Earticle

본 연구에서는 5대 광역권의 대중교통 이동성 수준을 평가하기 위해, 교통카드와 내비게이 션 데이터 등 교통 빅데이터를 활용하여 개인교통수단 대비 노선버스의 이동성을 권역별로 측 정하고 실증하였다. 분석 결과, ‘승용차 통행시간’에 대한 ‘버스 통행시간’의 상대비율은 1.20~ 2.42배 수준으로 나타났다. 5대 광역시 중 승용차 대비 버스 통행시간 차이가 가장 낮은 광역시 는 대구(1.20배)이며, 그 차이가 가장 큰 광역시는 울산(2.42배)으로 분석되었다. 추가적으로 각 권역별로 승용차·버스 간의 통행속도 상대지표에 대한 첨두·비첨두 집단간 통계검증을 수행하 였으며, 시간대에 대한 대중교통 이동성 지표 차이도 유의한 수준으로 분석되었다. 본 연구를 통해 대도시권별 노선버스 모빌리티 특성을 기반으로 분석된 대중교통 이동성 지표는 교통수 요예측 과정에서의 버스 특성을 현실적으로 모사하기 위한 수단선택모형 기초자료 및 대중교 통 정책 의사결정 등에 활용될 수 있을 것으로 기대된다.

This study used big data on transportation, including transit cards and navigation data, to measure and empirically analyze the mobility of public buses compared to personal vehicles across five major metropolitan areas. The analysis showed that the ratio of ‘bus travel time' to ‘private car travel time' ranged from 1.20 to 2.42 times. Among the five metropolitan cities, Daegu showed the smallest difference in bus travel time compared to private car travel time (1.20 times), while Ulsan showed the largest difference (2.42 times). In addition, statistical tests were conducted for peak and off-peak groups concerning the relative indicators of car and bus travel speeds for each region, and significant differences in bus mobility measures according to the time of day were analyzed. The bus mobility measures analyzed based on the characteristics of public urban buses in large metropolitan areas are expected to be used as fundamental data for mode choice models to analyze bus characteristics realistically in transportation demand forecasting processes and for decision-making in public transportation policies.

In this paper, we design some new LDPC-coded orthogonal modulation (OM) schemes for high data rate transmissions (HDRT) in the navigation satellite systems. We analyze their error-performance utilizing soft-decision bit metrics and compare them with those of L61 and L62 signals in the quasi-zenith satellite system (QZSS) for centimeter-level augmentation services (CLAS). Compare to the L62 signals of QZSS, both schemes have higher data rates (14.6% increase) and essentially the better error performance at high SNR region. At the region where frame error rate (FER) , one of the proposed schemes has better error performance of 1.4 dB in terms of carrier-to-noise ratio .

Recently autonomous vehicles and connected cars are being equipped with various information and communication technology (ICT). The installed ICT on such vehicles and cars makes it possible to record events generated during communication between the built-in ICT module and the driver’s mobile phones and driver’s activity information. For example, the Audio Video Navigation (AVN) system, an ICT module, interacts with drivers and provides convenient features to drivers. AVN can be connected to a driver’s mobile device, and it can be used to store various driver-specific real time information such as driving records, phone call records, SMS, and music playback events. In this paper, we collect and analyze the digital data stored in an AVN installed in a KIA K5 sedan. Most of the analyzed data is related to the activities initiated from the mobile device connected to the AVN via Bluetooth. The result of our research reported in this paper can be useful for the forensic data analysis of vehicles.

해양 탄성파탐사 자료취득시스템은 항측시스템, 기록시스템, 스트리머 케이블, 음원 등으로 구성된다. 항측시스템은 계획된 측선에 따라 탐사선을 계산된 위치로 이동시키며, 탐사선과 수중에서 예인되는 탐사장비의위치를 측정 및 계산하는 중요한 역할을 수행한다. 본 기술보고에서는 동해 울릉분지에서 심해 유가스전 탐사기술 개발을 위해 석유물리탐사선 탐해2호로 수행된 항측 자료취득 및 품질관리 등의 과정과 항측 자료취득및 품질관리의 중요성에 대해서 소개하고자 한다.

