• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.2D
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• pp.185-192
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• 2011

More practical outputs and insights can be obtained through transportation analysis considering the time-dependent traffic movements. This study proposes a method of constructing time-dependent O-D trip tables for expressway corridor using real-world individual trip data. In this study, time-dependent O-D trip tables for the nationwide highway network are constructed based on toll collection system data. The proposed methodology is to convert nationwide time-dependent O-D trip tables into Korean expressway corridor O-D trip tables in order to deal with the computational complexity arising from simulating a large-scale traffic network. The experiment results suggest that actual individual trip record data can be used to effectively construct time-dependent O-D trip tables. They also imply that the construction of time-dependent O-D trip tables for the national highway networks along with those for Korean expressway developed in this study would make transportation analysis more practical and applicable to real-time traffic operation and control.

• Journal of Korean Society of Transportation
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• v.36 no.3
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• pp.203-215
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• 2018

This study suggests a method to construct large scale dynamic O/D reflecting the characteristic that the passengers' travel patterns change according to the land use patterns of the destination. There are limitations in the existing research about dynamic O/D estimation method, such as the difficulty of collecting data, which can be applied only to a small area, or limiting to a specific transportation network such as highway networks or public transportation networks. In this paper, we propose a method to estimate dynamic O/D without limitation of analysis area based on transportation resources that can be easily collected and used according to the big data era. Clustering analysis was used to calculate the departure time trip distribution ratio based on arrival time and departure time trip distribution function was estimated by each cluster. As a result of the comparison test with the survey data, the estimated distribution function was statistically significant.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.129-137
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• 2009

Operation of intelligent transport systems technologies in transportation networks and more detailed analysis give rise to necessity of dynamic traffic analysis model. Existing static models describe network state in average. on the contrary, dynamic traffic analysis model can describe the time-dependent network state. In this study, a dynamic traffic model for the expressway system using FTMS data is developed. Time-dependent origin-destination trip tables for nationwide expressway network are constructed using TCS data. Computation complexity is critical issue in modeling nationwide network for dynamic simulation. A subarea analysis model is developed which converts the nationwide O-D trip tables into subarea O-D trip tables. The applicability of the proposed model is tested under various scenario. This study can be viewed as a starting point of developing deployable dynamic traffic analysis model. The proposed model needs to be expanded to include arterial as well without critical computation burden.

• Journal of Korean Society of Transportation
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• v.18 no.5
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• pp.83-97
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• 2000

The traffic management schemes through traffic signal control and information provision could be effective when the link-level data and trip-level data were used simultaneously in analysis Procedures. But, because the trip-level data. such as origin, destination and departure time, can not be obtained through the existing surveillance systems directly. It is needed to estimate it using the link-level data which can be obtained easily. Therefore the objective of this study is to develop the model to estimate O-D demand using only the link flows in highway network as a real time. The methodological approaches in this study are kalman filer, least-square method and normalized least-square method. The kalman filter is developed in the basis of the bayesian update. The normalized least-square method is developed in the basis of the least-square method and the natural constraint equation. These three models were experimented using two kinds of simulated data. The one has two abrupt changing Patterns in traffic flow rates The other is a 24 hours data that has three Peak times in a day Among these models, kalman filer has Produced more accurate and adaptive results than others. Therefore it is seemed that this model could be used in traffic demand management. control, travel time forecasting and dynamic assignment, and so forth.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.5 no.1 s.9
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• pp.1-12
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• 2006

In order to estimate a dynamic origin and destination demand between on and off-ramps in the freeways, a traffic flow theory can be used to calculate a link distribution proportion of traffics moving between them. We have developed a dynamic traffic estimation model based on the three-phase traffic theory (Kerner, 2004), which explains the complexity of traffic phenomena based on phase transitions among free-flow, synchronized flow and moving jam phases, and on their complex nonlinear spatiotemporal features. The developed model explains and estimates traffic congestion in terms of speed breakdown, phase transition and queue propagation. We have estimated the link, on and off-ramp volumes at every time interval by using traffic data collected from vehicle detection systems in Korea freeway sections. The analyzed results show that the developed model describes traffic flows adequately.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.93-102
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• 2005

An Origin-Destination (O/D) is considered as one of the important information in route choices and trip assignments. A household interview survey is deemed to be the traditional and the most widely used method in making sample O/D and its conversion to the total O/D. Some researchers have studied to estimate dynamic O/D from the relationship between link volumes and trip assignment model. Nowadays, owing to the recent rapid spread of cellular phones. Location information of the cellular phone through the Base Station(BS) is considered as an alternative to O/D estimation. In this study, the methodology of generating BS-based O/D and the methodology of converting this O/D into an administrative district-based O/D are proposed. The information of GPS positions and cellular BS positions have acquired by establishing GPS equipment and cellular phone on taxies in Cheongju. Three weeks data are collected and used in estimating O/D by matching them on a digital map. Scatter diagram and sample correlation coefficients are used to investigate the similarity of the GPS-based O/D pattern among weeks, among days, and among times in day. The results show that there are few significant differences among weeks. But there is a difference in O/C pattern between weekday and weekend. Furthermore, there is a difference between morning peak and afternoon peak. Two methodologies are proposed to convert BS-based O/D into an administrative district-based O/D. The first one is to use the distribution pattern of GPS coordinates, the other is to use the coverage area of the BSs. To validate such converted O/D, GPS O/D is used as a true value. The statical analyses through scatter diagram, MAE and RMSE shows that there is few significant defference of pattern between the estimated BS-based O/D and GPS O/D. In the case of using only cellular information, the methodology using coverage area of the BSs is recommended for estimating O/D.

• Journal of Korean Society of Transportation
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• v.24 no.6 s.92
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• pp.89-102
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• 2006

The purpose of this paper is to develop a dynamic OD estimating model to overcome the limitation of depicting teal situations in dynamic simulation models based on static OD trip. To estimate dynamic OD matrix we used the hybrid discrete choice model(called the 'Demand Simulation Model'), which combines travel departure time with travel mode and travel path. Using this Demand Simulation Model, we deduced that the traveler chooses the departure time and mode simultaneously, and then choose his/her travel path over the given situation In this paper. we developed a hybrid simulation model by joining a demand simulation model and the supply simulation model (called LiCROSIM-P) which was Previously developed. We simulated the hybrid simulation model for dependent/independent networks which have two origins and one destination. The simulation results showed that AGtt(Average gap expected travel time and simulated travel time) did not converge, but average schedule delay gap converged to a stable state in transportation network consisted of multiple origins and destinations, multiple paths, freeways and some intersections controlled by signal. We present that the hybrid simulation model can estimate dynamic OD and analyze the effectiveness by changing the attributes or the traveler and networks. Thus, the hybrid simulation model can analyze the effectiveness that reflects changing departure times, travel modes and travel paths by demand management Policy, changing network facilities, traffic information supplies. and so on.