• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.83-94
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• 2017

There is a two lane ECTS(Electronic Toll Collection System) that users can pass with 80kph high speed in SeoBusan Tall Gate. This system to be combined two hi-pass lanes for removing meddle-island have been operated successfully. But, the appearance of two Lane ETCS makes toll gate more complicated, so it is very important how to arrange effectively various tolling lanes. This study was trying to evaluate lane configuration for minimizing speed and speed deviation among all kinds of lanes including two Lane ETCS in seoul toll gate. That is, we selected all scenarios to be happened actually, and evaluated them using micro traffic simulation model (VISSIM). The results of this study showed that each alternative had a very different speed and speed deviation by lane each other, so we will be able to achieve effective operation and configuration of lanes in toll gate using scenario methodology.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.3
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• pp.521-528
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• 2016

The tollbooths of a main motorway toll plaza are usually operated proactively responding to the variations of traffic demands of two-type vehicles, i.e. cars and the other (heavy) vehicles, respectively. In this vein, it is one of key elements to forecast accurate traffic volumes for the two vehicle types in advanced tollgate operation. Unfortunately, it is not easy for existing univariate short-term prediction techniques to simultaneously generate the two-vehicle-type traffic demands in literature. These practical and academic backgrounds make it one of attractive research topics in Intelligent Transportation System (ITS) forecasting area to forecast the future traffic volumes of the two-type vehicles at an acceptable level of accuracy. In order to address the shortcomings of univariate short-term prediction techniques, a Multiple In-and-Out (MIO) forecasting model to simultaneously generate the two-type traffic volumes is introduced in this article. The MIO model based on a non-parametric approach is devised under the on-line access conditions of large-scale historical data. In a feasible test with actual data, the proposed model outperformed Kalman filtering, one of a widely-used univariate models, in terms of prediction accuracy in spite of multivariate prediction scheme.