• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.216-238
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• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.45-67
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• 2017

According to the Internet Usage Research performed in 2016, the number of internet users and the internet usage have been increasing. Smartphone, compared to the computer, is taking a more dominant role as an internet access device. As the number of smart devices have been increasing, some views that the demand on high-speed internet will decrease; however, Despite the increase in smart devices, the high-speed Internet market is expected to slightly increase for a while due to the speedup of Giga Internet and the growth of the IoT market. As the broadband Internet market saturates, telecom operators are over-competing to win new customers, but if they know the cause of customer exit, it is expected to reduce marketing costs by more effective marketing. In this study, we analyzed the relationship between the cancellation rates of telecommunication products and the factors affecting them by combining the data of 3 cities, Anyang, Gunpo, and Uiwang owned by a telecommunication company with the regional data from KOSIS(Korean Statistical Information Service). Especially, we focused on the assumption that the neighboring areas affect the distribution of the cancellation rates by coupling type, so we conducted spatial cluster analysis on the 3 types of cancellation rates of each region using the spatial analysis tool, SatScan, and analyzed the various relationships between the cancellation rates and the regional data. In the analysis phase, we first summarized the characteristics of the clusters derived by combining spatial information and the cancellation data. Next, based on the results of the cluster analysis, Variance analysis, Correlation analysis, and regression analysis were used to analyze the relationship between the cancellation rates data and regional data. Based on the results of analysis, we proposed appropriate marketing methods according to the region. Unlike previous studies on regional characteristics analysis, In this study has academic differentiation in that it performs clustering based on spatial information so that the regions with similar cancellation types on adjacent regions. In addition, there have been few studies considering the regional characteristics in the previous study on the determinants of subscription to high-speed Internet services, In this study, we tried to analyze the relationship between the clusters and the regional characteristics data, assuming that there are different factors depending on the region. In this study, we tried to get more efficient marketing method considering the characteristics of each region in the new subscription and customer management in high-speed internet. As a result of analysis of variance, it was confirmed that there were significant differences in regional characteristics among the clusters, Correlation analysis shows that there is a stronger correlation the clusters than all region. and Regression analysis was used to analyze the relationship between the cancellation rate and the regional characteristics. As a result, we found that there is a difference in the cancellation rate depending on the regional characteristics, and it is possible to target differentiated marketing each region. As the biggest limitation of this study and it was difficult to obtain enough data to carry out the analyze. In particular, it is difficult to find the variables that represent the regional characteristics in the Dong unit. In other words, most of the data was disclosed to the city rather than the Dong unit, so it was limited to analyze it in detail. The data such as income, card usage information and telecommunications company policies or characteristics that could affect its cause are not available at that time. The most urgent part for a more sophisticated analysis is to obtain the Dong unit data for the regional characteristics. Direction of the next studies be target marketing based on the results. It is also meaningful to analyze the effect of marketing by comparing and analyzing the difference of results before and after target marketing. It is also effective to use clusters based on new subscription data as well as cancellation data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.117-127
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• 2018

The author tried to propose the orthographic and DTM (digital terrain model) creation and evaluate the accuracy for an university campus using UAV (unmanned aerial vehicle) system. Most previous studies used GPS-based data, but in this paper, the observations of triangulation level measurements was used for comparison of accuracy. Accuracy analysis results showed that the operational requirements for aerial photographic standards are satisfied in all scenaries. The author confirmed availability in aviation photo measurements and applications using UAV (Drone). In order to create a sophisticated DTM and contour, we need to eliminate interference from building, trees, and artificial objects. The results of this study are expected to be used as the basis for future studies in the creation of DTM and the accuracy assessments using Drone.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.451-456
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• 2009

In this paper, a virtual force is generated and fed back to the operator to make the teleoperation more reliable, which reflects the relationship between a slave robot and an uncertain remote environment as a form of an impedance. In general, for the teleoperation, the teleoperated mobile robot takes pictures of the remote environment and sends the visual information back to the operator over the Internet. Because of the limitations of communication bandwidth and narrow view-angles of camera, it is not possible to watch certain regions, for examples, the shadow and curved areas. To overcome this problem, a virtual force is generated according to both the distance between the obstacle and the robot and the approaching velocity of the obstacle w.r.t the collision vector based on the ultrasonic sensor data. This virtual force is transferred back to the master (two degrees of freedom joystick) over the Internet to enable a human operator to estimate the position of obstacle at the remote site. By holding this master, in spite of limited visual information, the operator can feel the spatial sense against the remote environment. It is demonstrated by experiments that this collision vector based haptic reflection improves the performance of teleoperated mobile robot significantly.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.597-602
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• 2014

We propose hybrid-sensing system for human tracking. This system uses laser scanners and image sensors and is applicable to wide and crowded area such as hallway of university. Concretely, human tracking using laser scanners is at base and image sensors are used for human identification when laser scanners lose persons by occlusion, entering room or going up stairs. We developed the method of human identification for this system. Our method is following: 1. Best-shot images (human images which show human feature clearly) are obtained by the help of human position and direction data obtained by laser scanners. 2. Human identification is conducted by calculating the correlation between the color histograms of best-shot images. It becomes possible to conduct human identification even in crowded scenes by estimating best-shot images. In the experiment in the station, some effectiveness of this method became clear.

