• Journal of Korean Society of Transportation
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• v.21 no.3
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• pp.107-120
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• 2003

Over the decades, a lot of studies have dealt with the traffic characteristics and phenomena at a merging area. However, relatively few analytical techniques have been developed to evaluate the traffic flow at the area and, especially, the ramp merging capacity has rarely been. This study focused on the merging behaviors that were characterized by the relationship between the shoulder lane flow and the on-ramp flow, and modeled these behaviors to determine ramp merge capacity by using gap acceptance theory. In the process of building the model, both an ideal mergence and a forced mergence were considered when ramp-merging vehicles entered the gap provided by the flow of the shoulder lane. In addition, the model for the critical gap was proposed because the critical gap was the most influential factor to determine merging capacity in the developed models. The developed models showed that the merging capacity value was on the increase as the critical gap decreased and the shoulder lane volume increased. This study has a meaning of modeling the merging behaviors including the forced merging type to determine ramp merging capacity more precisely. The findings of this study would help analyze traffic phenomena and understand traffic behaviors at a merging area, and might be applicable to decide the primary parameters of on-ramp control by considering the effects of ramp merging flow.

• Journal of Navigation and Port Research
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• v.26 no.1
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• pp.95-100
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• 2002

The first version of KHCM was Published in 1992 and is currently used in engineering Practice extensively. The study of new manual was initiated by Korea Institute of Construction Technology 1998 and is intended to be ready for publication by the year 2002. According to the field survey, the action of the individual merging vehicle creates turbulence in the vicinity of the ramp-freeway junction area. The purpose of this paper is to develop the model for Predicting the for entering the lanes 1 and 2($V_{12}$) and the density function at the influence zone by comがring the research works on the ramp junction in the USHCM 2000. The methodology has two major steps : the determination of the flow entering Lanes 1 and 2 immediately upstream of the merge influence area: and the density of the flow within the ramp influence area As a result of this paper the specific functions for such models are suggested through the regression analysis of data collected at four freeway fields in Korea.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.115-126
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• 2009

The lane-change behavior usually consists of discretionary lane-change and mandatory lane-change types. For the first type, drivers change lanes selectively to maintain their own driving condition and the second type is the case that the drivers must change the current lane, which can occur in recurrent congestion sections like merging and weaving sections. The mandatory lane-change behavior have a great effect on the operation condition of freeway. In this paper, we first generate data such as traffic volumes, speeds, densities, and the number of lane-change within the merging and weaving sections using the data of individual vehicle collected from time-lapse aerial photography. And then, the data is divided into the stable and congested flow by analyzing the speed variation pattern of individual vehicles. In addition, the number of lane-changing from ramp to mainline within every 30-meter interval is investigated before and after traffic congestion at study sites and the distribution of lane-changing at each 30-meter point is analyzed to identify the variation of lane-changing ratio depending on the stable and congested flows. To recognize the effect of mainline flow influenced by ramp flow, this study also analyzes the characteristics of the lane-changing distributions within the lanes of mainline. The purpose of this paper is to present the basic theory to be used in developing a lane-changing model at the merging and weaving sections on freeways.

• Journal of Korean Society of Transportation
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• v.18 no.5
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• pp.33-42
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• 2000

This Paper is a Part of research Project series to analyze unique traffic characteristics observable within weaving sections on urban freeways. The research objectives were to establish with headway distribution and maximum Passing volume on weaving sections the basis of weaving designs that can promote safety and efficiency. Until now, when one wants to check the maximum Passing volume on weaving sections, it is taken for granted using headway distribution of freeway basic section. However. it was suspected in this research that for weaving sections different form of headway distribution had better be used. To prove this, field surveys were made to count headway intervals which supposedly were influenced not only by freeway basic section flows but also by weaving flows and later on used to develop headway distribution for weaving sections. For validation of the developed headway distribution, $x^2$-test was applied to three different data set of observed headways, currently used headway distribution for basic sections(Pearson Type III distribution) and new headway distribution. The result indicated new headway distribution as the most appropriate distribution form. Also, maximum passing volume within weaving sections was calculated based on new headway distribution and compared with Drew's maximum Passing volume.

• Journal of Korean Port Research
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• v.14 no.1
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• pp.66-75
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• 2000

From the traffic analysis, and model constructions and verifications for speed prediction on the freeway ramp junctions with 70mph speed limit, the following results were obtained : ⅰ) The traffic flow distribution showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy distribution was also shown to be varied by a big difference depending on the time periods. Especially, the occupancy in the morning peak period showed over 100% increase when compared with the 24hours average occupancy, and the occupancy in the afternoon peak period over 25% increase when compared with the same occupancy. ⅲ) The speed distribution was not shown to have a big difference depending on the time periods. Especially, the speed in the morning peak period showed 10mph decrease when compared with the 24hours'average speed, but the speed did not show a big difference in the afternoon peak period. ⅳ) The analyses of variance showed a high explanatory power between the speed predictive models(SPM) constructed and the variables used, especially the upstream speed. ⅴ) The analysis of correlation for verifying the speed predictive models(SPM) constructed on the ramp junctions were shown to have a high correlation between observed data and predicted data. Especially, the correlation coefficients showed over 0.95 excluding the unstable condition on the diverge section. ⅵ) Speed predictive models constructed were shown to have the better results than the HCM models, even if the speed limits on the freeway were different between the HCM models and speed predictive models constructed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.111-121
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• 1999

From the traffic analyses, and model constructions and verifications for speed prediction on the freeway ramp junctions with 70mph speed limit, the following results obtained: ⅰ) The traffic flow distribution showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy distribution was also shown to be varied by a big difference depending on the time periods. Especially, the occupancy in the morning peak period showed over 100% increase when compared with the 24hours average occupancy, and the occupancy in the afternoon peak period over 25% increase when compared with the same occupancy.ⅲ) The speed distribution was not shown to have a big difference depending on the time periods. Especially, the speed in the morning peak period shown 10mph decrease when compared with the 24hours' average speed, but the speed did not show a big difference in the afternoon peak period.ⅳ) The analyses of variance showed a high explanatory power between the speed predictive models(SPM) constructed and the variables used, especially the upstream speed. ⅴ) The analysis of correlation for verifying the speed predictive models(SPM) constructed on the ramp junctions were shown to have a high correlation between observed data and predicted data. Especially, the correlation coefficients showed over 0.95 excluding the unstable condition on the diverge sectionⅵ) Speed predictive models constructed were shown to have the better results than the HCM models, even if the speed limits on the freeway were different between the HCM models and speed predictive models constructed.