3 in a study by maze and kamyab 2 a work zone

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Unformatted text preview: eveloped using ARENA simulation program. The model developed to provide the delay estimation when a lane closure occurs and to visually demonstrate the forecasted delay. Lane changing and car following algorithms were included in the simulation model. The authors investigated the effects of the slow moving vehicles and late mergers using the developed simulation model. They compared the results of the developed simulation model, traffic flow rate, speed, and delay time with the actual data. They found that the outputs of the model establish a level of confidence that the model is capable of simulating the conditions of the work zone. The results of their study showed that with traffic volumes less than 700 vehicles per hour, it is unlikely to observe delay at the lane closures. At traffic volumes of 950 vehicles per hour, it is more likely to observe delay in 6 the construction work zones. The authors were contacted in order to get more information about the details of the ARENA simulation model, but no information was obtained about the architecture of the model. Al-Kaisy, Stewart and Van Aerde [5] performed a simulation study to examine the capacity and the operational performance at freeway diverge a reas. In order to understand the traffic behavior at freeway diverge areas, they used microscopic traffic simulation model INTEGRATION. Car following behavior and lane changing behavior are the most important features of INTEGRATION for simulating freeway operations. Using the user specified free flow speed, speed at capacity, capacity and jam density single regime speed flow density relationship is determined in the model. Another important feature of the program is that it includes both mandatory and discretionary lane changing behavior. Mandatory lane changing occurs when a driver must change the lane because of the ending lane or closed lane, and discretionary lane changing occurs when the other lane provides better driving conditions. Al-Kaisy et al. developed their model at an exit ramp. They analyzed different deceleration lane lengths at exit ramps and their effects on capacity and operational performance at freeway diverge areas. . Benekohal and Abu-Lebdeh [6] performed a variability analysis, using the stochastic traffic simulation model TRAF-NETSIM outputs. In the study the authors used batch means and replications to assess variability in the measure of effectiveness calculations of NETSIM. They used average delay, average speed, and vehicle trips as the measures of effectiveness parameters. The outputs of the simulation model are analyzed by the statistical methods such as batch means method, replication method, and correlation among batches method. The batch means method is performed by running the 7 program for one long replication and dividing it into smaller batches. Statistics are collected and using the variability within the batches, a confidence interval is build for the model. Another way of building confidence interval is replication method. In this method multiple independent replications having same roadway and traffic conditions are run for the model and statistics on the system performance are collected. Statistics for the batches may be treated as stationary time series data, when a long run is divided into batches. Plot of the mean value for each batch against time will help to determine whether the time series is stationary. The authors proposed an interval calculation method and compared the results of the simulation model with the results they calculated using the proposed interval calculation method. Their study showed that with the proposed interval calculation method they could build confidence intervals for the measure of effectiveness values. Bloomberg and Dale [7] compared microscopic simulation models VISSIM and CORSIM by using them in a study for designing alternatives in Seattle, Washington. CORSIM was developed by FHWA to analyze freeways, urban streets, and corridors or networks. VISSIM was developed at the University of Karlsruhe, Germany to analyze functionally classified roadways and public transportation operations. In order to compare these two simulation models, the authors applied the models to analyze the alternatives for the project performed by Washington State Department of Transportation. Six different scenarios were analyzed using the models. The authors find differences in the car following logic, network-coding process, gap acceptance, modeling of signals, animation features and output data of the models. The network coding process is different between the two models. CORSIM uses a link- node structure wherein the user defines the 8 attributes such as speed, lane configurations, and traffic control devices to the links and nodes. In VISSIM use of nodes is eliminated, the model relies on links and connecters which allow the user to match the network geometry to field conditions. The car following model in CORSIM sets a desired amount of headway distanc...
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This document was uploaded on 02/26/2014 for the course E 515 at University of Louisiana at Lafayette.

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