• Journal of Korean Society of Transportation
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• v.31 no.4
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• pp.3-17
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• 2013

The purpose of this study is to develop a traffic assignment model where the variable of signal intersection delay is taken into account in assigning traffic in large-scale network settings. Indeed, despite the fact that the majority of the increase in travel time or cost involving congested urban network or interrupted flow are accounted for by stop delays or congested delays at signal intersections, the existing traffic assignment models did not reflect this. The traffic assignment model considering intersection delays presented in this study was built based on the existing traffic assignment models, which were added to by the analysis technique for the computation of intersection delay provided in Korea Highway Capacity Manual. We can conclude that a multiple variety of simulation tests prove that this model can be applied to real network settings. Accordingly, this model shows the possibility of utilizing a model considering intersection delay for traffic policy decisions through analysis of effects of changes in traffic facilities on large urban areas.

• Journal of the Korean Society for Railway
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• v.14 no.3
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• pp.276-284
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• 2011

In our study, we present a new LOGIT-based traffic assignment model applicable to intercity railway network. Most traffic assignment models have been developed for public transit assignment in urban area, so that they are known to produce unrealistic results in intercity railway demand analysis. Especially, since the introduction of KTX, more passengers are using a route including KTX service and the schedule becomes more compatible with transfer. Our study presents a new LOGIT-based traffic assignment model considering passenger transfer. To do so, we suggest a new route search algorithm to find K paths with non increasing order in the utility value.

• 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.

• Management Science and Financial Engineering
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• v.15 no.1
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• pp.51-69
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• 2009

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 a non-linear objective function with the linear constraints. In the model, the flow-conservation constraints are utilized to restrict the solution space and to force the link flows become consistent to the traffic counts. The objective of the model is to minimize the discrepancies between two sets of link flows. One is the set of link flows satisfying the constraints of flow-conservation, trip production from origin, trip attraction to destination and traffic counts at observed links. The other is the set of link flows those are estimated through the trip distribution and traffic assignment using the path flow estimator in the logit-based SUE. In the proposed GA, a chromosome is defined as a real vector representing a set of Origin-Destination Matrix (ODM), link flows and route-choice dispersion coefficient. Each chromosome is evaluated by the corresponding discrepancies. 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 technique is used during the crossover and mutation.

• Journal of Korean Society of Transportation
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• v.8 no.1
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• pp.55-71
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• 1990

The behavioral mechanism underlying the traffic assignment model is a choice, or decision-making process of traveling paths between origins and destinations. The deterministic approach to traffic assignment assumes that travelers choose shortest path from their origin-destination pair. Although this assumption seems reasonable, it presumes that all travelers have perfect information regarding travel time, that they make consistently correct decision, and that they all behave in identical fashion. Stochastic user equilibrium assignment relaxes these presumptions by including a random component in traveler's perception of travel time. The objective of this study is to compare "A Model of Deterministic User Equilibrium Assignment" with "Models of Stochastic User Equilibrium Assignment" in the theoretical and practical aspects. Specifically, SUE models are developed to logit and probit based models according to discrete choice functions. The models were applied to sioux Falls net ork consisting of 24 zones, 24 nodes and 76 links. The distribution of perceived travel time was obtained by using the relationship between speed and traffic flow.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.123-137
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• 2004

The study on traffic assignment is actively being performed which reflect networks status using time. Its background is increasing social needs to use traffic assignment models in not only hardware area of road network plan but also software area of traffic management or control. In addition, multi-class traffic assignment model is receiving study in order to fill a gap between theory and practice of traffic assignment model. This model is made up of two, one of which is multi-driver class and the other multi-vehicle class. The latter is the more realistic because it can be combined with dynamic model. On this background, this study is to build multidynamic model combining the above-mentioned two areas. This has been a theoretic pillar of ITS in which dynamic user equilibrium assignment model is now made an issue, therefore more realistic dynamic model is expected to be built by combining it with multi-class model. In case of multi-vehicle, FIFO would be violated which is necessary to build the dynamic assignment model. This means that it is impossible to build multi-vehicle dynamic model with the existing dynamic assignment modelling method built under the conditions of FIFO. This study builds dynamic network model which could relieve the FIFO conditions. At the same time, simulation method, one of the existing network loading method, is modified to be applied to this study. Also, as a solution(algorithm) area, time dependent shortest path algorithm which has been modified from existing shortest path algorithm and the existing MSA modified algorithm are built. The convergence of the algorithm is examined which is built by calculating dynamic user equilibrium solution adopting the model and algorithm and grid network.

• 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.11 no.1
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• pp.67-86
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• 1993

A formulation of dynamic traffic assignment between multiple origins and single destination was first introduced in 1987 by Merchant and Nemhauser, and then expanded for multiple destination in the late 1980's (Carey, 1987). Based on behavioral choice theory which provides proper demand elasticities with respect to changes in policy variables, traffic phenomena can be analysed more realistically, especially in peak periods. However, algorithms for these models are not well developed so far(working with only small toy network) and solutions of these models are not unique. In this paper, a new model is developed which keeps the simplicity of static models, but provides the sensitivity of dynamic models with changes of O-D flows over time. It can be viewed as a joint departure time and route choice model, in the given time periods(6-7, 7-8, 8-9 and 9-10 am). Standard multinomial logit model has been used for simulating the choice behavior of destination, mode, route and departure time within a framework of the incremental network assignment model. The model developed is workable in a PC 386 with 175 traffic zones and 3581 links of Seoul and tested for evaluating the exclusive use of Namsan tunnel for HOV and the left-turn prohibition. Model's performance results and their statistical significance are also presented.

• Journal of Korean Society of Transportation
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• v.17 no.4
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• pp.71-84
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• 1999

The purpose of this study is to construct a dynamic traffic analysis model using the existing traffic flow theory in order to develope a dynamic traffic assignment technique. In this study the dynamic traffic analysis model was constructed using Daganzo's CELL TRANSMISSION THEORY which was considered more suitable to dynamic traffic assignment than the other traffic flow theories. We developed newly the diverging split module, the cost update module and the link cost function and defined the maximum waiting time decision function that Daganzo haven't defined certainly at his Papers. The output that resulted from the simulation of the dynamic traffic analysis model with test network I and II was shown at some tables and figures, and the analysis of the bottleneck and the HOV lane theory showed realistic outputs. Especially, the result of traffic assignment using the model doesn't show equilibrium status every time slice but showed that the average travel cost of every path maintains similarly in every time slice. It is considered that this model can be used at the highway operation and the analysis of traffic characteristics at a diverging section and the analysis of the HOV lane effect.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.113-128
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• 2000

This paper presents a first year report of an ongoing multi-year project to develop a systolic parallel simulation system for dynamic traffic assignment. The fundamental approach to the simulation is systolic parallel processing based on autonomous agent modeling. Agents continuously act on their own initiatives and access to database to get the status of the simulation world. Various agents are defined in order to populate the simulation world. In particular existing modls and algorithm were incorporated in designing the behavior of relevant agents such as car-following model headway distribution Frank-Wolf algorithm and so on. Simulation is based on predetermined routes between centroids that are computed off-line by a conventional optimal path-finding algorithm. Iterating the cycles of optimization-then-simulation the proposed system will provide a realistic and valuable traffic assignment. Gangnum-Gu district in Seoul is selected for the target are for the modeling. It is expected that realtime traffic assignment services can be provided on the internet within 3 years.