truck traffic safety. While most of the previous studies focused on factor analysis that contributes to traffic accidents, this study presented traffic safety policies (4 major-criteria and 12 sub-criteria) for trucks through driver interviews and previous studies. Then, the priority of the policies was evaluated by using Fuzzy-AHP. As a result, the improvement of truck drivers' working environment was evaluated as the most important criteria, and followed by the improvement of road traffic conditions. In detail, there is an urgent need to improve the freight car fare system, ensure sufficient rest for drivers, and strengthen the crackdown of illegal parking and stopping along roads. This study is expected to be usefully utilized in preparing traffic flow safety policies in preparation for the continuous increase of truck traffic.

The Performance Improvement of U-Net Model for Landcover Semantic Segmentation through Data Augmentation (데이터 확장을 통한 토지피복분류 U-Net 모델의 성능 개선)

  • Baek, Won-Kyung;Lee, Moung-Jin;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.38 no.6_2
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    • pp.1663-1676
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    • 2022
  • Recently, a number of deep-learning based land cover segmentation studies have been introduced. Some studies denoted that the performance of land cover segmentation deteriorated due to insufficient training data. In this study, we verified the improvement of land cover segmentation performance through data augmentation. U-Net was implemented for the segmentation model. And 2020 satellite-derived landcover dataset was utilized for the study data. The pixel accuracies were 0.905 and 0.923 for U-Net trained by original and augmented data respectively. And the mean F1 scores of those models were 0.720 and 0.775 respectively, indicating the better performance of data augmentation. In addition, F1 scores for building, road, paddy field, upland field, forest, and unclassified area class were 0.770, 0.568, 0.433, 0.455, 0.964, and 0.830 for the U-Net trained by original data. It is verified that data augmentation is effective in that the F1 scores of every class were improved to 0.838, 0.660, 0.791, 0.530, 0.969, and 0.860 respectively. Although, we applied data augmentation without considering class balances, we find that data augmentation can mitigate biased segmentation performance caused by data imbalance problems from the comparisons between the performances of two models. It is expected that this study would help to prove the importance and effectiveness of data augmentation in various image processing fields.

Major environmental factors and traits of invasive alien plants determining their spatial distribution

  • Oh, Minwoo;Heo, Yoonjeong;Lee, Eun Ju;Lee, Hyohyemi
    • Journal of Ecology and Environment
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    • v.45 no.4
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    • pp.277-286
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    • 2021
  • Background: As trade increases, the influx of various alien species and their spread to new regions are prevalent and no longer a special problem. Anthropogenic activities and climate changes have made the distribution of alien species out of their native range common. As a result, alien species can be easily found anywhere, and they have nothing but only a few differences in intensity. The prevalent distribution of alien species adversely affects the ecosystem, and a strategic management plan must be established to control them effectively. To this end, hot spots and cold spots were analyzed according to the degree of distribution of invasive alien plants, and major environmental factors related to hot spots were found. We analyzed the 10,287 distribution points of 126 species of alien plants collected through the national survey of alien species by the hierarchical model of species communities (HMSC) framework. Results: The explanatory and fourfold cross-validation predictive power of the model were 0.91 and 0.75 as AUC values, respectively. The hot spots of invasive plants were found in the Seoul metropolitan area, Daegu metropolitan city, Chungcheongbuk-do Province, southwest shore, and Jeju island. Generally, the hot spots were found where the higher maximum temperature of summer, precipitation of winter, and road density are observed, but temperature seasonality, annual temperature range, precipitation of the summer, and distance to river and sea were negatively related to the hot spots. According to the model, the functional traits accounted for 55% of the variance explained by the environmental factors. The species with higher specific leaf areas were more found where temperature seasonality was low. Taller species preferred the bigger annual temperature range. The heavier seed mass was only preferred when the max temperature of summer exceeded 29 ℃. Conclusions: In this study, hot spots were places where 2.1 times more alien plants were distributed on average than non-hot spots (33.5 vs 15.7 species). The hot spots of invasive plants were expected to appear in less stressful climate conditions, such as low fluctuation of temperature and precipitation. Also, the disturbance by anthropogenic factors or water flow had positive influences on the hot spots. These results were consistent with the previous reports about the ruderal or competitive strategies of invasive plants instead of the stress-tolerant strategy. The functional traits are closely related to the ecological strategies of plants by shaping the response of species to various environmental filters, and our result confirmed this. Therefore, in order to effectively control alien plants, it is judged that the occurrence of disturbed sites in which alien plants can grow in large quantities is minimized, and the river management of waterfronts is required.

