The car following model in corsim sets a desired

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Unformatted text preview: e between the vehicles. Vehicles in the model seek to maintain the minimum allowed headway distance while they are not exceeding the maximum allowed speed. Speed, acceleration, and status of each vehicle are recomputed in every second by CORSIM. VISSIM like CORSIM uses an interval based simulation approach. VISSIM simulates traffic flow by moving driver- vehicle units through a network. Stochastic distributions are used to replicate individual driver vehicle unit behavior and dynamic headway. Gap acceptance feature in CORSIM is adapted using 10 different driver types. Variable gap acceptance is assigned to each driver considering the current available gap and a personal gap acceptance value. Bloomberg and Dale concluded that both simulation models are acceptable for modeling traffic, but they recommended that the modelers should use more than one simulation model to make more accurate recommendations. Makigami and Nakanishi [8] developed a macroscopic simulation model to investigate the traffic flow in the bottleneck sections of an expressway during peak period. They collected the traffic flow data by video recording, aerial photography, and measuring travel times and running speeds. Estimation of capacity of bottleneck sections and measurement of spot running speed is calculated using video recording method. Aerial photography method gave the measurement of traffic density and pursuit of behavior of congested area. Using these traffic data the capacity of the highway section is calculated. Mathematical simulation model is developed using the capacity 9 information. The results of the developed simulation model are compared to the actual data collected. The results of the simulation model did not show significant difference from the actual traffic data collected. Memmott and Dudek [9] developed a model entitled Queue and User Evaluation of Work Zones (QUEWZ). The purpose of the model is to determine the effects of different lane closure strategies in work zones. Memmott and Dudek found limitations in several of the methods previously developed by traffic engineers and software engineers to measure the costs associated with work zone delays. Most of the simulation models used average daily traffic volume for simulation, but Memmott and Dudek used hourly traffic volumes in their model. The traffic pattern can have a large effect on the speeds and queues throughout the day and using average daily volume might cause misleading results. Usually, the traffic will not arrive at a work zone in a uniform pattern and therefore, the average daily traffic value can misrepresent the actual arrival rates for different hours of the day. This effect is evident during rush hour when typically more delays occur than at times associated with less traffic volume. Delay or travel time costs, vehicle running costs, speed-change cycling costs, and accident costs resulting from restricted capacity through a work zone can be determined using the model developed by Memmott and Dudek. Morales and Paniati [10] conducted a simulation study to analyze the effectiveness of traffic simulation model, ROADSIM, at two- lane roads. Roadsim is a reprogrammed version of an earlier developed model TWOWAF. The model recalculates the position of the vehicles in 1-second intervals considering the effects of the roadway geometry, traffic control, driver preferences, vehicle type and performance 10 characteristics, and passing opportunities based on the oncoming traffic. TWOWAF logic was modified to include the car following logic and vehicle generation logic which emits vehicles onto the simulated roadway at each end. This new model is called Roadsim. Morales and Paniati compared the results of the simulation model Roadsim, measures of effectiveness values, with the actual data collected from the two- lane rural road in Virginia. The geometric conditions (grade of the road) and traffic conditions (mean speed, percentage of the trucks) are studied and it is found that ROADSIM generates appropriate results for simulating the traffic flow at two lane rural roads when it is compared to the actual traffic flow data. Nakanishi et al. [11] developed a macroscopic traffic simulation system, which also includes the microscopic simulation features. The simulation model MITRAM (Road Traffic Simulation System with the Microscopic Model for Analyzing Traffic Jam in the Broad Areas) is used for the congested real time road traffic simulation. The microscopic features of the model like decision- making process of the motorists are modeled according to the fuzzy theory. They developed a fuzzy model for simulating the behavior of the vehicle, which reflects the microscopic features of the traffic in the simulation. Robles and Janson [12] implemented a dynamic traffic simulation model (DYMOD) to the I-25/HOV corridor at southeast of Denver to predict the traffic conditions during incidents. Robles and Janson used loop detectors to collect the actual traffic data. Using the...
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