Marine seismic data acquisition system consists of navigation system, recording system, streamer cable and seismic source. Navigation system performs the important role steering the vessel along the pre-plot survey line and measuring and calculating the position between survey vessel and deployed equipments. To develop the deepwater hydrocarbon exploration technology in the Ulleung Basin, in this technical report, we introduce the processes of navigation data acquisition and quality control conducted by navigation system of R/V Tamhae II and report those importance.

전기자동차는 화석연료 사용으로 인한 대기오염을 줄여 삶의 질을 개선하고, 신규 사업을 창조하여 경제적 발전에 역할을 할 것으로 기대된다. 그러나 이러한 기대와는 달리 전기자동차의 보급은 쉽지 않다. 주요한 이유 가운데 하나는 화석연료를 사용하는 자동차에 비해 충전이 늦거나 불편하다는 것이다. 전기자동차가 보급되지 않은 상황에서 선제적으로 충전소를 확보하는 일은 비용부담과 관리의 어려움을 야기할 수 있어 주의해야 한다. 본 연구는 디자인 과학 연구법을 활용하고 전기자동차 충전소 결정 문제를 정보시스템 관점에서 해석한다. 주행 범위 불안감을 이론적 근거로 삼아 여정 설계 알고리즘을 제안하고 네비게이션 사용자 데이터를 분석함으로써 서울시 충전소의 위치 선정의 문제점을 확인한다. 또한 여정 설계 디자인의 적용 가능성을 검토하고 시사점을 도출한다.

Electric cars are expected to increase quality of life by reducing air pollution and to contribute to economic growth by creating new businesses. However, electric car adoption has lagged and has not satisfied public expectation. One of the primary reasons for this outcome is the slow charging speed or inconvenience of charging a battery. Under the insufficient diffusion of electric cars, pushing business entities to construct charging facilities is undesirable for a policy maker to increase the adoption rate because of cost and management issues. This study adopts the design science methodology to interpret the problem of deploying electric car charging stations in the view of information systems. A trip planning algorithm is suggested on the basis of the theory of range anxiety. We investigate issues related to the current charging locations using data from drivers’ car navigation devices. We also review its applicability to trip planning to obtain insights.

도로상에서 발생하는 교통 혼잡비용은 지역 간 도로 보다는 도심부 내에서 비중 있게 발생하며, 이는 전체 혼 잡비용의 약 63.39%를 차지하고 있다. 따라서, 교통혼잡비용의 절감을 위해서는 도심부의 교통 혼잡을 해소 하는 것이 중요하다. 도심부의 교통 혼잡은 반복정체와 비반복정체로 구분되며, 비반복 정체를 신속하고 정확 하게 검지하는 것이 교통 혼잡의 해소에 있어 무엇보다 중요하다. 그러나 돌발상황 검지에 관한 연구는 대부 분 연속류를 대상으로 수행되어 왔다. 도심부 단속류 도로의 경우, 신호 교차로·주정차 차량 등 다양한 변수가 존재하기 때문에 연속류에 적용되는 돌발상황 검지 알고리즘을 수정없이 적용하기에 무리가 있다. 따라서 본 연구에서는 도심부 단속류 도로를 대상으로 수집된 GPS 기반의 차량궤적 데이터에 인공신경망을 적용하여 돌발상황검지 모형을 구축하였다. 제안된 모형의 정확도 검증 결과, 돌발상황 검지율 46.15%, 오보율 25.00%가 도출되었다. 이러한 결과는 단속 류를 대상으로 하는 초기 연구 결과로서 의미가 있다. 또한 내비게이션 장치와 같은 차량 궤적 데이터만을 활 용하여 비반복정체를 검지 할 수 있는 가능성을 제시 했다는 것에 의미를 찾을 수 있을 것이다.