Analysis of Urban Environmental Factors Affecting Illegal Parking: Focused on the Smart Civil Complaints Data in Seoul, Korea (불법 주정차에 영향을 미치는 도시 환경 요인 분석: 서울시 스마트 불편신고 민원자료를 중심으로)

  • Park, Junsang;Lee, Sugie
    • Journal of the Korean Regional Science Association
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    • v.38 no.3
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    • pp.3-17
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    • 2022
  • The automobile-centered lifestyle has provided many advantages to urban residents, but it is also causing various problems. Among them, illegal parking is one of the representative urban problems that negatively affect them. The purpose of this study is to derive the urban environmental factors affecting illegal parking and provide policy implications by using data related to illegal parking among civil complaints about smart inconvenience reports in Seoul in 2019. It was judged that the influencing factors would differ depending on the time of the complaint, and the analysis was conducted by dividing the time of the complaint into a whole day, daytime, and nighttime. As a result of the analysis of this study, it was found that land-use variables and the number of POI facilities were closely related to illegal parking complaints. Also, the subway station area and road width were found to be closely related to illegal parking complaints. On the other hand, parking facilities did not show significant results with illegal parking complaints. This study showed that the use of civic complaint data could be used as important data to identify urban problems that city residents actually experience and to come up with policy implications.

Study on Time-of-day Operation of Pedestrian Signal Based on Residual Pedestrians (잔류보행기반 시간대별 보행신호 운영기법 연구)

  • Chae, HeeChul;Eom, Daelyoung;Yun, Ilsoo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.4
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    • pp.1-17
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    • 2022
  • As pedestrian deaths account for a high proportion of traffic accident deaths in Korea, interest in pedestrian safety is growing. In particular, it is necessary to develop various pedestrian-centered traffic signal operation techniques to improve the pedestrian environment at signal intersections. Therefore, in this study, a method for time-of-day operating a pedestrian signal based on residual pedestrians was studied. To this end, the pedestrian signal operation technique in response to the pedestrian demand, which is operated by extending the pedestrian signal time only during the time when the pedestrian demand and the number of remaining pedestrians increase, was applied to the field. The difference in safety according to the application of the new pedestrian signal operation technique was statistically analyzed. As a result of the analysis, the residual pedestrian rate decreased by 20% (3.3 people) before application and 8% (1.4 people) after application, and the residual pedestrian rate in the crosswalk at the time of red signal decreased by 12% (1.9 people), And it was analyzed that the position of the residual pedestrian decreased by 3.3m from 5.2m before application to 1.9m after application.

Improvement and Estimation of Effect for Speed Limit Tolerance (속도위반 단속 허용범위 개선안 제시 및 효과 추정)

  • Su-hwan Jeong;Kyeung-hee Han;Min-ho Lee;Choul-ki Lee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.2
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    • pp.164-181
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    • 2023
  • In a low speed limit environment, the speed limit tolerance of automated traffic enforcement devices is very high, which is one of the main factors for the low compliance rate. Therefore, in this study, we aimed to the improve the speed limit tolerance and to present a new standard. The effects of the operator and user errors that can cause speeding by drivers were analyzed. Based on the results of the analysis, an improvement of the tolerance was proposed by applying an error in the enforcement device and GPS speed. In addition, long-term expected safety effects such as the accident rate and severity were estimated from the operator's perspective when improving the tolerance. As a result of the estimation, the speed limit compliance rate, accident rate, and change rate of a number of severe accidents due to speed change, and pedestrian traffic accident mortality rate were all improved in all speed limit environments. The introduction of the proposed improvement is expected to improve road safety significantly.

Development of Deep Learning Model for Detecting Road Cracks Based on Drone Image Data (드론 촬영 이미지 데이터를 기반으로 한 도로 균열 탐지 딥러닝 모델 개발)

  • Young-Ju Kwon;Sung-ho Mun
    • Land and Housing Review
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    • v.14 no.2
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    • pp.125-135
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    • 2023
  • Drones are used in various fields, including land survey, transportation, forestry/agriculture, marine, environment, disaster prevention, water resources, cultural assets, and construction, as their industrial importance and market size have increased. In this study, image data for deep learning was collected using a mavic3 drone capturing images at a shooting altitude was 20 m with ×7 magnification. Swin Transformer and UperNet were employed as the backbone and architecture of the deep learning model. About 800 sheets of labeled data were augmented to increase the amount of data. The learning process encompassed three rounds. The Cross-Entropy loss function was used in the first and second learning; the Tversky loss function was used in the third learning. In the future, when the crack detection model is advanced through convergence with the Internet of Things (IoT) through additional research, it will be possible to detect patching or potholes. In addition, it is expected that real-time detection tasks of drones can quickly secure the detection of pavement maintenance sections.

