• Journal of Korean Society of Transportation
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• v.28 no.6
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• pp.159-166
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• 2010

Trip distribution is to connect travel demand for each OD pair based on travel cost, trip production and attraction derived from trip generation step. In real world the travel cost is a function of travel demand, but existing models could not fully consider such functional relation between travel cost and demand, which leads to an equilibrium in trip distribution model. This paper proves the equilibrium trip distribution by using gravity model. In order to obtain such equilibrium this paper also presents a solution algorithm based on fixed point theorem. The algorithm will be tested with an example and confirmed the equilibrium solution of trip distribution.

• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.58-82
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• 1995

This study providesd an empirical analysis of trip-chaining behavior and its application to transportation planning. In the empirical analysis, changes in trip-chaining patterns since 1970 have been examined and details of current trip-chaining behavior as they describe shopping trip-chaining behavior has changed. Individual trip-chaining has become longer and complex. It appears that the average number of trips per chains has substantially increased over the past 20 years. An increased number of trips in chains means fewer home-based trips. Changes in trip-chaining behavior have several consequences. Important consequences are for transportation and land-use planning. Up to now trips have been treated as if they are independent clusters of home-to-destination-to-home; this approach has not usually taken into account the trip-chaining behavior of individuals. this calls for a different approach to at least the trip generation and trip distribution part of transportation planning. In this study, application of trip-chaining behavior to trip distribution model formulation is proposed and its calibration results are presented.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.3 s.30
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• pp.43-50
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• 2004

This study has an object of searching for appropriateness in applying the trip distribution model by studying the changes of the character of parameter which the model contains and by analyzing and evaluating trip distribution technique out of few steps of pre-estimate technique for the traffic demand through computer simulation centering around Kwangju. Method of this study is investigating the basic theory for trip distribution model and with this grounding, I rearranged it as research data for trip distribution model compatible for Kwangju, using data such as research data on actual state, the statistics annual report and basic plan for traffic full equipment of Kwangju. So, The most stable measure of the type of trip distribution of Kwangju city was produced in Fratar and Detroit model, however, gravity model has a little bit low reliance in sharing of estimation and actual survey although it is astringent in short period.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.81-89
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• 2011

Trip distribution is the second step of the conventional travel demand estimation process, which connects trips between origin and destination, while transport mode choice is the third step of the process, which chooses transport mode among several modes serving for each origin-destination pair. Although these two steps have closely connected, they have been estimated independently each other in the estimation procedure. This paper presents an integrated model combining trip distribution and transport mode choice, and also presents its solution algorithm. The model integrates gravity model adopted for the trip distribution process with logit model employed for the mode choice process. The model would be expected to cope with the inconsistency issue existing in the conventional travel demand estimation procedure. This paper also presents an equilibrium condition, sensitivity of the model, and compares them with those of existing models.

• 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.1 no.1
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• pp.43-47
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• 1983

Within the conventional transportation planning process, "trip distribution" has a significant role to play. The most widely applied trip distribution model is the gravity model, for which Wilson provided the theoretical basis in 1967. The concept of the gravity model, however, still remains ambiguous if we analyze the "trip distribution" with a disaggregate data set. Thus, this paper hypothesizes that the gravity technique is still valid even with the disaggregate data set, by proving that the estimated coefficients of the gravity model, which is derived under the principle of entropy maximization, are identical with those of the multinomial logit model, which is derived under the principle of individual utility maximization.tility maximization.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.2
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• pp.61-68
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• 2011

The circuit breaker of power distribution board is essential part for the protection of electrical disaster from load short, trouble of power system. For the normal operation of circuit breaker, trip coil of the circuit breaker can cut the mechanical contact of circuit breaker from the detection of power system troubles. This paper presents a design and experimental results of trip coil fault detection system for the real time monitoring of the circuit breaker. The designed system is consisted by the trip coil fault detector which is connected to the each circuit breaker and remote monitoring unit. The trip coil fault detector can detect the impedance and operating voltage of the trip coil, and the detected values are compared with the normal state. And the remote monitoring unit can be connected to the 32 channels of trip coil fault detectors by serial communication. From the designed system, the fault and normal states of the trip coil can be remotely monitored in real time. The designed system is verified by the practical circuit breaker of power distribution board. And the results shows the effectiveness of the designed system.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.143-150
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• 2005

Estimation of trip distribution, estimated O-D matrix must satisfy the condition that the sum of trips in a row should equal the trip production, and the sum of trips in a column should equal the trip attraction. In most cases the iterative calculation for convergence is needed to satisfy this condition. Most of all present convergence of iterative methods may results a big difference between estimated value and converged value, and from this, the trip distribution patterns may be changed. This paper presents a new convergence of iterative method that comes closer to meeting the convergence condition and gives the maximum likelihood estimation for calculating a distribution patterns from the trip distribution estimation model. The newly developed method differs from existing methods in three important ways. First, it simultaneously considers both the convergence condition and the distribution patterns. Second, it computers simultaneous convergence of rows and columns instead of iterating respectively. Third, instead of using the growth rates to the trip production, trip attraction, it uses the differences between trip production and sum of trips in a row, and trip attraction and sum of trips in a column. Using 38 by 38 O-D matrix, this paper compared the Fratar method and the Furness method to the newly developed method and found that this method was superior to the other two methods.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.19-28
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• 2009

In case of land development projects constructed, to solve induced transportation volume needs analysis of traffic demand. Trip-generation of land development projects is exactly predicted by using traffic instigating-basic-unit in each facility of land developments. But in case of a phase of trip-distribution, because a range of destinations is very enormous and it needs enormous data to reflect all of its characters, whenever trip-distribution is predicted, the method which assumes the rate of trip-distribution is same both before completion of land development projects and after is often used. But because there is no exact criterion, the method suggested above is also affected by subjective opinion. Accordingly, this study look over using trip-distribution of specific areas's DB and suggests a size of zone to predict a distribution of land development projects exactly. Also production - constrained gravity model which uses the gap between a distribution of suggested ranges and induced land development project is suggested for more exact prediction of trip-distribution. Besides accuracy of prediction is scrutinized by using Mean Squared Error.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.576-584
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• 2017

Traffic demand prediction result is a primary factor for decision making such as the traffic planning and operation. The existing traffic demand prediction 4-step model only covers the trip between the origin and the destination, and not the demand followed by the accessibility improvement, due to the characteristic of this model. Therefore, the purpose of this research is to improve the limitations of the existing model by developing the inter-city trip generation and trip distribution model with more accessibility. After calculating of the trip generation and trip distribution model with more accessibility, the sign of the accessibility coefficient was positive. Commuting was the most insensitive indicator, affected by external factors among the other trip purposes. The leisure trip was the most sensitive, affected by the trip fee. According to the result of comparison with each of estimated model and observational data, it was certain that the reliability and assumption of the model have been improved by discovering the reduced weighted average error rate, Root Mean Square Error (RMSE) and total error through the model with more accessibility compared with the existing one.