• 로봇학회논문지
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• 제9권1호
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• pp.1-10
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• 2014

In recent years, the research of 3D mapping technique in urban environments obtained by mobile robots equipped with multiple sensors for recognizing the robot's surroundings is being studied actively. However, the map generated by simple integration of multiple sensors data only gives spatial information to robots. To get a semantic knowledge to help an autonomous mobile robot from the map, the robot has to convert low-level map representations to higher-level ones containing semantic knowledge of a scene. Given a 3D point cloud of an urban scene, this research proposes a method to recognize the objects effectively using 3D graph model for autonomous mobile robots. The proposed method is decomposed into three steps: sequential range data acquisition, normal vector estimation and incremental graph-based segmentation. This method guarantees the both real-time performance and accuracy of recognizing the objects in real urban environments. Also, it can provide plentiful data for classifying the objects. To evaluate a performance of proposed method, computation time and recognition rate of objects are analyzed. Experimental results show that the proposed method has efficiently in understanding the semantic knowledge of an urban environment.

• ETRI Journal
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• 제45권5호
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• pp.746-757
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• 2023

This study presents a novel safe landing algorithm for urban drone deliveries. The rapid advancement of drone technology has given rise to various delivery services for everyday necessities and emergency relief efforts. However, the reliability of drone delivery technology is still insufficient for application in urban environments. The proposed approach uses the "landing angle control" method to allow the drone to land vertically and a rapidly exploring random tree-based collision avoidance algorithm to generate safe and efficient vertical landing paths for drones while avoiding common urban obstacles like trees, street lights, utility poles, and wires; these methods allow for precise and reliable urban drone delivery. We verified the approach within a Gazebo simulation operated through ROS using a six-degree-of-freedom drone model and sensors with similar specifications to actual models. The performance of the algorithms was tested in various scenarios by comparing it with that of stateof-the-art 3D path planning algorithms.

• 대한토목학회논문집
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• 제29권1D호
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• pp.111-120
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• 2009

최근 우리나라에서는 도시공간구조를 자동차 중심형 에너지 다소비형에서 대중교통과 보행을 우선하는 형태로 재편하여 대중교통이용자의 편의를 도모하는 동시에 에너지소비를 줄이려는 노력이 확대되고 있다. 우리나라의 도시는 미국과 유럽의 도시들에 비해 상대적으로 고밀로 개발되어 있고 대중교통서비스도 상대적으로 양호하여 대중교통중심형 도시구조로의 발전 잠재력은 매우 높다고 할 수 있다. 그러나 현재 우리나라의 도시들은 선진국의 주요도시들에 비해 대중교통수송분담률이 낮고 도시환경의 질도 상대적으로 낮다. 본 연구의 목적은 우리나라 도시들이 대중교통중심형 도시로 탈바꿈하기 위하여 풀어 나가야 할 도시구조상의 문제가 무엇인지 분석하는데 있다. 이를 위해 본 연구에서는 수도권 내에 위치한 대중교통결절점을 중심으로 실태를 조사하여 토지이용밀도, 토지이용복합성, 보행편의성, 대중교통연계 측면에서의 문제점을 분석하였다. 또한 분석 결과를 토대로 우리나라 도시들이 대중교통중심형 도시공간구조로 전환되기 위한 도시계획 측면의 개선방향을 제시하고자 한다.

• 한국지역지리학회지
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• 제3권2호
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• pp.227-253
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• 1997

21C는 문화 예술의 시대가 될 것임을 예고하고 있다. 따라서 전통적으로 지역을 연구해 온 지리학은 지역 문화에 대한 심층적 연구를 필요로 하게 되었다. 지역 문화를 밝힐 수 있는 중요한 것 중의 하나가 지역의 상징이다. 오늘날 지구 도시의 출현과 더불어 특히 도시 문화에 대한 연구는 시대적 요청이 되고 있다. 도시 문화를 도시의 상징 즉 한국 각 도시가 제정하고 있는 상징 노래(시가(市歌)), 상징새(시조(市鳥)), 상짐꽃(시화(市花)), 상징 나무(시목(市木))를 통해 분석하여 도시 상징의 공간 환경을 밝혀 보고자 한다. 한국 도시의 상징 노래를 분석해 보면 노래가사 속에는 공간 환경 요소를 포함하고 있는데, 그 중 지형 주로 산과 강의 명칭 그리고 해당 지역의 지명은 거의 모든 노래 가사 속에서 나타나고 있다. 이러한 공간 환경 요소들은 특정 도시의 정체성을 나타내 주며, 그 시민들의 통합성과 일체감을 불러일으키는 상징적 공간으로 볼 수 있다. 특히, 산 및 강과 관련된 지명은 국토의 70%가 산지지형인 우리나라에서는 풍수의 기본 요소로서 산 및 물과 관련된 상징적 공간으로 볼 수 있다. 지명 또한 그 지역의 이미지를 잘 나타내는 상징적 공간이 핀다. 한국 도시의 상징물 즉 상징새, 상징 나무, 상징꽃 분석을 통해 한국 도시의 상징물은 중복 제정이 많다. 특히 상위 계층의 상징물이 하위 계층에서 중복 제정되었다는 점이다. 이러한 상징물들은 우리 민족의 삶을 통해 내려온 상징의 공간 환경으로 볼 수 있으나, 해당 도시의 기후, 토양 등 공간 환경적 특성과 상관없이 중복 제정된 점과 정체성이 없는 외래종이 많은 점은 시대적으로 상징물을 재검토해야 할 필요성이 있다. 가장 지방적인 것이 가장 지구적인 것이 되어야 할 시대에 우리의 기후, 토양, 문화적 특성에 맞는 도시의 상징물을 정할 것이 요망된다.