Evaluation of Transportation Policy Using Multidimensional Scaling Method (다차원척도법에 의한 교통정책 평가 인지 차이 분석에 관한 연구)

  • Lee, Won Gyu;Jung, Hun Young;Ko, Sang Seon;Yoon, Hang Mook
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.3D
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    • pp.255-261
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    • 2010
  • The evaluation regarding a transportation policy by an evaluation volition viewpoint there is a difference. Consequently the insurgent analysis which is simple compared to against the evaluation object it was accurate, the analysis which leads the order anger probably is necessary. The research which it sees for the evaluation regarding the transportation policy of the metropolis divided in road being understood, public transportation, parking and pedestrian environment, wide area transportation and transportation information and transportation field whole. And against these field it tried the ALSCAL method and MDPREF method which is a Multidimensional Scale method and it analyzed. The regression analysis result for a dimensional analysis ALSCAL method the case of the transportation policy star improvement degree which it follows in introduction presence of intelligence transportation system and MDPREF method it confronted to the transportation policy star improvement degree which it follows in expansion to construction of specific function appeared with the fact that it is the tendency probably. And the evaluation object and evaluation in the object which will cut the positioning one result was each divided in 4 group. And two methods all it was visible a similar tendency. The ALSCAL method currently transportation system construction degree condition in base and, the MDPREF method currently improvement degree of the transportation policy which it follows in traffic system construction appeared with the fact that it is desirable to establish a hereafter traffic policy in base.

Inter-Lane Distance Measurement Method for Predicting the Lateral Movement of the Vehicle in Front (전방 차량의 횡간 이동 예측을 위한 차선 간 거리 측정 방법)

  • Sung-Jung Yong;Hyo-Gyeong Park;Seo-young Lee;Yeon-Hwi You;Il-Young Moon
    • Journal of Practical Engineering Education
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    • v.14 no.3
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    • pp.593-600
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    • 2022
  • Various sensors such as lidar, radar, and camera are fused and used in autonomous vehicles. Rider and radar sensors are difficult to popularize because they are expensive equipment. In order to popularize autonomous vehicles, research that can replace expensive equipment is continuously being conducted. In this paper, we use a single camera that is inexpensive and can be easily mounted. We propose a method for detecting the wheels and adjacent lanes of a front-side vehicle of a driving vehicle and estimating distances. Our proposed method detects lanes and wheels from frame images after frame extraction via input images. In addition, the distance is measured and compared with the actual distance measured in the actual road environment. The distance could be calculated relatively accurately within the error range of ± 3 cm. Through this, it is expected that the camera can be used as an alternative means when the cost of autonomous vehicles is reduced or when the lidar or radar sensor fails.

Entropy-Based 6 Degrees of Freedom Extraction for the W-band Synthetic Aperture Radar Image Reconstruction (W-band Synthetic Aperture Radar 영상 복원을 위한 엔트로피 기반의 6 Degrees of Freedom 추출)

  • Hyokbeen Lee;Duk-jin Kim;Junwoo Kim;Juyoung Song
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1245-1254
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    • 2023
  • Significant research has been conducted on the W-band synthetic aperture radar (SAR) system that utilizes the 77 GHz frequency modulation continuous wave (FMCW) radar. To reconstruct the high-resolution W-band SAR image, it is necessary to transform the point cloud acquired from the stereo cameras or the LiDAR in the direction of 6 degrees of freedom (DOF) and apply them to the SAR signal processing. However, there are difficulties in matching images due to the different geometric structures of images acquired from different sensors. In this study, we present the method to extract an optimized depth map by obtaining 6 DOF of the point cloud using a gradient descent method based on the entropy of the SAR image. An experiment was conducted to reconstruct a tree, which is a major road environment object, using the constructed W-band SAR system. The SAR image, reconstructed using the entropy-based gradient descent method, showed a decrease of 53.2828 in mean square error and an increase of 0.5529 in the structural similarity index, compared to SAR images reconstructed from radar coordinates.