• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.117-134
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• 2004

Truck traffic accounts for a substantial fraction of the traffic stream in many regions and is often the source of localized traffic congestion, potential parking and safety problems. Truck trips tend to be ignored or treated superficially in travel demand models. It reduces the effectiveness and accuracy of travel demand forecasting and may result in misguided transportation policy and project decisions. This paper presents the development of speed-flow relationships with truck impacts based on CORSIM simulation results in order to enhance travel demand model by incorporating truck trips. The traditional BPR(Bureau of Public Road) function representing the speed-flow relationships for roadway facilities is modified to specifically include the impacts of truck traffics. A number of new speed-flow functions have been developed based on CORSIM simulation results for freeways and urban arterials.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.115-124
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• 2010

VDF(volume-delay function) is one of the most important factor to improve the reliability of traffic demand estimation because it is for estimation of link travel time based on the traffic volume variation. Because VDF of link except for freeway is applied as the parameter of BPR(bureau of public road) of U.S., it causes to deteriorate the accuracy of traffic demand estimation. The purpose of this paper is to establish new parameter of VDF based on the real-surveyed traffic data in order to improve the problem of the existing VDF. We suggest the reclassification of road hierarchy, the approach of traffic survey, the estimating method of VDF parameter, and the improvements of new VDF application. The new VDF allows us to estimate more realistic traffic situation in parts of demand, travel time and path between origin-destination.

• Journal of Korean Society of Transportation
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• v.30 no.5
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• pp.71-82
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• 2012

Some previous studies adopted a method statistically based on the observed traffic volumes and travel times to estimate the parameters. Others tried to find an optimal set of parameters to minimize the gap between the observed and estimated traffic volumes using, for instance, a combined optimization model with a traffic assignment model. The latter is frequently used in a large-scale network that has a capability to find a set of optimal parameter values, but its appropriateness has never been demonstrated. Thus, we developed a methodology to estimate a set of parameter values of BPR(Bureau of Public Road) function using Harmony Search (HS) method. HS was developed in early 2000, and is a global search method proven to be superior to other global search methods (e.g. Genetic Algorithm or Tabu search). However, it has rarely been adopted in transportation research arena yet. The HS based transportation network calibration algorithm developed in this study is tested using a grid network, and its outcomes are compared to those from incremental method (Incre) and Golden Section (GS) method. It is found that the HS algorithm outperforms Incre and GS for copying the given observed link traffic counts, and it is also pointed out that the popular optimal network calibration techniques based on an objective function of traffic volume replication are lacking the capability to find appropriate free flow travel speed and ${\alpha}$ value.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.6
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• pp.94-104
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• 2010

The capacity of highway is restricted and traffic congestion is caused by increasing traffic demand. Also, greenhouse gases are increased by traffic congestion. CDM (Clean Development Mechanism) is an idea of interest to reduce greenhouse gases. However, CDM's cases applied in traffic field are rare. Thus, it is necessary that methodology to reduce greenhouse gas should be developed and applied to CDM. A methodology for identifying greenhouse gas emissions was developed in this paper. This methodology was developed on the basis of baseline methodology registered at UN. Travel time and speed in the conventional traffic condition and in the automated traffic condition are compared by BPR function. The calculated speed applied to emission factor equation and then $CO_2$ emissions was calculated. A simulation was executed to evaluate the validity of the developed methodology. In the result, advanced vehicle's $CO_2$ emissions are more than conventional vehicle's $CO_2$ emissions in the stable flow condition. However, advanced vehicle's $CO_2$ emissions are less than conventional vehicle's $CO_2$ emissions in the unstable flow condition. It is assure that capacity of highway is enhanced and efficiency of highway is improved by adopting advanced safety vehicle in the smart road.