Traffic congestion cost is more likely to occur in the inner city than interregional road, and it accounts for about 63.39% of the whole. Therefore, it is important to mitigate traffic congestion of the inner city. Traffic congestion in the urban could be divided into Recurrent congestion and Non-recurrent congestion. Quick and accurate detection of Non-recurrent congestion is also important in order to relieve traffic congestion. The existing studies about incident detection have been variously conducted, however it was limited to Uninterrupted Traffic Flow Facilities such as freeway. Moreover study of incident detection on the interrupted Traffic Flow Facilities is still inadequate due to complex geometric structure such as traffic signals and intersections. Therefore, in this study, incident detection model was constructed using by Artificial Neural Network to aim at urban arterial road that is interrupted traffic flow facility. In the result of the reliability assessment, the detection rate were 46.15% and false alarm rate were 25.00%. These results have a meaning as a result of the initial study aimed at interrupted traffic flow. Furthermore, it demonstrates the possibility that Non-recurrent congestion can be detected by using car navigation data such as car navigator system device.

2018년 도입된 「민자고속도로 공공성 강화를 위한 통행료 관리 로드맵」은 '동일 서비스 동일 요금'을 전제로 하고 있으나, 두 운영체계가 실제로 동일한 공간적 서비스를 제공하는지에 대한 실증적 검증은 부족하였다. 본 연구에서는 네비게이션 자료를 활용하여 우리나라 고속도로 46개 노선의 출발·도착 통행을 읍면동 단위로 식별하고, 노선별 OD의 공간분포를 가중 표준거리로 산출하였다. 산출된 WSD를 절대값, 노선 연장으로 정규화한 비율, 노선 연장을 공변량으로 하는 log-log 회귀모형의 세 지표로 두 운영구분 간 차이를 검정하였다. 분석결과, 절대 WSD에서 재정고속도로의 평균(81.3km)이 민자고속도로(54.7km)보다 통계적으로 매우 유의하게 큰 것으로 나타났다(Mann-Whitney U, p<0.001). 그러나 이 차이는 노선 연장으로 단순 정규화한 비율 비교(p=0.572)에서는 사라지는 것으로 확인되었다. 한편 노선 연장의 비선형 효과를 통제한 log-log 회귀모형에서는 노선 길이가 같다고 가정하더라도 민자고속도로의 평균 WSD가 재정고속도로보다 약 25% 좁은 것으로 분석되었다. 이상의 분석결과는 두 운영체계의 절대적 공간 도달범위 차이가 노선 길이 분포 차이로 상당 부분 설명되며, 그 외에 작지만 통계적으로 유의한 운영구분의 잔존 효과도 함께 존재함을 보여 준다. 따라서 통행료·통합운영·공공성 강화 정책의 비교 단위는 운영구분(재정·민자) 그 자체보다 노선 길이와 공간적 역할 유형(집산형·코리더형)을 함께 고려하는 방향으로 정교화될 필요가 있다.

This study quantitatively compares the spatial distribution of trips on Korea's publicly financed expressways and privately operated (BTO) expressways using the Weighted Standard Distance (WSD). The Toll Management Roadmap for Strengthening the Publicness of Privately Operated Expressways, introduced in 2018, is premised on the principle of "same service, same fare," yet empirical verification of whether the two operating systems actually provide the same spatial service has been lacking. Using navigation data, we identified origin–destination trips on 46 expressway routes and computed the WSD of each route's OD distribution. The two operating groups were then compared along three measures: absolute WSD, WSD normalized by route length, and a log-log regression that controls for route length as a covariate. In absolute WSD, publicly financed expressways (mean 81.3 km) are statistically significantly more spatially expansive than their privately operated counterparts. However, this difference essentially disappears when normalized by route length. When the nonlinear effect of route length is controlled in a log-log regression, the private-expressway dummy coefficient remains statistically significant, indicating that private expressways exhibit roughly 25% narrower spatial distributions than public ones even after route length is held constant. Routes were further classified into a "collector/gateway type" and a "corridor type". These findings indicate that the difference in spatial reach between the two operating systems is largely explained by differences in their route-length distributions, with a small but statistically significant residual effect of the operating distinction. Toll, integrated operation, and publicness policies should therefore be refined to consider not only the operating distinction (public vs. private) but also route length and spatial role type (collector vs. corridor).

