교통카드 데이터는 도시 유동 패턴 분석을 가능하게 하는 양질의 대용량 데이터를 제공한다. 하지만 유동 클러스터링의 방법론적 어려움으로 인해 기존의 연구들은 데이터의 이점을 최대로 활용하지 못하고 있다. 이러한 한계를 극복하고자, 본 연구는 교통카드 데이터에 기반한 효율적인 유동 클러스터 탐지 기법을 제시하고, 이를 서울시 대중교통 통행 데이터에 적용하여 유의미한 유동 통행 클러스터를 도출하고자 한다. 사례 분석 결과, 서울 전체에 걸쳐 있는 다양한 대중교통 통행 클러스터를 도출할 수 있었고, 특히 공간상에서는 인접하지만 서로 다른 교통수단과 노선 하에서 이루어진 개별 유동들을 하나의 유동 통행 패턴으로 탐지할 수 있었다, 더 나아가, 일반적인 빈도분석으로는 뚜렷하게 나타나지 않지만 공간적으로 인접한 여러 다발의 유동이 모였을 때 유의미한 통행량을 가지게 되는 주요 통행 패턴을 포착할 수 있었다. 본 연구는 유동 현상을 분석하는데 중요한 방법론적 시사점을 제시하고 있으며, 제시된 알고리즘은 향후 보다 진보된 유동 클러스터링 기법을 개발하는데 필요한 기초 결과로 활용될 수 있을 것으로 기대된다.

PURPOSES : This study prioritizes the potential technology for establishing an efficient traffic control in the ramp junction of urban deep underground tunnels in the future. We considered most of the applicable technologies that ensure traffic safety at the on-off ramp junction. METHODS : This study proposes a methodology to prioritize the applicable technology for establishing efficient traffic control in the ramp junction of an urban deep underground tunnel using an analytical hierarchy process (AHP). First, an AHP structure was developed. Second, an individual survey was conducted to collect the opinions of road and transportation experts. Based on the survey results, weights were estimated depending on the relevant criteria of the developed structure. The estimated weights were verified using the consistency index (CI) and consistency ratio (CR). In addition, a sensitivity analysis was performed to confirm the reliability of the estimated weights. Finally, the potential technology for an efficient traffic control in the ramp junction of an urban deep underground tunnel was prioritized. RESULTS : In the first level of hierarchy, traffic demand control had the highest priority, and ramp metering, section speed control, and shoulder lane control were selected in the second level of hierarchy. CONCLUSIONS : These results implied that prioritizing would be useful in establishing traffic operation strategies for traffic safety when constructing and opening deep underground tunnels in urban areas in the future.

Assessment of noise exposed population is to check the environment noise level and social influence in order to reduce the risks such as annoyance and disturbance that are generated by environmental noise. Also, this method suggests the preferential noise abatement policy and action plan by accurately finding the area that the noise causes harmful effect to human health. Recently, a noise map, which can predict noise in comprehensive area, is used for the assessment of noise exposed population, breaking from the methods using existing measures. In particular, countermeasure for noise can be considered more effectively by using assessment methods of noise exposed population for specific noise level, area and building types which are the main input factors in noise maps. In this study, we propose noise prediction at traffic noise due to noise map.

PURPOSES : For vehicle-alone accidents with a high mortality rate, it is necessary to analyze the factors influencing the severity of roadside fixed-object traffic accidents. METHODS : A total of 313 roadside fixed obstacle traffic accidents, variables related to fixed obstacles, and variables related to road geometry were collected. The estimation model was constructed with data collected using an ordinal probit regression model. RESULTS : Piers, vertical slopes, and distances between roads and objects were the primary causes of increased accident severity. CONCLUSIONS : Countermeasures, such as object removal, relocation, clear zones, frangibles, breakaway poles, etc., are required for accident-prone or dangerous points.