• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.3
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• pp.63-80
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• 2007

This study is a generalization of 'stable dynamics' recently suggested by Nesterov and de Palma[29]. Stable dynamics is a new model which describes and provides a stable state of congestion in urban transportation networks. In comparison with user equilibrium model that is common in analyzing transportation networks, stable dynamics requires few parameters and is coincident with intuitions and observations on the congestion. Therefore it is expected to be an useful analysis tool for transportation planners. An equilibrium in stable dynamics needs only maximum flow in each arc and Wardrop[33] Principle. In this study, we generalize the stable dynamics into the model with multiple traffic classes. We classify the traffic into the types of vehicle such as cars, buses and trucks. Driving behaviors classified by age, sex and income-level can also be classes. We develop an equilibrium with multiple traffic classes. We can find the equilibrium by solving the well-known network problem, multicommodity minimum cost network flow problem.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.110-123
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• 2019

Traffic data is the most basic element necessary for transportation planning and traffic system operation. Recently, a method of estimating traffic flow characteristics using distance to a leading vehicle measured by an ADAS camera has been attempted. This study investigated the feasibility of the ADAS vehicle reflecting the distance error of image-based vehicle identification technology as a means to estimate the traffic flow through the normalized root mean square error (NRMSE) based on the number of lanes, traffic demand, penetration rate of probe vehicle, and time-space estimation area by employing the microscopic simulation model, VISSIM. As a result, the estimate of low density traffic flow (i.e., LOS A, LOS B) is unreliable due to the limitation of the maximum identification distance of ADAS camera. Although the reliability of the estimates can be improved if multiple lanes, high traffic demands, and high penetration rates are implemented, artificially raising the penetration rates is unrealistic. Their reliability can be improved by extending the time dimension of the estimation area as well, but the most influential one is the driving behavior of the ADAS vehicle. In conclusion, although it is not possible to accurately estimate the traffic flow with the ADAS camera, its applicability will be expanded by improving its performance and functions.

• Journal of Korean Society of Transportation
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• v.17 no.2
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• pp.149-162
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• 1999

One of the most important steps of the design, capacity and operation analysis stapes in the two-lane two way highways is the effect of heavy vehicle to traffic flow quality. This heavy vehicle's effect on traffic flow can be represented as PCE, which is the number of passenger cars that are displaced by a single heavy vehicle of a particular type under prevailing roadway, traffic, and control conditions. In this paper, we focus on the heavy vehicles effect on volume, speed, delay, and the maneuver of freedom which are major MOE's in traffic operation analysis and PCE criterion which should be measurable, determinable and able to reflect the traffic flow characteristics. Therefore, the objective of the paper is to determine the PCE criterion and to develop a new PCE determination method. In this study, delay is adopted as PCE criterion and, for calculation of delay, the highway is divided into the passing zone and the no-passing zone. PCE is determined by comparing the delay due to total traffic flow interaction with the delay due to a single heavy vehicle, Also, this paper proposes a new method to determine the average PCE on the highway that has the passing zones and no-passing zones.

• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.117-134
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• 2004

Truck traffic accounts for a substantial fraction of the traffic stream in many regions and is often the source of localized traffic congestion, potential parking and safety problems. Truck trips tend to be ignored or treated superficially in travel demand models. It reduces the effectiveness and accuracy of travel demand forecasting and may result in misguided transportation policy and project decisions. This paper presents the development of speed-flow relationships with truck impacts based on CORSIM simulation results in order to enhance travel demand model by incorporating truck trips. The traditional BPR(Bureau of Public Road) function representing the speed-flow relationships for roadway facilities is modified to specifically include the impacts of truck traffics. A number of new speed-flow functions have been developed based on CORSIM simulation results for freeways and urban arterials.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.9 no.1
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• pp.1-10
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• 1989

The stress history of a bridge is different depending on the characteristic of traffic flow. Because the flow is varied with vehicle type, weight and headway time etc., statistical analysis in bridges is necessary to estimate the history by traffic flow. By applying the statistical analyses in fracture mechanics, the remaining service life of the structure can be estimated. In this paper, 1)the statistical analysis of vehicle type, weight and headway time etc. to analysis randomness of traffic flow, 2)measuring and analysis of stress history of a real bridge, 3)reappearance of stress history by Monte-Carlo Simulation using constitution ratio of vehicle type, weight and headway time as probabilitic variable, 4)comparision of the calculated and modelled stress history, 5)calculation of reduction factor, 6)comparision of frequency of stress range depending on span length etc. were performed. From the results, the basic modelled stress history which is necessary for the method of estimation of the remaining service life of the structure could be suggested.

