• Journal of Cadastre & Land InformatiX
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• v.51 no.1
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• pp.53-65
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• 2021

C-ITS(Cooperative Intelligent Transport System) that pursues traffic safety and convenience uses various sensors to generate traffic information. Therefore, it is necessary to improve the sensor-related technology to increase the efficiency and reliability of the traffic information. Recently, the role of CCTV in collecting video information has become more important due to advances in AI(Artificial Intelligence) technology. In this study, we propose to identify and track dynamic objects(vehicles, people, etc.) in CCTV images, and to analyze and provide information about them in various environments. To this end, we conducted identification and tracking of dynamic objects using the Yolov4 and Deepsort algorithms, establishment of real-time multi-user support servers based on Kafka, defining transformation matrices between images and spatial coordinate systems, and map-based dynamic object visualization. In addition, a positional consistency evaluation was performed to confirm its usefulness. Through the proposed scheme, we confirmed that CCTVs can serve as important sensors to provide relevant information by analyzing road conditions in real time in terms of road infrastructure beyond a simple monitoring role.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.526-534
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• 2022

In August 2014, the Ministry of Land, Infrastructure, and Transport (MOLIT) devised an innovative ITS measure in which private and public sectors share roles to maximize investment efficiency and effectiveness in collecting and offering traffic information that had been separately implemented by the state and private sector. The main details of the innovative measure include the following: For communication information, the information collected by the private sector is used, and the state concentrates on safety-related information collection, such as unexpected situations, including construction, accidents, and deteriorating weather conditions. Consequently, safety-related information is offered in real-time through smartphones and navigation, in addition to electric road signs that have limitations in providing unexpected real-time situations due to installation at specific spots. This study presented a connected traffic information priority coordination plan to improve the accuracy of traffic information offering by analyzing problems of related traffic information, including a general national highway case study to enhance the efficiency of national highway ITS implementation, according to actual public-private traffic information sharing. In addition, this study reviewed whether to operate or demolish the information collection equipment by analyzing traffic volume level and availability of related traffic information in the existing ITS operation sections and presented ITS collection equipment installation judgment standards based on the cases concerned.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.483-490
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• 2021

Due to the recent increase in various problems from underground development in urbanized areas, accurate underground facility information management is highly needed. Therefore, in this study, in order to utilize the Integration Map of Underground Goespatial Information in real time on-site, the function of comparing the mutual location of the GPR (Ground Penetration Radar) sensing data and the Integration Map of Underground Goespatial Information, and function of analyze underground facilities, and function of converting surveying data into a shape file through position correction & attribute editing in a 3D space, and the function of submitting the shape file to the Integration Map of Underground Goespatial Information mobile center was defined and developed as a program. In addition, for the on-site application test of the development program, scenarios used at the underground facility real-time survey site and GPR exploration site were derived, and four sites in Seoul were tested to confirm that the use scenario worked properly. Through this, the on-site utilization of the program developed in this study could be confirmed, and it would contribute to the confirmation of the quality of Shape-file and the "update automation" of "Integration Map of Underground Goespatial Information". In addition, it is expected that the development program will be further applied to the Underground Facility Map's Accuracy Improvement Diffusion Project' promoted by the MOLIT (Ministry of Land, Infrastructure, and Transport).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.6
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• pp.1023-1035
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• 2016

Suspended sediment concentration (SSC) is a crucial riverine parameter in terms that it can be utilized for analyzing sediment transport, stability assessment of river and structure and so on. However, in case of domestic, sediment discharge data are not enough because of using conventional sediment samplers. This study aimed at developing a practical technique for estimating suspended sediment concentration in high spatial and temporal resolution by building relationship between acoustic backscatter (or SNR) from H-ADCP with actually observed data using LISST-100X. In this regard, a dedicated correction algorithm was proposed particularly for the adapted H-ADCP (SonTek SL-3000). Then, a SNR-SSC relation was built based upon a real-scale field experiment, where both H-ADCP and LISST-100X were concurrently operated to observe SNR and SSC, respectively. The coefficient of determination for the developed regression equation of SNR-SSC relation was around 0.85~0.88, thereby the relation could be evaluated to be highly correlated. The result of this study might be potentially applied for real-time and simultaneous observation of SSC when H-ADCP could be applied.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.1 s.12
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• pp.13-26
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• 2007

