• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.153-161
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• 2002

다사용자계층 통행배정(Multiple User Class Assignment) 문제란 교통망을 이용하는 통행자들이 이질적인 통행계층으로 구성된 경우, 이들 각 계층의 통행수요를 교통망에 배정하는 문제를 의미한다. 이는 기존 통행 배정모형들이 모든 통행자의 통행특성이 동질적이라고 가정함으로서 발생하는 불합리한 통행배정 결과를 완화시키기 위한 방법이다. 또한, 최근 지능형교통체계(Intelligent Transportation Systems, ITS)사업에서 교통정보제공시스템이 구현될 예정임에 따라, 교통정보를 제공받는 계층과 그렇지 못한 계층간의 영향을 분석하거나 혼잡통행료부과 등과 같은 교통관리전략을 정확히 평가하기 위해서 다사용자계층 통행배정모형에 대한 관심이 증가하고 있다. 그러나, 다사용자계층 통행배정모형의 경우, 사용자간의 상호영향으로 통행비용함수의 1차 편미분행렬(Jacobian matrix)이 비대칭(Asymmetric)이 되어 동등 수리최소화문제(Equivalency mathematical Minimization program)로 구성할 수 없고 또한 수치적으로 풀기가 어렵다는 문제가 있다. 본 연구는 이런 문제점을 극복할 수 있는 모형식과 알고리듬을 제시코자 한다. 본 연구에서 제시된 모형은 2가지 특징이 있다. 먼저, 각 사용자 계층간의 상호영향을 모형내에 반영하며, 기종점쌍간의 통행시간변화에 따른 수요변화를 고려한다는 점이다. 이를 위하여 변동부등모형(Variational Inequality Model. VI)으로 문제를 구성하며, 이에 대한 해석 알고리듬도 제시한다. 또한, 변동부등모형으로 구축된 다사용자계층 모형이 다사용자계층 균형조건과 동일함을 보여주는 동등성조건(Equivalency condition)도 제시한다.

• Journal of Korean Society of Transportation
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• v.25 no.4
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• pp.99-108
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• 2007

This paper presents an elastic demand stochastic user equilibrium traffic assignment that could not be easily tackled. The elastic demand coupled with a travel performance function is known to converge to a supply-demand equilibrium, where a stochastic user equilibrium (SUE) is obtained. SUE is the state in which all equivalent path costs are equal, and thus no user can reduce his perceived travel cost. The elastic demand SUE traffic assignment can be formulated based on a dynamic system, which is a means of describing how one state develops into another state over the course of time. Traditionally it has been used for control engineering, but it is also useful for transportation problems in that it can describe time-variant traffic movements. Through the Lyapunov Function Theorem, the author proves that the model has a stable solution and confirms it with a numerical example.

• Journal of Korean Society of Transportation
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• v.19 no.1
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• pp.89-99
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• 2001

The conventional studies on equilibrium network design problem(ENDP) with fixed travel demand models assume that the future OD travel demand might not be changed even if the structure and the capacity of the network are improved. But this fixed demand assumption may loose its validity in the long-range network design because OD travel demand actually shifts with the network service level. Thus, it is desirable to involve the variable travel demand which is determined endogenously in the model in the optimal network design. In this paper a hi-level model formulation and solution procedure for ENDP with variable travel demand are presented. Firstly It is considered how to measure the net user benefits to be derived from the improved in link capacities, and the equilibrium network design problem considered here is to maximize the increase of net user benefit which results from a set of lift capacity enhancements within the budget constraints, while the OD travel demands and link travel times are obtained by solving the lower level network equilibrium problem with variable demand. And secondly sensitivity analysis is carried out to find the links to which the network equilibrium flow pattern is the most sensitive. Finally numerical example with simple network is carried out to test the validity of the model.

• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.169-178
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• 2006

Traffic assignment has been used both for predicting travel demands and for evaluating the tools for alleviating congestion on road network in advance. Some assignment models have been proposed such as equivalent mathematical minimization method, variational inequality problem, nonlinear complementary problem and fixed point method, in following the principle of Wardrop (1952) that no driver can not Improve his travel cost by unilaterally changing his route. Recently Jin(2005a) presented a traffic assignment model based on dynamic process. This paper proposes a solution algorithm for the model of Jin and assesses the performances. Compared to the Frank-Wolfe method, which has been wildly used for solving the existing assignment models, the proposed algorithm is expected to be more efficient because it does not need to evaluate the objective function. Two numerical examples are used for assessing the algorithm, and they show that the algorithm converges to user equilibrium of Wardrop.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.155-167
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• 2008

