http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
이하식,김의진,박수진,고승영,박호철 대한교통학회 2019 대한교통학회지 Vol.37 No.4
In vehicle-pedestrian crashes, it is necessary to reflect the crash exposure, which can be divided into vehicle traffic volume and pedestrian traffic volume, in order to accurately estimate the crash. However, it is difficult to measure the pedestrian traffic volume due to the pedestrian characteristics compared to vehicle traffic volume. Previous studies have estimated the pedestrian traffic volume by using a travel survey or demographics of traffic zones, but those are costly and have a limitation in reflecting pedestrian traffic patterns well. In this study, we estimate the pedestrian traffic volume by using smart card data in which actual pedestrian traffic patterns are reflected, and suggest a pedestrian safety performance functions based on this. The pedestrian traffic volume is derived by using the floating population around the public transit nodes, and the vehicle traffic volume is reflected as the length of the hierarchically classified road. The suggested method is applied to the city of Seoul, which has high public transportation mode shares, smart card data, and road GIS information. In this study, the Seoul area is divided into a grid of 500m×500m, and the number of expected crash occurrences in the grid sections is estimated by negative binomial regression. As a result, the McFadden pseudo R2 of the estimated model is 0.65, which indicates that the model could explain the vehicle-pedestrian crash well, and all the variables are statistically significant. In addition, based on the model, we select vulnerable sections of the vehicle-pedestrian crash and analyze the causes. This study shows that pedestrian safety evaluation based on smart card data can be utilized fully. 보행 교통사고를 정확히 추정하기 위해서는 사고 노출률인 보행 및 차량 통행량을 정확히 반영해야 한다. 그러나 보행사고 노출률에 있어 차량통행량에 비해 보행통행량은 보행특성으로 인해 측정에 어려움이 있다. 이를 보완하기 위해 기존 연구에서는 보행통행량을 직접 조사하거나 인구지표 등을 활용하여 추정하였으나 이는 많은 비용이 소요되며 보행 통행패턴을 반영하기에 한계가 있다. 본 연구에서는 이를 개선하기 위해 사람들의 통행패턴이 반영된 교통카드 자료를 이용하여 보행교통량을 산정하며 이를 바탕으로 보행안전성능함수를 제안한다. 보행교통량은 정류장 유동인구를 통해 추정되며, 차량교통량은 정해진 구간 내 위계별 도로 길이로써 반영하였다. 제안된 방법론은 대중교통 수단분담율이 높고, 교통카드 및 도로 GIS 정보가 구축되어 있는 서울시를 대상으로 적용된다. 본 연구에서는 서울시를 500m×500m 크기의 격자로 나누고, 해당 격자구간의 기대사고건수를 음이항 회귀분석을 통해 추정한다. 분석 결과 구축한 모형의 McFadden’s Pseudo R2의 값이 0.65로 나타나 보행사고건수에 대한 설명력이 높음을 확인하였고, 사용된 보행사고 노출률 변수들도 통계적으로 유의한 결과를 보인다. 또한 분석 결과를 이용하여 서울시 보행사고 및 교통약자 보행사고 취약 구간을 선정하고, 그 원인을 분석한다. 본 연구는 교통카드 자료를 기반으로 한 보행사고 안전성 평가가 충분히 활용될 수 있음을 보여준다.
이하식(Lee Ha-Shik),이강희(Lee Kang-Hee) 대한건축학회 2009 대한건축학회 학술발표대회 논문집 - 계획계/구조계 Vol.29 No.1(계획계)
In this paper, it aimed at classifying the mixed-use building into function, circulation, relation according to the public and private space and the building shape to provide the design information such as land area, functional complex, accessibility, etc.. The classification of the mixed-use buildings is divided into four areas. The data are collected with foreign countries in Japan, Europe and US. Results of the study are as follows; First, the commercial function is mainly centered with other functions. Second, after studied the development scale, accessibility, building form, the commercial and residential area overwhelmly share at the total area.
생존 분석을 활용한 서울시 도시고속도로 병목구간 혼잡발생 확률추정 연구
이진학,한영준,이하식,김도경 한국도로학회 2023 한국도로학회논문집 Vol.25 No.2
PURPOSES : Traffic congestion on freeway generally occurs when the traffic volume exceeds the road capacity. Most traffic manuals *such as the Korean Highway Capacity Manual) present the highway capacity as approximately 2,000 units/hour. However, in the real world, freeway congestion occurs for various reasons, including unusual driver behaviors, physical road limitations, and large traffic volumes. Thus, the flow rate at a traffic breakdown can have a wide range of volumes. Therefore, using 5-min volume and speed data from the field, this study explores the stochastic features of traffic breakdowns on major urban freeways in Seoul. METHODS : First, a breakdown point is defined by applying a wavelet transform to identify the sharp drop in the speed data near freeway bottlenecks. Second, based on the flow rate at and before a breakpoint, a survival analysis is performed to construct the probability distributions of the traffic breakdown. Log-rank tests are also conducted to verify the similarities of the distributions between freeways. RESULTS : The analysis results confirm the stochastic features of the urban freeways in Seoul. Specifically, the freeways have typical S-shaped distributions of breakdown probabilities. However, the distributions rise steeply (exceeding a 50% of breakdown probability) at flow rates of 1,150 vphpl to 1,700 vphpl; this is lower than the general expectation. CONCLUSIONS : The statistical differences in the probability distributions for freeways indicates that applying a general standard to every urban highway could raise problems. This study has a limitation in identifying the specific causes of traffic congestion owing to the by physical relationships between individual vehicles. An investigation if vehicle trajectory data should be conducted to examine these aspects in further detail.