• Journal of KIISE
• /
• v.43 no.12
• /
• pp.1351-1355
• /
• 2016

The number of CCTV units is rapidly increasing annually, and the demand for intelligent video-analytics system is also increasing continuously for the effective monitoring of them. The existing analytics engines, however, require considerable computing resources and cannot provide a sufficient detection accuracy. For this paper, a light analytics engine was employed to analyze video and we collected metadata, such as an object's location and size, and the dwell time from the engine. A further data analysis was then performed to filter out the target of interest; as a result, it was possible to verify that a light engine and the heavy data analytics of the metadata from that engine can reject an enormous amount of environmental noise to extract the target of interest effectively. The result of this research is expected to contribute to the development of active intelligent-monitoring systems for the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.6
• /
• pp.1-12
• /
• 2009

Recently, as the importance of Economical Driving has been gradually growing up, the needs for research on automatic analysis of driving patterns that will ultimately provide drivers the methods for Economical Driving have been increasingly risen. Based on this purpose, we have executed two things in this paper. First, we have collected overall driving information such as date, distance, driving time, speed, idle time, sudden acceleration/deceleration count, and the amount of fuel consumption. Second, we have analyzed the influences of driving patterns on economical driving by employing the data mining techniques. These results can be applied in preventing bad driving patterns which will have consequently bad effects on Economical Driving in two aspects: by presenting some information on the terminal of the vehicles such as idle time, over-speed time, sudden acceleration/deceleration count continuously and by providing the drivers with alert information when the idle time ratio and the over-speed time ratio are excessive.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.9 no.3
• /
• pp.30-40
• /
• 2010

The freeway congestion is largely generated by a mainline spillover of the exit ramp queue. So it is necessary to study for modeling of the phenomenon and applying the model. In this study, the authors evaluated applicability of the Supply-Demand model, which can express traffic flow for the freeway by applying flexibly supply and demand curves for capacity of the freeway. First the authors proposed methods processing input data required in the Supply-Demand model, such as sending & receiving functions and time-varying capacity constraints for the freeway mainline. After modeling the Supply-Demand application model, the authors applied the model to the site including congested Hongeun exit ramp in Seoul Ring-road, and improved the model by adjusting application techniques and calibrating parameters. The result of the analysis showed that the Supply-Demand model yielded a queuing pattern and queue location similar to them observed in the field data, and applicability of the Supply-Demand model was varified.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.4
• /
• pp.13-29
• /
• 2020

Automobiles have long been an essential part of daily life, but the social costs of car traffic accidents exceed 9% of the national budget of Korea. Hence, it is necessary to establish prevention and response system for car traffic accidents. In order to present a model that can classify and predict the degree of injury in car traffic accidents, we used big data analysis techniques of K-nearest neighbor, logistic regression analysis, naive bayes classifier, decision tree, and ensemble algorithm. The performances of the models were analyzed by using the data on the nationwide traffic accidents over the past three years. In particular, considering the difference in the number of data among the respective injury severity levels, we used down-sampling methods for the group with a large number of samples to enhance the accuracy of the classification of the models and then verified the statistical significance of the models using ANOVA.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.12 no.5
• /
• pp.22-35
• /
• 2013

With the increase in image detectors, concerns about the reliability of traffic information are increasing. In this paper, we propose a method to generate reliable traffic volume using analysis of the point detector data as a representative value. Therefore, targeting expressway, we analyzed the difference in traffic volume collected by loop and image detector, and verified statistically using t-test, and finally analyzed the error rate compare to the real traffic volume. Analysis revealed that there was a statistically difference the traffic date collected by the loop detector and the image detector, in the same period, the same time, respectively. In addition, the difference between the actual traffic volume and traffic that have been collected in a loop detector was the lowest Therefore, creating a traffic volume of representative value, we proposed a method to use loop detector than the average traffic volume collected by each detector. It shows that it is more important to use one high-quality data rather than various low-quality data to produce a representative value.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.6
• /
• pp.607-614
• /
• 2015

In this paper, structural analysis for the 16 core competencies of aircraft maintenance crew using FSM is carried out for the purpose of improving the capability of aircraft maintenance. As a result, the three groups of layers are composed of the 3 top layers, 3 middle layers and 10 lowest layers. These results make it possible to grasp the impact and importance. In addition, the core competency of aircraft maintenance crew can improve the maintenance quality and productivity through working on the spot. In this viewpoint, fuzzy relational matrix, which is used as a basis for evaluating the work, can be obtained from the data of the 100 aircraft maintenance crew for core competencies. In this paper, the efficiency of this model is shown by utilizing the 100 modeling data and the 67 checking data.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.1
• /
• pp.160-173
• /
• 2021

Recently, research on the development of autonomous vehicles has increased worldwide. Moreover, a means to identify and analyze the characteristics of traffic accidents of autonomous vehicles is needed. Accordingly, traffic accident data of autonomous vehicles are being collected in California, USA. This research examined the characteristics of traffic accidents of autonomous vehicles. Primarily, traffic accident data for autonomous vehicles were analyzed, and the text data used text-embedding techniques to derive major keywords and four topics. The methodology of this study is expected to be used in the analysis of traffic accidents in autonomous vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.5
• /
• pp.133-148
• /
• 2022

In this study, a road pavement crack deterioration model was developed for a pavement road sections of the Sejong-city. Data required for model development were acquired using a deep learning-based road asset monitoring system. Road pavement monitoring was conducted on the same sections in 2021 and 2022. The developed model was analyzed by dividing it into a method for estimating the annual average amount of deterioration and a method based on Bayesian Markov Mixture Hazard model. As a result of the analysis, it was found that an analysis results similar to the crack deterioration model developed based on the data acquired from the Automatic pavement investigation equipmen was derived. The results of this study are expected to be used as basic data by local governments to establish road management plans.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.2
• /
• pp.147-163
• /
• 2023

Recently, there has been an increase in the research and development of automated vehicles worldwide. Research focused on automated vehicles in Korea is steadily progressing as a national R&D project. Since automated driving technology comprises diverse technology fields, it is necessary to identify the current position of the research. In this study, we propose a methodology for analyzing research trends using the NTIS data. In addition, we review the effectiveness of the currently developed research trend methodology by deriving primary keywords and major topics using the proposed method. We expect that the methodology developed in this study can be applied to identify and analyze future automated vehicle research trends.

• Journal of Korean Society for Geospatial Information Science
• /
• v.21 no.4
• /
• pp.125-134
• /
• 2013

Since 2012, the local autonomous governments, under the recommendations regarding cancellation of local committees directing overly-unexecuted urban planning facilities, have tried to prove validity of such facilities. Factors such as specific standards of cancelation process, will execute policies, diversification of local conditions, connectivity to nearby facilities and possible arise of civil complaints, however, all hinder overly-unexecuted urban planning facilities from getting revitalized. Considering that these unexecuted facilities that local governments have to manage increase in number every year, the burden continuously increases for the governments due to the difficulty of setting aside budget for performing validity checks on such facilities. This research aims to analyze the criteria regarding efficient and systematic method on confirming validity of overly-unexecuted urban planning facilities, to establish into several different processes according to defined categories, and to objectify and quantify such standards. Also, using intelligent spatial information such as digital map, LiDAR data and ortho-images, spatial information analysis method suitable for reassessment was chosen and applied to execute validity analysis regarding overly-unexecuted urban planning facilities.