• Journal of Korean Society of Transportation
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• v.34 no.3
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• pp.278-290
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• 2016

Maximum traffic flow rate is an important performance measure of operational status in transport networks, and has been considered as a key parameter for transportation operation since a bottleneck in congestion decreases maximum traffic flow rate. Although previous studies for traffic flow analysis have been widely conducted, a detection method for changes in dynamic traffic flow has been still veiled. This paper explores the dynamic traffic flow detection that can be utilized for various traffic operational strategies. Turning point analysis (TPA), as a statistical method, is applied to detect the changes in traffic flow rate. In TPA, Bayesian approach is employed and vehicle arrival is assumed to follow Poisson distribution. To examine the performance of the TPA method, traffic flow data from Jayuro urban expressway were obtained and applied. We propose a novel methodology to detect turning points of dynamic traffic flow in real time using TPA. The results showed that the turning points identified in real-time detected the changes in traffic flow rate. We expect that the proposed methodology has wide application in traffic operation systems such as ramp-metering and variable lane control.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.179-186
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• 2008

It is crucial in traffic flow management to maintain productivity and the traffic stability at the same time especially under congested traffic conditions. This issue has not been explicitly addressed under the intelligent transportation system environments. However, the ubiquitous transportation system environments make it possible to collect the data for each vehicle's position and velocity and to perform more sophisticated traffic flow management at individual vehicle or platoon level through V2V and V2I communications. In this paper, a preventive traffic flow management scheme is proposed, in which the objective is to maintain traffic flow stability while the productivity of the system is not decreased. The management scheme is proposed based on Greenshield's model because it is simple and easy to handle. It is considered that further research should be performed to evaluate the various traffic flow models.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.2031-2042
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• 2017

In this paper, a novel traffic flow control method based-on ramp metering and speed regulation using an adaptive sliding mode control (ASMC) method along with a deadzoned parameter adaptation law is proposed at a stochastic macroscopic level traffic environment, where the influence of the density and speed disturbances is accounted for in the traffic dynamic equations. The goal of this paper is to design a local traffic flow controller using both ramp metering and speed regulation based on ASMC, in order to achieve the desired density and speed for the maintenance of the maximum mainline throughput against disturbances in practice. The proposed method is advantageous in that it can improve the traffic flow performance compared to the traditional methods using only ramp metering, even in the presence of ramp storage limitation and disturbances. Moreover, a prior knowledge of disturbance magnitude is not required in the process of designing the controller unlike the conventional sliding mode controller. A stability analysis is presented to show that the traffic system under the proposed traffic flow control method is guaranteed to be uniformly bounded and its ultimate bound can be adjusted to be sufficiently small in terms of deadzone. The validity of the proposed method is demonstrated under different traffic situations (i.e., different initial traffic status), in the sense that the proposed control method is capable of stabilizing traffic flow better than the previously well-known Asservissement Lineaire d'Entree Autoroutiere (ALINEA) strategy and also feedback linearization control (FLC) method.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.818-825
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• 2016

Network management and anomaly detection are challenges in high-speed networks due to the high volume of packets that has to be analysed. Flow-based analysis is a scalable method which reduces the high volume of network traffic by dividing it into flows. As sampling methods are extensively used in flow generators such as NetFlow, the impact of sampling on the performance of flow-based analysis needs to be investigated. Monitoring using sampled traffic is a well-studied research area, however, the impact of sampling on flow-based anomaly detection is a poorly researched area. This paper investigates flow sampling methods and shows that these methods have negative impact on flow-based anomaly detection. Therefore, we propose an efficient probabilistic flow sampling method that can preserve flow traffic distribution. The proposed sampling method takes into account two flow features: Destination IP address and octet. The destination IP addresses are sampled based on the number of received bytes. Our method provides efficient sampled traffic which has the required traffic features for both flow-based anomaly detection and monitoring. The proposed sampling method is evaluated using a number of generated flow-based datasets. The results show improvement in preserved malicious flows.

• Journal of Internet Computing and Services
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• v.6 no.6
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• pp.85-97
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• 2005

In this paper, we construct the traffic information database by using the acquired data from the traffic information devices installed in road network, and, by referring to this database, propose the intersection simulation system which can dynamically manage the real-time traffic flow for each section of road from the intersections, This system consists of hierarchical 3 parts, The lower layer is the physical layer where the traffic information is acquired on an actual road. The traffic flow control framework exists in the middle layer. The framework supports the grouping of intersection, the collection of real-time traffic flow information, and the remote monitoring and control by using the traffic information of the lower layer, This layer is designed by extending the distributed object group framework we developed. In upper layer, the intersection simulator applications controlling the traffic flow by grouping the intersections exist. The components of the intersection application in our system are composed of the implementing objects based on the Time-triggered Message-triggered Object(TMO) scheme, The intersection simulation system considers the each intersection on road as an application group, and can apply the control models of dynamic traffic flow by the road's status. At this time, we use the real-time traffic information collected through inter-communication among intersections. For constructing this system, we defined the system architecture and the interaction of components on the traffic flow control framework which supports the TMO scheme and the TMO Support Middleware(TMOSM), and designed the application simulator and the user interface to the monitoring and the controlling of traffic flow.

