• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.19-28
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• 2015

In this paper, we proposed an algorithm for the identification of relieving or worsening current traffic congestion using historic traffic congestion patterns. Historical congestion patterns were placed in an adjacency list. The patterns were constructed to represent spatial and temporal length for status of a congested road. Then, we found information about historical traffic congestions that were similar to today's traffic congestion and will use that information to show how to change traffic congestion in the future. The most similar pattern to current traffic status among the historical patterns corresponded to starting section of current traffic congestion. One of our experiment results had average error when we compared identified changes of the congestion for one of the sections in the congestion road by using our proposal and real traffic status. The average error was 15 minutes. Another result was for the long congestion road consisting of several sections. The average error for this result was within 10 minutes.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.99-109
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• 2007

There have been few studies on the impacts of independent recurrent and non-recurrent congestion on freeway networks. The main reason is due partly to the lack of traffic data collected during those periods of recurrent and non-recurrent congestion and partly to the difficulty of using the simulation tools effectively. This study has suggested a methodology to analyze the independent impacts of the recurrent and non-recurrent congestion on target freeway segments. The proposed methodology is based on an elaborately calibrated simulation analysis, using real traffic data obtained during the recurrent and non-recurrent congestion periods. This paper has also summarized the evaluation results from the field tests of two ITS technologies, which were developed to provide drivers with real-time traffic information under traffic congestion. As a result, their accuracy may not be guaranteed during the transition periods such as the non-recurrent congestion. In summary, this study has been focused on the importance of non-recurrent congestion compared to recurrent congestion, and the proposed methodology is expected to provide a basic foundation for prioritizing limited government investments for improving freeway network performance degraded by recurrent or non-recurrent congestion.

• Journal of Korean Society of Transportation
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• v.24 no.4 s.90
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• pp.129-148
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• 2006

The objective of this thesis is to develop a capacity analysis and to develop a methodology to evaluate Level of Service over the entire freeway sections by single MOE (Measure of Effectiveness) This study set forth from a following viewpoint. to analyze entire freeway sections as freeway facility system, it is important to identify the exact point where congestion would occur and the extent of the congestion. Therefore, in this thesis, congestion mechanism on freeways was figured out and congestion analysis methodology was developed. Thereby maximum possible throughput rate and maximum throughput rate in bottleneck sections were calculated and a congestion analysis was carried out. The difference between the new method and existing Procedures is that maximum possible throughput rate and maximum throughput rate. that can be considered as capacities of un-congested and congested flow in the bottleneck section, are variable capacities dependent on demand flow.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.61-74
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• 2005

This study is to investigate the effects of driving anger and traffic congestion on drivers' behaviors. Driving anger is the propensity to become angry while driving, and people differ in the tendency to get angry when encountering frustration and provocation on the road. Individual differences of the propensity contribute to anger on the road and aggressive driving leading traffic vaiolations and accidents. In the experiment three traffic conditions (an open road condition, a bumper-to-bumper traffic condition and a being stuck behind a slower driver condition) were simulated and driving behaviors were collected with RTSA-DS(Road Traffic Safety Authority-Driving Simulator). The results were as follows: Most of high anger drives drove at higher speeds in an open road condition, and in the bumper-to-bumper condition they drove faster and had an higher crash rate, which suggests they did aggressive driving, and risky and unsafe behaviors.

• Journal of the Korea Society for Simulation
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• v.26 no.3
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• pp.95-104
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• 2017

This study focuses on resolving traffic congestion caused by a large scale event based on the case of ROK Joint Officer Commissioning Ceremony, and it was conducted through literature review as well as Arena Simulation. The study purpose is to appropriately allocate and disperse the traffic by utilizing nearby parking lots of facilities. The annual event draws about 7,400 vehicles to a limited number of parking lots, and all vehicles leave the parking lots concurrently, causing a severe bottleneck near the exit and a few roads. In order to resolve the issue, the optimal number of cars in the event area was analyzed. After the analysis, the study found that the overflow of cars in the event area should be allocated to nearby parking lots of facilities with shuttle buses operating to transport the attendees. As the proposed result of the simulation, the traffic congestion time was reduced from 150 minutes to 64 minutes, a total reduction of 86 minutes.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.29-37
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• 2006

