• 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 the Korean Society for Railway
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• v.17 no.2
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• pp.140-147
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• 2014

Line planning is an important step to determine the optimal frequencies of trains given the forecasted demand for each train type. The main input data for line planning is the leg traffic demand which can be derived using suitable traffic assignment models. However most assignment models require a line plan, in other words, train frequencies or headways, so that inconsistent results just by the procedural approach to find an optimal line plan after determining leg traffic can be avoided. This paper suggests a unified model that can consider the traffic assignment and line planning, simultaneously. We further provide an elaborated approximation algorithm and, finally, provide experimental results determined for the Korean railway network.

• Journal of Korean Society of Transportation
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• v.18 no.5
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• pp.99-107
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• 2000

Path-based assignment(PBA) is valuable to dynamic traffic control and routing in integrated ITS framework. As one of widely studied PBA a1gorithms, Gradient Projection(GP) a1gorithm typically fields rapid convergence to a neighborhood of an optimal solution. But once it comes near a solution, it tends to slow down. To overcome this problem, we develop more efficient path-based assignment algorithm by combining Conjugate Gradient method with GP algorithm. It determines more accurate moving direction near a solution in order to gain a significant advantage in speed of convergence. Also this algorithm is applied to the Sioux-Falls network and verified its efficiency. Then we demonstrate that this type of method is very useful in improving speed of convergence in the case of user equilibrium problem.

• Journal of the Korean Society for Railway
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• v.12 no.4
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• pp.488-498
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• 2009

The characteristics of intercity rail network are different from those of public transit network in urban area. In this paper, we proposed a new transit assignment model which is generalized form of deterministic assignment model by introducing line selection probability on route section. This model consider various characteristics of intercity rail and simplify network expansion for appling search algorithms developed in road assignment model. We showed the model availability by comparing with existing models using virtual networks. The tests on a small scale network show that this model is superior to existing models for predicting intercity rail demand.

• Journal of Korean Society of Transportation
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• v.19 no.2
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• pp.53-60
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• 2001

본 논문의 목적은 대중교통 노선배정 시에 여러 수단간의 환승을 고려함으로써 다수단 대중교통망 내에서 수단선택과 노선선택을 동시에 수행할 수 있도록 확률적인 통행배분(traffic assignment) 모형의 하나인 다이알 알고리즘을 응용할 것을 제시하고 그 알고리즘의 속성을 정확하게 규명하는데 있다 승용차의 확률적 통행배분모형으로 잘 알려져 있는 Dial 알고리즘은 로짓모형에 기초한 것이므로 다수단간의 대중교통 수단선택과 노선선택과 같은 선택 행태를 동시에 설명할 수 있는 모형적 특성을 기본적으로 내재하고 있다. 본 연구에서 제시한 대중교통 노선선택에 적용될 수 있도록 수정된 다이알 알고리즘은 기존의 결정적 대중교 통 노선배정 모형들의 단점을 극복할 수 있는 특성을 갖고 있다. 즉 결정적 대중교통 노선배정모형은 기종점간 최단경로에 교통량을 전랑배분(All-or-Nothing)하여 통행자들의 행태적 속성을 제대로 반영하지 못하고 있으며, 다수단 대중교통망 내에서 환승을 포함한 복합 대중교통수단의 선택을 효용극대화 이론에 기초하지 않고 최소비용노선에 전량배분하는 모형의 한계점을 갖고 있다. 이러한 결정적 대중교통 노선배정모형의 단점을 수정된 다이알 알고리즘은 개선할 수가 있다. 본 연구에서는 알고리즘의 특성을 파악하기 위한 모의실험으로 Sioux Falls 형태의 대중교통 네트워크를 이용하여 기존의 알고리즘과 비교 분석하였다. 분석의 탄력성을 갖고 있는 수정된 대중교통 다이알 알고리즘이 현실적 대중교통 통행패턴을 기존 모형보다 합리적으로 설명할 수 있을 것으로 보이며, 특히 다수단 대중교통망이 형성된 대도시의 대중교통 정책분석에 적합한 기법이 될 수 있을 것으로 고려된다.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.89-100
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• 2008

In an urban network controlled by traffic signals, there is an interaction between the signal timing and the routes chosen by individual road users. This study develops a bi level programming model for traffic signal optimization in networks with path based traffic assignment. In the bi level programming model, genetic algorithm approach has been proposed to solve upper level problem for a signalized road network. Path based traffic assignment using column generation technique which is proposed by M.H. Xu, is applied at the lower-level. Genetic Algorithm provieds a feasible set of signal timings within specified lower and upper bounds signal timing variables and feeds into lower level problem. The performance of this model is investigated in numerical experiment in a sample network. In result, optimal signal settings and user equilibrium flows are made.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.117-130
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• 2005

