• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.1 s.4
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• pp.45-52
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• 2004

There are many cities installing ITS(Intelligent Transportation Systems) and running TMC(Trafnc Management Center) to improve mobility and safety of roadway transportation by providing roadway information to drivers. There are many devices in ITS which collect real-time traffic data. We can obtain many valuable traffic data from the devices. But it's impossible to avoid missing traffic data for many reasons such as roadway condition, adversary weather, communication shutdown and problems of the devices itself. We couldn't do any secondary process such as travel time forecasting and other transportation related research due to the missing data. If we use the traffic data to produce AADT and DHV, essential data in roadway planning and design, We might get skewed data that could make big loss. Therefore, He study have explored some imputation techniques such as heuristic methods, regression model, EM algorithm and time-series analysis for the missing traffic volume data using some evaluating indices such as MAPE, RMSE, and Inequality coefficient. We could get the best result from time-series model generating 5.0$\%$, 0.03 and 110 as MAPE, Inequality coefficient and RMSE, respectively. Other techniques produce a little different results, but the results were very encouraging.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.14-28
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• 2018

Thanks to technical improvement on the vehicle to vehicle communication and the intelligent transportation system, gradual introduction of the autonomous vehicles is expected soon in the market. The study analyzes the autonomous vehicles' impacts on the network efficiencies. In order to measure the network efficiencies, the study applies the sequential procedures that combines the microscopic and macroscopic simulations. The microscopic simulation attends to the capacity changes due to the autonomous vehicles' proportions on the roadway while the macroscopic simulation utilizes the simulation results in order to identify the network-wide improvement. As expected, the autonomous vehicles efficiently utilizes the existing capacity of the roadway than the human driving does. Particularly, the maximum capacity improvements are expected by the 190.5% on the expressway. The significant capacity change is observed when the autonomous vehicles' proportions are about 80% or more. These improvements are translated into the macroscopic model, which also yields overall network efficiency improvement by the autonomous vehicles' penetration. However, the study identifies that the market debut of the autonomous vehicles does not promise the free flow condition, which implies the possible needs of the system optimal routing scheme for the era of the autonomous vehicles.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.23-32
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• 2007

Variable message sign (VMS), which is used for providing real-time information on traffic conditions and incidents, is one of the important components of intelligent transportation systems. VMS messages need to meet the requirements with the consideration of human factors that messages should be readable and understandable while driving. This study developed a legibility distance model for VMS messages using in-vehicle differential global positioning data (DGPS). Traffic conditions, highway geometric conditions, and VMS message characteristics were investigated for establishing the legibility model based on multiple linear regression analysis. The height of VMS characters, speed, and the number of lanes were identified as dominant factors affecting the variation of legibility distances. It is expected that the proposed model would play a significant role in designing VMS messages for providing more effective real-time traffic information.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.962-974
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• 2010

Recently, the convergence of information technology with bio-technology, nano-technology or other technologies has been creating a new paradigm. In a field of transportation, the intelligent transport systems which is a convergence of intelligent technologies and transportation systems have been studied. The Variable Speed Limit(VSL), is one of ITS technologies, is thought to improve safety and efficiency of transportation while controlling speed limit based on road conditions. Legacy studies have considered only one station for VSL algorithm. However, it is not appropriate for an urban freeway installed with many stations. In this paper, new algorithm is proposed to not only enhance effectiveness of VSL based on cooperation of stations but also reflect road conditions within 30 seconds. The proposed algorithm consists of 4 steps: the first is a "searching bottleneck station" step, the second is a "calculating a size of congestion" step, the third is a "calculating the number of controlled stations" step, the final is a "calculating VSL" step. This algorithm guarantees improved safety and minimum additional travel time. The travel time should be considered because drivers would against the VSL algorithm when the proposed algorithm occurs additional travel time. In our experiments, microscopic traffic simulator VISSIM is selected to perform a modeling work. The results show that proposed algorithm provides the improved safety and minimum increase of travel time.