As a recurrent congestion of urban freeway occurs in almost same time and section, it is possible to manage the congestion effectively by the expectation and advance correspondence. In the existing traffic management system. we have used pattern data to manage a recurrent congestion. But it is not applicable to an urban freeway which kas various traffic circumstance. In this study, the probability by travel speed using a statistical distribution method will be used to predict the probability of recurrent congestion. It is expected that we can get the point of time and the duration of recurrent congestion, and we can devise an effective advance correspondence and a transportation operation.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.522-530
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• 2014

Spatio-temporal congestion evolution pattern can be reproduced using the VDS(Vehicle Detection System) historic speed dataset in the TMC(Traffic Management Center)s. Such dataset provides a pool of spatio-temporally experienced traffic conditions. Traffic flow pattern is known as spatio-temporally recurred, and even non-recurrent congestion caused by incidents has patterns according to the incident conditions. These imply that the information should be useful for traffic prediction and traffic management. Traffic flow predictions are generally performed using black-box approaches such as neural network, genetic algorithm, and etc. Black-box approaches are not designed to provide an explanation of their modeling and reasoning process and not to estimate the benefits and the risks of the implementation of such a solution. TMCs are reluctant to employ the black-box approaches even though there are numerous valuable articles. This research proposes a more readily understandable and intuitively appealing data-driven approach and developes an algorithm for identifying congestion patterns for recurrent and non-recurrent congestion management and information provision.

• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.115-128
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• 2006

The analytic methodology of a merging area in KHCM(2004) supposes that congestion nay occur when traffic demand is more than capacity However, in many cases, congestion on merging area occurs when summation of traffic demand of main line and ramp is less than capacity, and in present methodology analysis of how main line and ramp flow effect on congestion occurrence is difficult. In this study, the model that is able to estimate traffic flow condition on merging area in accordance with the combination of main line and ramp demand flow is developed. Main characteristic of the model is estimation of maximum possible throughput rate and maximum throughput rate according to the combination of main line and ramp demand flow. Through the estimation of maximum possible throughput rate and maximum throughput rate. it was Possible to predict whether congestion would occur or not and how much maximum throughput rate and congestion would be on merging area. On one hand, in present LOS evaluation methodology on merging area, congestion state is determined as un-congested flow if demand flow is less than capacity. Therefore, to establish more reasonable In evaluation method, new criterion of LOS evaluation on merging area was searched based on the model of this study.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.68-77
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• 2013

This study suggested experimental study results of congestion detection method for intruding vehicle enforcement system. This congestion detection method is developed to determine optimal operation criteria of intruding vehicle enforcement system as detecting traffic congestion. In ITS sector, traffic management systems generally have used a sectional travel speed for congestion detection. However, image sensors have high error rate of congestion detection because of speed error. This study suggested comprehensive congestion detection criteria based on speed and occupancy rate using field studies. As field study results, the proposed intruding vehicle enforcement system using image sensor is capable of accurately detecting the traffic congestion using sectional speed of 20km/h and occupancy rate of 60% as congestion detection criteria.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.161-168
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• 2009

The ubiquitous transportation system environments make it possible to collect each vehicle's position and velocity data and to perform more sophisticated traffic flow management at individual vehicle or platoon level through V2V and V2I communication. It is necessary to develop a new traffic management paradigm to take advantage of the ubiquitous transportation system environments. This paper proposed a preventive congestion management algorithm for uninterrupted flow, whose goal is to minimize the incident potential and maximize the productivity by maintaining traffic flow stability. The algorithm includes the following steps: Processing the raw data to produce the 3-dimension speed/flow/density profile and to produce the platoon profile and the shock wave profile, Determining the traffic state and the flow stability based on the processed data, Deciding the desirable speed the according the traffic flow state, and finally Providing the desirable speed information. It remains as further work to perform field experiments and calibrate the algorithm parameters.