• 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.

• Journal of Korean Society of Transportation
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• v.5 no.2
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• pp.97-112
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• 1987

The objective of this study is to construct not only trip production and attraction in Pusan but also to study and examine appropriateness of the model positively. Depending on the estimation models of trip production and attraction of each zone that have been constructed in this study, it has been proved that the formula of multiple regression by the explanation variables like the indices of total employees, total students, floor spaces of residentials and floor spaces of educational and cultural areas within the study areas have very high explanatory capacity and appropriateness. It si considered that a study of method on new division, integration or omission etc. of the existing zones preceeding for reduction of calculation quantity and a study of estimation error have to be done for future study, if these models are used actually.

• 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.

• Proceedings of the KIEE Conference
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• 1999.07a
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• pp.354-356
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• 1999

Through the Standard of MCCB, the Adjustable Type Instant Trip Unit should NO trip at -20% of each current from $5{\times}In$ to $10{\times}In$ and trip +20% of those. In this paper, we obtain the attraction force between Fixing Magnet and Moving Armature. So we first made some samples. do experiments of weight, and simulated the modelling by 3D Maxwell S/W. With values of experiment and simulated values, we do design instant trip springs by using the ADAMS S/W of kinematic simulation. Finally we product the 250A Adjustable Instant Trip Unit, and it is very useful to our customers.

• International Journal of Highway Engineering
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• v.12 no.4
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• pp.93-100
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• 2010

Trip generation is the first step in the conventional four-step model and has great effects on overall demand forecasting, so accuracy really matters at this stage. A linear regression model is widely used as a current trip generation model for such plans as urban transportation and SOC facilities, assuming that the relationship between each socio-economic index and trip generation stays linear. But when rapid urban development or an urban planning structure has changed, socio-economic index data for trip estimation may be lacking to bring many errors in estimated trip. Hence, instead of assuming that a socio-economic index widely used for a general purpose, this study aims to develop a new trip generation model by type based on the market separation for the variables to reflect the characteristics of various zones. The study considered the various characteristics (land use, socio-economic) of zones to enhance the forecasting accuracy of a trip generation model, the first-step in forecasting transportation demands. For a market separation methodology to improve forecasting accuracy, data mining (CART) on the basis of trip generation was used along with a regression analysis. Findings of the study indicated as follows : First, the analysis of zone characteristics using the CART analysis showed that trip production was under the influence of socio-economic factors (men-women relative proportion, age group (22 to 29)), while trip attraction was affected by land use factors (the relative proportion of business facilities) and the socio-economic factor (the relative proportion of third industry workers). Second, model development by type showed as a result that trip generation coefficients revealed 0.977 to 0.987 (trip/person) for "production" 0.692 to 3.256 (trip/person) for "attraction", which brought the necessity for type classifications. Third, a measured verification was conducted, where "production" and "attraction" showed a higher suitability than the existing model. The trip generation model by type developed in this study, therefore, turned out to be superior to the existing one.

• Journal of Korean Society of Transportation
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• v.33 no.3
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• pp.268-275
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• 2015

As Korea is predicted to be a super-aged society in the near future, transport policies that internalize the elderly have also drawn attentions. Even though some studies have examined the travel by the elderly with various motives, it is, however, difficult to find references that deal with the unique spatio-temporal characteristics of senior trips. For example, the models by time period have represented the temporal property while a set of independent variables associated with urban infrastructure have addressed the spatial feature. This study was conducted under a trip attraction model for transit. The result shows that transit facilities, commercial areas, and hospitals are the dominant factors to explain the travel by the elderly, particularly during 09:00-17:00.

• Journal of Korean Society of Transportation
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• v.33 no.2
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• pp.113-124
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• 2015

The KOTI(Korea Transport Institute) released the new version of KTDB(Korea Transport DataBase) in public. The new KTDB is different from the past KTDB in using the concept of trip generation and trip attraction instead of using the concept of Origin-Destination (OD), which was used in the past KTDB. Thus, the appropriate analysis method for future travel demand became necessary for the new type of KTDB. The method should be based on the concept of PA(Production-Attraction). This study focused on analysis of trip generation and trip distribution related to newly generated trips by future land developments. The study also described clearly the standardized forecasting process and methods with PA travel tables. The study showed that the analysis results with OD-based analysis can be different from the results with PA-based analysis in forecasting travel demand for a simple example case even though they used exactly same orignal travel data. Therefore, this study emphasized that a proper method should be applied with the new PA-based KTDB. It is necessary to prepare and disseminate guidelines of the proper forecasting method and application with PA-based travel data for practician.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.712-714
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• 2002

Through the Standard of UL489, the Adjustable Type Instant Trip Unit should NO trip at 80% of each current from $5{\times}In$ to $10{\times}In$ and trip 130% of those. In this paper, we obtain the attraction force between Fixing Magnet and Moving Armature. we simulated the modelling by 3D Finite Element Method. With values of experiment and simulated values, in this paper, we show the method for set up the process of designing Instant spring.

• Proceedings of the KIEE Conference
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• 1998.07a
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• pp.134-136
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• 1998

When a MCCB Instant trip spring which is adjusted to notrip at -20% of each current from $5{\times}In$ to $10{\times}In$ and trip +20% of those is designed, we should know attraction force between Fixed Magnet and Armature. So we first made some samples, do experiments of weight, and simulated the modelling by 3D Maxwell S/W. With values of experiment and simulated values, we do design instant trip springs and repeat the above process. Finally we set up the Process of designing Instant spring. With it, we can save time and R&D cost.

• 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.