• Advanced Industrial SCIence
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• v.3 no.1
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• pp.23-29
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• 2024

In this scholarly investigation, the focus is placed on the transformative potential of edge computing in enhancing Intelligent Transportation Systems (ITS) for the facilitation of autonomous driving. The intrinsic capability of edge computing to process voluminous datasets locally and in a real-time manner is identified as paramount in meeting the exigent requirements of autonomous vehicles, encompassing expedited decision-making processes and the bolstering of safety protocols. This inquiry delves into the synergy between edge computing and extant ITS infrastructures, elucidating the manner in which localized data processing can substantially diminish latency, thereby augmenting the responsiveness of autonomous vehicles. Further, the study scrutinizes the deployment of edge servers, an array of sensors, and Vehicle-to-Everything (V2X) communication technologies, positing these elements as constituents of a robust framework designed to support instantaneous traffic management, collision avoidance mechanisms, and the dynamic optimization of vehicular routes. Moreover, this research addresses the principal challenges encountered in the incorporation of edge computing within ITS, including issues related to security, the integration of data, and the scalability of systems. It proffers insights into viable solutions and delineates directions for future scholarly inquiry.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.327-330
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• 2000

In this paper, we describe an intelligent method to detect types of vehicles using Support Vector Machines focused to the Intelligent Transportation System (ITS) applications such as in the CCD based Electronic Toll Collection System (ETCS). This algorithm can be used the various fields of ITS applications. Support Vector Machines employed in this paper has been recently proposed as a very effective method for 3D image recognition. And our proposed feature extraction method using the singluar values that directly come from pixels at input images. Consequently, The low calculation load and the high recognition rate in spite of image rotation and various noises are one of merits of proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.347-351
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• 1998

Dynamic programming is applicable to any situation where items from several groups must be combined to form an entity, such as a composite investment or a transportation route connecting several districts. The most desirable entity is constructed in stages by forming sub-entities that are candidates for inclusion in the most desirable entity are retained, and all other sub-entities are discarded. In the paper, the fuzzy dynamic programming is applied to the situation where each investment in the set has the following characteristics : the amount to be invested has several possible values, and the rte of return varies with the amount invested. Each sum that may be invested represents a distinct level of investment , and the investment therefore has multiple levels. A numeric example constructing a combination of multilevel investments is given in the paper.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.2
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• pp.96-101
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• 2015

Support vector machine (SVM) has a strong theoretical foundation and also achieved excellent empirical success. It has been widely used in a variety of pattern recognition applications. Unfortunately, SVM also has the drawback that it is sensitive to outliers and its performance is degraded by their presence. In this paper, a new outlier detection method based on genetic algorithm (GA) is proposed for a robust SVM. The proposed method parallels the GA-based feature selection method and removes the outliers that would be considered as support vectors by the previous soft margin SVM. The proposed algorithm is applied to various data sets in the UCI repository to demonstrate its performance.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2095-2107
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• 2000

In maned ship, crews may have risks as they manage damage control system in IPMS in damage situations such as fire in a ship. So the application of unmaned autonomous systms can reduce the number of boarding crews and attribute to safe marine transportation. The paper suggests an intelligent system of the fire fighting control using fuzzy logic in Integrated Platform Management System which can take measures against fire situation of a ship excluding unnecessary warnings with undamaged situations. The system here detected the fire more accurately and adopted more appropriate measures according to ship status compared with conventional systems. Of all, a reduction of false detection of fires was noted.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1157-1162
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• 2013

This thesis describes the active cruise control which is a part of AVHS(Advanced Vehicle and Highway System) in the ITS(Intelligent Transportation Systems). The active cruise control is a system which recognizes some obstructions and vehicles in front, drives in safe speed and puts on the brake in dangerous situations as the driver simply turns on the switch without stepping on the accelerator and brake. PID controller is used in the speed-control by linearizing the longitudinal model of the vehicle, obstacle detecting algorithm which makes use of the laser scanner is proposed to recognize the situation in front and the system's performance is tested.