GNSS 수신기는 자율주행 자동차에 장착되어 항법 장치를 이루는 필수 요소이다. 하지만 의도적인 재밍 신호가 발생하였을 경우, GNSS 수신기 추정 위치 값의 성능 저하로 인해 사고 위험에 노출될 우려가 있다. 이를 방지하기 위한 연구가 필요하며, 그에 따라 재밍 발생 장치가 구비되어야 한다. 그러나 재밍에 관련한 법 조항에 따라 이를 불법으로 규정하고 있다. 본 논문 에서는 법 조항을 준수하고, 주위 GNSS 센서에 영향을 주지 않는 차량 내 재밍 발생 장치를 구현한다. GNSS 알고리즘의 성능 평가를 위해 드라이빙 시뮬레이션을 활용하며, 간섭 환경에 서 발생하는 자율주행 차량의 오작동 및 GNSS 센서에서 출력된 데이터 오차를 분석한다.

A GNSS receiver installed in autonomous vehicles is the most essential device for its navigation. However, if an intentional jamming signal is generated, there is a risk of exposure to an accident risk due to deterioration of the GNSS sensor's performance. Research is required to prevent this, and accordingly, a jamming generating device must be provided. However, according to the provisions of the law related to jamming, this is illegal. In this paper, we implement an in-vehicle jamming device that complies with the provisions of the law and does not affect the surrounding GNSS sensors. Driving simulation is used to evaluate the performance of the GNSS algorithm, and the malfunction of autonomous vehicles occurring in the interference environment and data errors output from the GNSS sensor are analyzed.

Autonomous Navigation Vehicle (AUV) navigates to the specified longitude and latitude on water surface by means of Global Positioning System (GPS), Inertial Navigation System (INS) and Electronic Compass (EC), then dives to the specified depth according to the measurements of Depth Gauge (DG). To overcome the low location accuracy of existing navigation technologies in AUV, an integrated navigation method based on multi-sensor data fusion of GPS/INS/EC/DG has been proposed. Since the systematic stability and high precision in short-term measurement of INS, it takes the INS as common reference system. The problem which measurement error accumulates with time is solved by the combination of four sub-filters and a main filter. The sub-filters output the measured velocity, position, orientation and depth error to the main filter, which fuse the data to obtain the global optimal estimation and feedback to the INS system. Realistic environment parameters are simulated in MATLAB to verify the rationality of the navigation algorithm. The feasibility of method is proved by the comparison of position errors with and without combined navigation.

In this age of information, which is available in different forms and these information play imperative part to enhance our knowledge base and so our social life. Information presentation is as important as information itself because to interpret the inside knowledge and interaction with it makes it more effective. This study investigates legend navigation interactive technique for comparative exploration of descriptive data mining results in order to communicate the insight information quickly, easily and in well understandable form. The legend navigation interactive mechanism is applied to two visualization techniques (column charts and bar charts) by performing descriptive data mining task on published Amazon dataset. The experimentation is done with 41 volunteers, selected by simple random sampling technique. The interactive technique is comprehensively analyzed in both visualization techniques considering visualization features. Equate the results with drill down interactive mechanism and discussed the utility of mechanism based on visualization features. The legend navigation approach and drill down interactive mechanism showed better performance in column chart comparatively.

IVEF is the protocol designed for the exchange of marine transportation information between the vessel traffic control systems and between the vessels. Standardization of the IVEF service is under way as a part of the next-generation marine navigation system called e-Navigation. This paper suggests an IVEF protocol based on the XmlPullParser, which supports faster processing speed and requires less memory than the existing SAX parser. It also suggests a server/client system which simulates the V-145 protocol in the wireless environment. Android-based smart phones were used to emulate the vessels, and Windows 7-based desktops were used to emulate the VTS (Vessel Traffic Service) service center.