In both deteministic user Optimal Traffic Assignment Model (UOTAM) and stochastic UOTAM, travel time, which is a major ccriterion for traffic loading over transportation network, is defined by the sum of link travel time and turn delay at intersections. In this assignment method, drivers actual route perception processes and choice behaviors, which can become main explanatory factors, are not sufficiently considered: therefore may result in biased traffic loading. Even though there have been some efforts in Stochastic UOTAM for reflecting drivers' route perception cost by assuming cumulative distribution function of link travel time, it has not been fundamental fruitions, but some trials based on the unreasonable assumptions of Probit model of truncated travel time distribution function and Logit model of independency of inter-link congestion. The critical reason why deterministic UOTAM have not been able to reflect route perception cost is that the route perception cost has each different value according to each origin, destination, and path connection the origin and destination. Therefore in order to find the optimum route between OD pair, route enumeration problem that all routes connecting an OD pair must be compared is encountered, and it is the critical reason causing computational failure because uncountable number of path may be enumerated as the scale of transportation network become bigger. The purpose of this study is to propose a method to enable UOTAM to reflect route perception cost without route enumeration between an O-D pair. For this purpose, this study defines a link as a least definition of path. Thus since each link can be treated as a path, in two links searching process of the link label based optimum path algorithm, the route enumeration between OD pair can be reduced the scale of finding optimum path to all links. The computational burden of this method is no more than link label based optimum path algorithm. Each different perception cost is embedded as a quantitative value generated by comparing the sub-path from the origin to the searching link and the searched link.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.135-150
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• 2002

The basic assumption of analytical Dynamic Traffic Assignment models is that traffic demand and network conditions are known as a priori and unchanging during the whole planning horizon. This assumption may not be realistic in the practical traffic situation because traffic demand and network conditions nay vary from time to time. The rolling horizon implementation recognizes a fact : The Prediction of origin-destination(OD) matrices and network conditions is usually more accurate in a short period of time, while further into the whole horizon there exists a substantial uncertainty. In the rolling horizon implementation, therefore, rather than assuming time-dependent OD matrices and network conditions are known at the beginning of the horizon, it is assumed that the deterministic information of OD and traffic conditions for a short period are possessed, whereas information beyond this short period will not be available until the time rolls forward. This paper introduces rolling horizon implementation to enable a multi-class analytical DTA model to respond operationally to dynamic variations of both traffic demand and network conditions. In the paper, implementation procedure is discussed in detail, and practical solutions for some raised issues of 1) unfinished trips and 2) rerouting strategy of these trips, are proposed. Computational examples and results are presented and analyzed.

• 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.

• Proceedings of the KOR-KST Conference
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• 1998.10a
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• pp.31-40
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• 1998

본 연구의 목적은 기존의 Cell Transmission(1994, Daganzo) 교통류 이론을 기반으로 동적통행배정 모형을 개발하는 것이다. 이 모형은 동적 O-D 발생모듈, HOV 차선모듈, 분류부 분할모델, 링크비용함수 모듈, 최단경로 탐색 모듈등으로 구성된다. 이 모델에서 적용하는 교통류 모델은 각 링크를 동일한 특성을 가지는 셀로 구분하여 셀내의 진입시간과 진출시간을 계산하여 링크비용을 계산하는데 이것은 비용의 과대·과소 추정을 피할 수 있으며 교통지체 현상을 현실적으로 표현해 줄 수 있는 장점이 있다. 또한 HOV 차선 모듈에 의해 수단별 교통류 진행 및 비용고려가 가능하며 HOV 차선의 평가 및 분석이 가능하다. 기존의 동적통행배정모형은 매 시간대별 출발지에서 균형상태를 추구하는 통행배정기법을 사용하고 있지만 이 모델은 분류되는 노드를 가상의 출발점이라고 가정하여 각 시간대별로 최단경로를 탐색하여 균형상태를 추구해나가는 기법을 적용하고 있다. 각 셀별 차량을 목적지별, 차종별, 대기시간별로 추적하여 진행시키며 분류부에서는 최단경로를 탐색하여 배분된다. 또한 진행하고자 하는 셀의 용량과 현재 셀의 밀도를 고려함으로서 용량제약 하에서의 동적통행배정모형을 적용하고 있다. 이 모형은 고속로의 합류부 및 분류부의 교통특성을 세밀히 분석할 수 있으며, TCS 및 램프미터링과 접목하여 고속도로 운영에 이용될 수 있으며, 고속도로 중·장기적인 계획에 이용될 수 있다.