• Journal of Korean Port Research
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• v.14 no.4
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• pp.419-427
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• 2000

Today travel demand continues to increase with spread of economic zones. Also, urban freeway plays an important role in intra-zone transportations as a major corridor in a big city. However, most of urban freeways experience a severe congestion with the excess of inflowing or outflowing traffic through freeway ramps. The purpose of this study is to identify the traffic characteristics, analyze the relationships between the traffic characteristics and finally construct the speed predictive models on the ramp junctions of urban freeway under the intelligent transportation system(ITS) settings. From the analyses of traffic characteristics following results were obtained: ⅰ) 24 hours average traffic characteristics flow, occupancy, speed under the ITS settings showed about 40%, 38%, 8.8% increase each on urban freeway junctions period when compared with that under the non-ITS settings each other. Free flow speed and traffic flow on the mainline sections of urban freeway under the ITS settings also showed about 20% and 17% increase when compared with that under the non-ITS, respectively. ⅱ) The upstream when compared speed( $S_{u}$)and downstream occupancy( $O_{d}$) were especially shown to have higher explanatory powers on the stable flow ramp junctions, but the upstream speed( $S_{u}$) and downstream flow( $V_{d}$) were especially shown on the unstable flow ramp junctions of urban freeway under the ITS settings.ngs.ngs.

• Wind and Structures
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• v.30 no.4
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• pp.325-338
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• 2020

In this paper, the improvement of the anti-snow performance of a high-speed train (HST) is studied using the unsteady Reynolds-Averaged Navier-Stokes simulations (URANS) coupled with the Discrete Phase Model (DPM). The influences of the proposed flow control scheme on the velocity distribution of the airflow and snow particles, snow concentration level and accumulated mass in the bogie cavities are analyzed. The results show that the front anti-snow structures can effectively deflect downward the airflow and snow particles at the entrance of the cavities and alleviate the strong impact on the bogie bottom, thereby decrease the local accumulated snow. The rotational rear plates with the deflecting angle of 45° are found to present well deflecting effect on the particles' trajectories and force more snow to flow out of the cavities, and thus significantly reduce the accretion distribution on the bogie top. Furthermore, running speeds of HST are shown to have a great effect on the snow-resistance capability of the flow control scheme. The proposed flow control scheme achieves more snow reduction for HST at higher train's running speed in the cold regions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.92-106
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• 2017

The adverse weather is known as a factor that interrupts traffic flow and causes traffic accidents and traffic congestion by lowering visibility of drivers. Especially, in case of fog unlike any other weather conditions, traffic accidents lead to serious accidents and the fatality of the accidents is known to be high. This paper aims to analyze uninterrupted traffic flow characteristics under foggy conditions among adverse weathers. The traffic volumes and speeds under foggy and normal conditions were analyzed. Results indicated that fog with low visibility causes the most insignificant reduction in traffic volumes. On the other hand, the reduction in the speeds due to low visibility was evident. In addition, the relationship between flow, speed, and density in fog were analyzed. Analysis results showed that the fog with less than 200m visibility had clear impact on traffic flow.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.171-176
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• 2007

To give a guarantee a consistently high level of quality and reliability of Telematics traffic service, traffic flow forecasting is very important issue. In this paper, we proposed an adaptable integrated prediction model to predict the traffic flow in the future. Our model combines two methods, short-term prediction model and long-term prediction model with different combining coefficients to reflect current traffic condition. Short-term model uses the Kalman filtering technique to predict the future traffic conditions. And long-term model processes accumulated speed patterns which means the analysis results for all past speeds of each road by classifying the same day and the same time interval. Combining two models makes it possible to predict future traffic flow with higher accuracy over a longer time range. Many experiments showed our algorithm gives a better precise prediction than only an accumulated speed pattern that is used commonly. The result can be applied to the car navigation to support a dynamic shortest path. In addition, it can give users the travel information to avoid the traffic congestion areas.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1359-1363
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• 2009

The object of this research is to develop a simulation system for earthmoving operations in consideration of the impact of congestion in-between equipment and existing traffic flow around the site. The congestion in-between equipment and traffic flow affect work productivity. The conventional discrete event simulation, however, has limitations in simulating the flow of construction equipment. To consider the impact of congestion in-between equipment and existing traffic flow, in this paper, a multi-agent based simulation model that can realize characteristics of truck behavior more accurately to consider the impact of congestion was proposed. In this simulation model, multiple agents can identify environmental changes and adapt themselves to the new environment. This modeling approach is a better choice for this problem since it describes behavioral characteristics of each agent by sensing changes in dynamic surroundings. This study suggests a detailed system design of the multi-agent based simulation system.