In this paper we have considered the problem of outdoor mobile robot navigation using dead reckoning (DR) system and single GPS receiver. DR is a very simple and practical positioning technique. It is used in various positioning and navigation applications, especially for the mobile robot. DR can provide short term precise navigation information. But its errors will generally accumulate as the mobile robot continues to travel, and the calculated position of the mobile robot will become less and less accurate. For outdoor navigation application, GPS exhibit lots of advantages. It can provide real time and relatively accurate position data in spite of bad weather or other negative factors. But the big errors of civilian used single GPS receiver prevent it from applying to navigation for mobile robot alone. Differential GPS (DGPS) can be used to achieve an error of less than one meter but the costs are prohibitive in terms of commercializing it into the mass market. In this study, a cheap single GPS receiver cooperated with a DR system was used for the navigation system of a outdoors mobile robot in which a new GPS/DR data fusion method was utilized. This proposed fusion algorithm was based on the characteristics of the chosen single GPS receiver. The presented fusion algorithm does not bring much calculation burden and can provide accurate and robust navigation information for the mobile robot by adaptively switching between GPS/DR and DR when GPS lost the satellite signals. Simulation and experiment were performed to validate the effectiveness of the proposed fusion method and the good results showed its potential for outdoors mobile robot navigation.

Operational orbit determination (OOD) depends on the capability of generating accurate prediction of spacecraft ephemeris in a short period. The predicted ephemeris is used in the operations such as instrument pointing and orbit maneuvers. In this study the orbit prediction problem consists of the estimating diverse arc length orbit using GPS navigation data, the predicted orbit for the next 48 hours, and the fitted 30-hour arc length orbits of double differenced GPS measurements for the predicted 48-hour period. For 24-hour orbit arc length, the predicted orbit difference from truth orbit was 205 meters due to the along-track error. The main error sources for the orbit prediction of the Low Earth Orbiter (LEO) satellite are solar pressure and atmosphere density.

This paper presents a simple sensor fusion algorithm using neural network for navigation of mobile robots with obstacle avoidance and trap recovery. The multiple sensors input sensor data to the input layer of neural network activating the input nodes. The multiple sensors used include optical encoders, ultrasonic sensors, infrared sensors, a magnetic compass sensor, and GPS sensors. The proposed sensor fusion algorithm is combined with the VFH(Vector Field Histogram) algorithm for obstacle avoidance and AGPM(Adaptive Goal Perturbation Method) which sets adaptive virtual goals to escape trap situations. The experiment results show that the proposed low-level fusion algorithm is effective for real-time navigation of mobile robot.

In this study, an EKF (Extended Kalman Filter) based database reference navigation using both gravity gradient and terrain data was performed to complement the weakness of using only one type of geophysical DB (Database). Furthermore, a new algorithm which combines the EKF and profile matching was developed to improve the stability and accuracy of the positioning. On the basis of simulations, it was found that the overall navigation performance was improved by the combination of geophysical DBs except the two trajectories in which the divergence of TRN (Terrain Referenced Navigation) occurred. To solve the divergence problem, the profile matching algorithm using the terrain data is combined with the EKF. The results show that all trajectories generate the stable performance with positioning error ranges between 14m to 23m although not all trajectories positioning accuracy is improved. The average positioning error from the combined algorithm for all nine trajectories is about 18 m. For further study, a development of a switching geophysical DB or algorithm between the EKF and the profile matching to improve the navigation performance is suggested.

In mobile robotics, ultrasonic sensors became standard devices for collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. The global map building based on multi-sensor data fusion is applied for recognition an obstacle free path from a starting position to a known goal region, and simultaneously build a map of straight line segment geometric primitives based on the application of the Hough transform from the actual and noisy sonar data. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, Hough transform, since there exist several recent thorough books and review paper on this paper. Experimental results with a real Pioneer DX2 mobile robot will demonstrate the effectiveness of the discussed methods.