A VDS data in the domestic has been used within limits to real time information such as congestion management, incident management, and route guidance service. On the other hand, a VDS data in the foreign countries had been used to various objectives such as transportation policy assessment, transportation construction evaluation, franc safety improvement, and etc. The scope and method of the study is the VDS data which was installed in the uninterrupted flow such as the freeway and the interrupted flow in a diversion route of the leeway. It has investigated and analyzed the VDS as our subject to study, study objective and study methodology for each study generally classified as 1) data collection 2) data processing 3) data store and 4) data quality section. This study has investigated and analyzed the various literatures in domestic and foreign countries regarding the VDS data. And It drew the development direction of the study which is about VDS data in domestic from now.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.116-127
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• 2017

A fog on road is known as a weather factor that affects traffic flow. The method in order to solve the problem, recently, Variable Speed Limit(VSL) which provide reasonable speed limit by road and weather conditions in real time is introduced. However, if drivers do not comply with VSL, the road safety more decrease than without VSL because individual vehicle's speed deviation is larger than without VSL. Therefore, this paper aims to analyze to speed limit compliance and traffic characteristics under foggy conditions with and without VSL. A test using driving simulator divides into normal and foggy condition with visibilities are 200m, 150, 50~100m. The test results showed that 70 subjects's average speed mostly obeyed speed limit, but speed deviation generally declined with VSL. Especially, the speed deviation more reduced under foggy conditions. According to this study, compliance of VSL clearly rose in low visibility and VSL helped improve road safety due to reduction of speed deviation. The results of this study are expected to make use of reasonable speed limit for reference.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.6
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• pp.22-32
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• 2010

Increasingly advanced Information Technology (IT) has changed the operator so as to create more diversified and advanced traffic information demand. To deal with the changing demand in private sector, a concept of on-demand traffic information has been rapidly introduced. However VMS, a product of the first generation of ITS, which was designed to provide the unspecified individuals during driving the car with the basic level of traffic information by the public failed to actively change itself in such a changing pattern. This study was intended to describe the VMS system (tentatively, FM-VMS) which was further developed to accommodate the needs favoring the sophisticated PDA with the public role of providing the unspecified individuals with the equal information. FM-VMS introduced in this study is the device designed to transmit the voice and message to the drivers through the radio information device mounted on a car. A core technology is, unlike FM-DARC and RDS, the Water Making technology which directly inserts the digital signal into FM frequency in use. It's been currently used for broadcasting and security purpose. A detection rate as a result of testing FM-VMS system using Water Making technology was 90% or more in voice and message within 20m from test VMS. When a public-developed VMS information could be transmitted using FM frequency to the relatively vulnerable users (vulnerable to traffic information) in voice on a real-time basis to provide the regional traffic information, and furthermore, VMS message could be received through radio liquid using FM frequency only, it would obviously bring about the innovation in ITS as well as pave the way for creating the new added value down the road.

• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.119-130
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• 2003

SP data have been widely used in assessing new transport policies and transport related plans. However, one of criticisms of using SP is that respondents may show different reaction between hypothetical experiments and real life. In order to overcome the problem, combination of SP and RP data has been suggested and the combined methods have been being developed. The purpose of this paper is to suggest a new SP and RP combined method using error component method and to verify the method. The error component method decomposes IID extreme value error into non-IID error component(s) and an IID error component. The method estimates both of component parameters and utility parameters in order to obtain relative variance of SP data and RP data. The artificial SP and RP data was created by using simulation and used for the analysis, and the estimation results of the error component method were compared with those of existing SP and RP combined methods. The results show that regardless of data size, the parameters of the error component method models are similar to those assumed parameters much more than those of the existing SP and RP combined models, indicating usefulness of the error component method. Also the values of time for error component method are more similar to those assumed values than those of the existing combined models. Therefore, we can conclude that the error component method is useful in combining SP and RP data and more efficient than the existing methods.

• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.458-467
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• 2017

The expressway of the Korea has an important role in freight movement because 76 percent of the commodity is transported by trucks. However, there has been few indices on the role of expressways regarding freight transportation and truck traffic. The objective of this study is to propose four freight transportation related indices using ITS-related system such as TCS and HS-Wim: total truck's travel miles ($veh{\cdot}km/year$), total freight transport miles ($ton{\cdot}km/year$). efficiency of truck's travel ($veh{\cdot}km/km$), and efficiency of freight movement ($ton{\cdot}km/km$). These truck and freight related indices were estimated and compared by two different data sources: traffic volume data using VDS and OD data using TCS. These indices were designed to estimated on real time and updated every day and month.