• International Journal of Highway Engineering
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• v.14 no.2
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• pp.109-116
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• 2012

This study is aiming to separate highway entrance ramps from impact zones which are considered the characteristics and real traffic situations in each lane and section. The results of this study can be applied to Lane Control System and control the traffic flow for highway more efficiently. Based on earlier studies which analyzed impact zones in entrance-ramp junction using the standard deviation of speed, this study divides more segmentalized impact zones according to the degree of turbulences. As a result of this study, about 800m of intervals, from 500m of upper flow (1,2,3 lane) to 300m of lower flow(2, 3 lane), shows similar traffic characteristics influenced by entrance ramp directly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3230-3253
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• 2017

Android malware steals users' private information, and embedded unsafe advertisement (ad) libraries, which execute unsafe code causing damage to users. The majority of such traffic is HTTP and is mixed with other normal traffic, which makes the detection of malware and unsafe ad libraries a challenging problem. To address this problem, this work describes a novel HTTP traffic flow mining approach to detect and categorize Android malware and unsafe ad library. This work designed AndroCollector, which can automatically execute the Android application (app) and collect the network traffic traces. From these traces, this work extracts HTTP traffic features along three important dimensions: quantitative, timing, and semantic and use these features for characterizing malware and unsafe ad libraries. Based on these HTTP traffic features, this work describes a supervised classification scheme for detecting malware and unsafe ad libraries. In addition, to help network operators, this work describes a fine-grained categorization method by generating fingerprints from HTTP request methods for each malware family and unsafe ad libraries. This work evaluated the scheme using HTTP traffic traces collected from 10778 Android apps. The experimental results show that the scheme can detect malware with 97% accuracy and unsafe ad libraries with 95% accuracy when tested on the popular third-party Android markets.

• Journal of KIISE
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• v.44 no.4
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• pp.433-438
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• 2017

Presently, the ubiquitous emergence of high-speed-network environments has led to a rapid increase of various applications, leading to constantly complicated network traffic. To manage networks efficiently, the traffic classification of specific units is essential. While various traffic-classification methods have been studied, a methods for the complete classification of network traffic has not yet been developed. In this paper, a correlation model of the network flow is defined, and a traffic-classification method for which this model is used is proposed. The proposed network-correlation model for traffic classification consists of a similarity model and a connectivity model. Suggestion for the effectiveness of the proposed method is demonstrated in terms of accuracy and completeness through experiments.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.599-617
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• 2006

A network model and a Genetic Algorithm(GA) is proposed to solve the simultaneous estimation of the trip distribution and traffic assignment from traffic counts in the congested networks in a logit-based Stochastic User Equilibrium (SUE). The model is formulated as a problem of minimizing the non-linear objective functions with the linear constraints. In the model, the flow-conservation constraints of the network are utilized to restrict the solution space and to force the link flows meet the traffic counts. The objective of the model is to minimize the discrepancies between the link flows satisfying the constraints of flow-conservation, trip production from origin, trip attraction to destination and traffic counts at observed links and the link flows estimated through the traffic assignment using the path flow estimator in the legit-based SUE. In the proposed GA, a chromosome is defined as a vector representing a set of Origin-Destination Matrix (ODM), link flows and travel-cost coefficient. Each chromosome is evaluated from the corresponding discrepancy, and the population of the chromosome is evolved by the concurrent simplex crossover and random mutation. To maintain the feasibility of solutions, a bounded vector shipment is applied during the crossover and mutation.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.161-169
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• 2010

According to the recent increase in air traffic more efficient air traffic control is required. This paper proposes the algorithm for efficient air traffic flow management. Aeronautical traffic environment is different from the common traffic environment since it needs vertical and horizontal separation deviation. In this paper used vincenty's fomula, we calculated distance of route for produced weight that was applied air traffic volume in distance of route using dijkstra algorithm. Then we let aircraft selects a course that minimize to wasting of fuel and time. As a simulation result, so unlilke simply shortest course calculation of existing course calculation algorithm, we confirmed that proposed algorithm in this paper can do air traffic control more efficiently by selecting optimized route.