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Han, Yeong-Jun;Son, Bong-Su;Kim, Won-Gil
- 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.
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Park, Eun Mi;Oh, Hyun Sun
- 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.
https://doi.org/10.7470/jkst.2014.32.5.522 인용 PDF KSCI

Park, Eun-Mi;Go, Myeong-Seok
- Journal of Korean Society of Transportation
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- v.27 no.3
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- pp.71-77
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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 communications. The VISSIM simulation experiments were performed to address the issues in developing the preventive congestion management algorithm proposed in the companion paper. Traffic flow stability measures were developed based on the platoon profile, which enables us to explicitly consider traffic flow stability in traffic flow management. Traffic flow management strategies according to the traffic flow states were proposed: Maintain the equilibrium speed for free flow state, maintain the traffic flow stability by platoon control for critical state, and surpress the shock wave propagation for congested state. And finally potential benefit of the proposed traffic flow management scheme was evaluated based on the simulation experiment results. It is considered that extensive field experiments should be performed to confirm the simulated results.
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Park, Eun-Mi
- 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.
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