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A Dynamic Traffic Analysis Model for the Korean Expressway System Using FTMS Data

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A Dynamic Traffic Analysis Model for the Korean Expressway System Using FTMS Data Proceedings of the Eastern Asia Society for Transportation Studies, Vol.7, 2009 A Dynamic Traffic Analysis Model for the Korean Expressway System Using FTMS Data Jeong Whon, YU Mu Young, LEE Professor Researcher Division of Environmental, Civil Graduate School of Engineering and Transportation Engineering Ajou University Ajou University Suwon, Korea 443-749 Suwon, Korea 443-749 Fax: +81-31-219-1613 Fax: +81-31-219-1613 E-mail: [email protected] E-mail: [email protected] Abstract: Operation of intelligent transportation system 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 Key Words: Dynamic, Subarea, FTMS Data 1. INTRODUCTION 1.1 Background of the study Conditions of transportation system change according to the correlation between the physical facilities and the demand, which in turn varies with the passage of time. Until now, static analyses have been conducted for the planning and operation of the transportation system, focusing on the average behavior of the passengers. Meanwhile, the rapid increase in the number of registered vehicles is causing the problem of imbalance between the demand and the supply in the transportation system in Korea. It is not surprising that the concerns regarding dynamic traffic management, which involves the concentration of traffic by time flowing, are increasing (Ran, 1996). The transportation network that uses the ITS (intelligent transportation system) technology facilitates the construction of a time-dependent database for network state (Mahmassani, 2001), and the requirements which come to be high for analysis of the transportation system using this technology indicate the limitations of the current traffic analysis model and the future research trend. Dynamic traffic analysis that is a main subject of this research may be utilized in various traffic field such as real time traffic management, traffic operation, traffic demand management as well as Dynamic Traffic Assignment, utilizing by basis algorithm to prepare in ultramodern traffic system period hereafter. This research has a meaning from the point which is early step of research about dynamic traffic analysis that take advantage of real individual travel data and is expected that more lively research about dynamic analysis field. Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2009 1.2 Research Contents Development of dynamic analysis model on the basis of existing static traffic planning model 20 years ago in transportation planning field, is progressing and it is displaying big current of research direction that planning field and research of traffic operation field are widening commonness scope hereafter. In case of static analysis of concept an existing day or during 1 hour, it is a arithmetical and average analysis which follows in O-D traffic volume regarded as intention of travel and network capacity relationships. Also, the distinctive quality according to flowing of traffic to progress with flowing of time can't be reflected, and it has a problem that delay of intersection that is presented in several researches can't be reflected. Currently, travel time, speed, and delay according to Volume-delay Function utilized effect analysis by improvement of transportation system is the standard for choice of route, and it is not a travel time of correct meaning. Time-dependent O-D trip table is constructed every 15 minutes about expressway of whole country, utilizing data of FTMS (Freeway Traffic Management System) in this research, and methodology for converting time-dependent O-D of whole country expressway into time- dependent subarea O-D was developed in order to solve the problem of computation complexity. Subarea analysis must be conducted not only because of its efficiency in terms of operation time but also because the traffic analysis under the advanced transportation system involves the accurate analysis of the subject area instead of the whole network. Analysis of research is taking advantage of TCS data that is each individual real travel data through network of highway, the error of the O-D traffic volume which is a main input date of traffic analysis could be diminished. and then in case of trip maker using Expressway which is a toll road, he has a strong intention to shorten his own travel time when he chooses a path and this heighten reliability of path selection model. The construction of the time-dependent O-D trip table has been constructed over the Seoul- Daejeon corridor of Gyeongbu Line with model calibration process time zone every 15 minutes. While existing static traffic model is constructed through one calibration process about 1 points, but time-dependent calibration process of (60/15)* 24 =96 about 1 points is accomplished in this research. Also network state analysis by time zone is accomplished through scenario analysis by traffic accidents situation and capacity enlargement plan to confirm application possibility of constructed model. Figure 1 Procedure of the research Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2009 Chapter 3 of this paper introduces a methodology for converting the dynamic origin- destination (O-D) trip tables established using the FTMS (Freeway Traffic Management System) data into the subarea O-D trip tables. In Chapter 4, the applicability of this model is verified via scenario analysis, and the necessity of dynamic traffic analysis model, which is a future traffic analysis trend, is presented. In Chapter 5, the results of this study and the aim of the future study are presented. 2. Relevant Literature The researches on dynamic traffic analysis that have thus far been conducted used either of two kinds of techniques: the analytical and the simulation techniques. Among the analytical techniques, the approach that uses variational inequality is known to be useful in dynamic assignment. Friesz (1993) presented the problem of dynamic user equilibrium (DUE) by converting it into a variational inequality, and the link-based variational-inequality model was developed by Ran et al. (1996). The network model, which is a constraint of the dynamic model, must be accurately established so that it could describe the traffic with the passage of time. To describe the congestion in the network, the point queue model, wherein the travel time of the link is represented by the constant travel time and the delayed queue (Kuwahara, 1997), was recently studied. The horizontal traffic network load model, which horizontally expresses the physical location of a car and which is an improved version of the vertical traffic load model that expresses the queues by piling them up just in front of the crossroad, was also studied. Meanwhile, the models that focus on describing the dynamic characteristics of the traffic flow in a manner similar to the real world are called “dynamic network loading models.” These models, wherein the single link is divided into travel and queue sections and is described by dividing the dynamic condition of the link into travel and waiting, have a limitation in describing the diverse dynamic characteristics of the traffic flow. To address this problem, Cremer (1999) developed a moving cell-based simulation model. In the dynamic analysis model, the travel time changes with the passage of time, unlike the current static shortest-route selection algorithm, which has a fixed-link travel time regardless of the passage of time. The time-dependent, shortest-route selection algorithm was studied by Cooke and Halsey (1996) in full scale. Ziliaskopoulos (1993) developed a time-dependent, shortest-route algorithm from all origins to a specific destination, based on Bellman’s principle of optimality. Dynamic travel assignment has the limitations of dynamic changes, including the queue length of each link, dynamic travel time and traffic inflow/outflow, and route selection. When a constraint of the objective function is added, the objective function can be nonconvex and the optimal solution cannot be derived through the mathematical-optimization technique (Carey, 1992). The simulation loading algorithm, which is suitable for route-based travel assignment, was proposed for the driver’s dynamic route selection. Mahmassani (2001) developed a simulation-assignment methodology for dynamic travel assignment. The vehicles generated by the time-dependent O-D traffic are assigned using four methods. The travel pattern by time zone for the next travel assignment is generated through simulation Proceedings of the Eastern Asia Society for Transportation Studies, Vol.6, 2009 3. METHODOLOGY 3.1 Dynamic Traffic Analysis Model Traffic
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