• Journal of Korea Spatial Information System Society
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• v.1 no.1 s.1
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• pp.57-67
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• 1999

Two GIS and/or OGIS issues for ITS interoperability have been proposed and reviewed with some implications to Korean setting. They are location referencing and ITS map datum. The former must support ITS communication and data sharing. Therefore, an introduction of location referencing and other related issues have been addressed along with the Oak Ridge National Lab.'s (ORNL) location referencing scheme. The latter, proposed by ORNL, is a planned network of anchor points across the nation, that could potentially serve as a positional reference for ITS application (Gottsegen, 1997). It is composed of a set of nodes and links in a standard non-plannar network at a coarse scale for the entire nation for referencing purposes. To provide case of real time traffic information and to guarantee the seamless interoperability, we do need to develop the core ITS map datum as a national infrastructure, and the location referencing scheme should also be either developed or borrowed and localized to meet the domestic needs. Some institutional issues are also addressed along with the future research agenda.

• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.31-43
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• 2008

Travel time prediction is an indispensable to many advanced traveler information systems(ATIS) and intelligent transportation systems(ITS). In this paper we propose a method to predict travel time using $Na{\ddot{i}}ve$ Bayesian classification method which has exhibited high accuracy and processing speed when applied to classily large amounts of data. Our proposed prediction algorithm is also scalable to road networks with arbitrary travel routes. For a given route, we consider time-varying average segment velocity to perform more accuracy of travel time prediction. We compare the proposed method with the existing prediction algorithms like link-based prediction algorithm [1] and Micro T* algorithm [2]. It is shown from the performance comparison that the proposed predictor can reduce MARE (mean absolute relative error) significantly, compared with the existing predictors.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.63-70
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• 2009

3D GIS(Geographic Information System) processes, analyzes and presents various real-world 3D phenomena by building 3D spatial information of real-world terrain, facilities, etc., and working with visualization technique such as VR(Virtual Reality). It can be applied to such areas as urban management system, traffic information system, environment management system, disaster management system, ocean management system, etc,. In this paper, we propose video visualization technology based on 3D geographic information to provide effectively real-time information in 3D geographic information system and also present methods for establishing 3D building information data. The proposed video visualization system can provide real-time video information based on 3D geographic information by projecting real-time video stream from network video camera onto 3D geographic objects and applying texture-mapping of video frames onto terrain, facilities, etc.. In this paper, we developed sem i-automatic DBM(Digital Building Model) building technique using both aerial im age and LiDAR data for 3D Projective Texture Mapping. 3D geographic information system currently provide static visualization information and the proposed method can replace previous static visualization information with real video information. The proposed method can be used in location-based decision-making system by providing real-time visualization information, and moreover, it can be used to provide intelligent context-aware service based on geographic information.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.163-179
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• 2020

With the expansion of platform-based taxi service, mobility and convenience of users are getting better. However, due to profitability problem, marginalized areas in the supply of the service are expected to appear. As such, this study analyzed spatial marginalization of taxi service caused by imbalance in supply and demand during the night-time when public transportation service is suspended. According to hot-spot analysis of taxi, outskirt of a city and residential areas showed high vacancy and greater number of drop-offs compared to the number of pick-ups. On the contrary, they were confirmed low in the center and sub-centers of a city. Centrality analysis also showed a similar pattern with hot-spot analysis. Due to this, drivers may refuse to pick up a customer bound for an area with lower out-degree centrality compared to in-degree centrality as it might be difficult for the drivers to pick up another customer after dropping off the current customer. Thus, customers may need to wait for a taxi for a longer time. For this reason, improvement in spatial marginalization caused by mismatch of supply and demand is required. Also, the outcome of this study is expected to be utilized as a basic data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.208-221
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• 2020

The objective of this study is to estimate and analyze the traffic density of continuous flow using the trajectory of individual vehicles and the headway of sample probe vehicles-front vehicles obtained from ADAS (Advanced Driver Assitance System) installed in sample probe vehicles. In the past, traffic density of continuous traffic flow was mainly estimated by processing data such as traffic volume, speed, and share collected from Vehicle Detection System, or by counting the number of vehicles directly using video information such as CCTV. This method showed the limitation of spatial limitations in estimating traffic density, and low reliability of estimation in the event of traffic congestion. To overcome the limitations of prior research, In this study, individual vehicle trajectory data and vehicle headway information collected from ADAS are used to detect the space on the road and to estimate the spatiotemporal traffic density using the Generalized Density formula. As a result, an analysis of the accuracy of the traffic density estimates according to the sampling rate of ADAS vehicles showed that the expected sampling rate of 30% was approximately 90% consistent with the actual traffic density. This study contribute to efficient traffic operation management by estimating reliable traffic density in road situations where ADAS and autonomous vehicles are mixed.