• 자동차안전학회지
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• 제14권3호
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• pp.65-70
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• 2022

Lane change in urban environments is a challenge for both human-driving and automated driving due to their complexity and non-linearity. With the recent development of deep-learning, the use of the RNN network, which uses time series data, has become the mainstream in this field. Many researches using RNN show high accuracy in highway environments, but still do not for urban environments where the surrounding situation is complex and rapidly changing. Therefore, this paper proposes a lane change possibility decision network by adopting Attention layer, which is an SOTA in the field of seq2seq. By weighting each time step within a given time horizon, the context of the road situation is more human-like. A total 7D vectors of x, y distances and longitudinal relative speed of side front and rear vehicles, and longitudinal speed of ego vehicle were used as input. A total 5,614 expert data of 4,098 yield cases and 1,516 non-yield cases were used for training, and the performance of this network was tested through 1,817 data. Our network achieves 99.641% of test accuracy, which is about 4% higher than a network using only LSTM in an urban environment. Furthermore, it shows robust behavior to false-positive or true-negative objects.

• 반도체디스플레이기술학회지
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• 제22권2호
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• pp.112-119
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• 2023

In urban environments, signals of Global Positioning System (GPS) can be blocked and reflected by tall buildings, large vehicles, and complex components of road network. Therefore, the performance of the positioning system using the GPS module in urban areas can be degraded due to the loss of GPS signals necessary for the position estimation. To deal with this issue, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope and accelerometer, and Bayesian filters, such as Kalman filter (KF) and particle filter (PF), have been designed to enhance the performance of the GPS-based positioning system. Among Bayesian filters, the PF has been widely used for the target tracking and vehicle navigation, since it can provide superior performance in estimating the state of a dynamic system under nonlinear/non-Gaussian circumstance. This paper presents a positioning system that uses the double-stacked particle filter (DSPF) as well as the accelerometer, gyroscope, and GPS receiver on the smartphone to provide higher pedestrian positioning accuracy in urban environments. The DSPF employs a nonparametric technique (Parzen-window) to create the multimodal target distribution that approximates the posterior distribution. Experimental results show that the DSPF-based positioning system can provide the significant improvement of the pedestrian position estimation in urban environments.

• 한국대기환경학회지
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• 제34권5호
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• pp.697-707
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• 2018

A fast running model comprising the climate change effects is proposed for urban heat environment simulations so as to be used in urban heat island studies and/or the urban planning practices. By combining Hot City Model, a high resolution urban temperature prediction model utilizing the Lagrangian particle tracing technique, and the numerical weather simulation data which are constructed up to year of 2100 under the climate change scenarios, an efficient model is constructed for simulating the future urban heat environments. It is applicable to whole city as well as to a small block area of an urban region, with the computation time being relatively short, requiring the practically manageable amount of the computational resources. The heat environments of the entire metropolitan Seoul area in South Korea are investigated with the aid of the model for the present time and for the future. The results showed that the urban temperature gradually increase up to a significant level in the future. The possible effects of green roofs on the buildings are also studied, and we observe that green roofs don't lower the urban temperature efficiently while making the temperature fields become more homogeneous.

• 한국조경학회지
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• 제15권1호
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• pp.69-84
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• 1987

According to the complexity and the pluralism of the modern cities, they are changing themselves into the multinoded and social - classless urban environments. The sudden drift of population to the cities is giving rise to the serious environmental problems, and the rapid increase of recreational needs among the citizen is changing the urban society into a leisure - oriented one. In order to coping with the abrupt change in the social and natural urban environments, the various fields of urban society should be co - ordinated. The study uses the green - city concept to get solves the incongruity of urban structure in Chonju City. The existing open space maps were drawn up by the various techniques such as the analysis of the topographic maps and collected data, the interpretation of the aero-photographs and the reconnaissance of site. The authors suggested the existing condition, and the problems and potentials of open space elements in Chonju City through the analysis of the existing condition maps. After synthesizing the contents of analysis, the 7u(hors established an exclusive open space system for Chonju City.

• Journal of Positioning, Navigation, and Timing
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• 제7권4호
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• pp.205-215
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• 2018

The recent emergence of new Global Navigation Satellite Systems (GNSS) has resulted in a gradual improvement in the performance of positioning services. This paper verifies the degree of improvement in positioning performance of Assisted-GNSS (A-GNSS) receivers using assistance information compared to standalone-GNSS receivers that do not use assistance information in various urban environments in Korea. For this purpose, field tests are performed in various urban and indoor environments in Korea. The assistance information is provided by u-blox's AssistNow Online and low-cost commercial receivers are used for mobile station receivers. Through experiments, the Time to First Fix (TTFF), acquisition sensitivity, and position accuracy performance improvement are analyzed. The results of the experiments show that using assistance data improved the performance in all experiment locations, and, in particular, a significant performance improvement in terms of TTFF.

• 제어로봇시스템학회논문지
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• 제17권5호
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• pp.436-443
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• 2011

Recognition of structures in urban environments is a fundamental ability for unmanned ground vehicles. In this paper we propose the geometrical featured voxel which has not only 3-D coordinates but also the type of geometrical properties of point cloud. Instead of dealing with a huge amount of point cloud collected by range sensors in urban, the proposed voxel can efficiently represent and save 3-D urban structures without loss of geometrical properties. We also provide an urban structure classification algorithm by using the proposed voxel and machine learning techniques. The proposed method enables to recognize urban environments around unmanned ground vehicles quickly. In order to evaluate an ability of the proposed map representation and the urban structure classification algorithm, our vehicle equipped with the sensor system collected range data and pose data in campus and experimental results have been shown in this paper.