This paper studies a multiple user class variable demand user equilibrium and system optimal condition, and then establishes solution algorithms for them. The traffic network equilibrium is accomplished with basis on following assumptions. For considering heterogeneous road user, several user classes have discrete set of VOTs and the travel demand of each user classes varies according to generalized travel cost. this paper specifically investigates following question on multi-class variable demand: Are user equilibrium flows pattern dependent on the unit (time or money) perceived by road user classes? What is system optimal condition according to the unit used in measuring the travel cost or disutility? Finally, using this network equilibrium condition, The traffic assignment algorithm of each equilibrium condition are established.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.81-88
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• 2008

This paper presents the travel demand estimation using interval estimation methods during the trip generation stage, and then followed the other three stages of the four stage trip estimation. We have used real data of Dae-jun City. To estimate travel demand using the interval estimation method, a reliability level was set to 95% by a upper bound value, a middle value and a lower bound value. The four stage traffic demand analysis procedure was equally applied and finally interval traffic was estimated. The result showed a difference between maximum values and middle values depending on the destination during the trip generation stage. It depends on an explanation ability of regression analysis. Most of interval estimation ratio resulted in the traffic assignment stage showed ${\pm}5{\sim}18%$ difference on the average and ${\pm}30{\sim}50%$ at the most.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.139-149
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• 2004

As the expansion of road capacity has become impractical in many urban areas, congestion pricing has been widely considered as an effective method to reduce urban traffic congestion in recent years. The principal reason is that the congestion pricing may lead the user equilibrium (UE) flow pattern to system optimum (SO) pattern in road network. In the context of network equilibrium, the link tolls according to the marginal cost pricing principle can user an UE flow to a SO pattern. Thus, the pricing method offers an efficient tool for moving toward system optimal traffic conditions on the network. This paper proposes a continuous network design program (CNDP) in network equilibrium condition, in order to find optimal congestion toll for maximizing net economic benefit (NEB). The model could be formulated as a bi-level program with continuous variable(congestion toll) such that the upper level problem is for maximizing the NEB in elastic demand, while the lower level is for describing route choice of road users. The bi-level CNDP is intrinsically nonlinear, non-convex, and hence it might be difficult to solve. So, we suggest a heuristic solution algorithm, which adopt derivative information of link flow with respect to design parameter, or congestion toll. Two example networks are used for test of the model proposed in the paper.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.1
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• pp.61-83
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• 2009

This study developed a variable demand traffic assignment model by stable dynamics. Stable dynamics, suggested by Nesterov and do Palma[19], is a new model which describes and provides a stable state of congestion in urban transportation networks. In comparison with the user equilibrium model, which is based on the arc travel time function in analyzing transportation networks, stable dynamics requires few parameters and is coincident with intuitions and observations on congestion. It is therefore expected to be a useful analysis tool for transportation planners. In this study, we generalize the stable dynamics into the model with variable demands. We suggest a three stage optimization model. In the first stage, we introduce critical travel times and dummy links and determine variable demands and link flows by applying an optimization problem to an extended network with the dummy links. Then we determine link travel times and path flows in the following stages. We present a numerical example of the application of the model to a given network.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.675-685
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• 2014

This paper develops a differentiated pricing strategy over each segment of expressways based on the second-best pricing method for reducing congestion. To this end, a bi-level problem is proposed, in which the upper level of the model is formulated to determine toll level of each segment for minimizing traffic congestion, whereas the lower level of the model is formulated as a variable demand assignment problem. The sensitivity analysis based algorithm is took placed to find optimal solutions of upper level model. An application of the proposed model uses the modified Sioux-Falls network. The results show that the segment-based differentiated pricing strategy performs better than the existing uniform pricing strategy in reducing traffic congestion. This study can be applied as a demand management method to relieve disutility of excessively congested segments of expressways.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.253-259
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• 2013

Investment scenarios in the transportation network design problem usually contain installation or expansion of multi-mode transportation links. When one applies the mode choice analysis and traffic assignment sequentially for each investment scenario, it is possible that the travel impedance used in the mode choice analysis is different from the user equilibrium cost of the traffic assignment step. Therefore, to estimate the travel impedance and mode choice accurately, one needs to develop a combined model for the mode choice and traffic assignment. In this paper, we derive the inverse demand and the excess demand functions for the multi-mode multinomial logit mode choice function and develop a combined model for the multi-mode variable demand traffic assignment problem. Using data from the regional O/D and network data provided by the KTDB, we compared the performance of the partial linearization algorithm with the Frank-Wolfe algorithm applied to the excess demand model and with the sequential heuristic procedures.