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Agenda - 05-05-2009 - Information Item
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Agenda - 05-05-2009 - Information Item
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5/1/2009 2:20:07 PM
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5/5/2009
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Agenda
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Minutes - 20090505
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\Board of County Commissioners\Minutes - Approved\2000's\2009
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26 <br />probability of a person making 0, 1, 2, 3, 4, or 5 trips depending on trip purpose, and these <br />probabilities are used to calculate the effective daily trip rate per person. These rates are used to <br />calculate the overall trip rate for the household, by purpose, and these are summed to the traffic <br />analysis zone level. The models were estimated using data from the 1994 Triangle household <br />travel behavior survey. Several employment types were identified as special generators for the <br />Triangle Region. This classification was based on employment centers that exhibited unique trip <br />attraction characteristics asdemonstrated by the travel behavior survey data. Universities, regional <br />shopping centers, regional hospitals and the RDU airport were all identified as special generators. <br />Special generator rates were developed for those groups. Trip tables were also built for commercial <br />vehicles, internal -external trips, and through trips. <br />Non-motorized trips are separated out for each trip purpose using a model with variables for <br />household income group, density of the area for the household, and an accessibility measure. <br />School bus trips are also separated out based on the share of school bus trips for each county <br />based on the data in the travel behavior survey. <br />The travel behavior survey was used to determine where the trips would be `attracted to'. <br />Regression coefficients were developed for the five trip purposes based on: retail and non-retail <br />employment, and households. These trips at the employment end were then stratified into the <br />five strata using a share model. <br />3.8 Trio distribution <br />The Triangle Regional Model uses a destination choice model to distribute trips. The model <br />builds zone-to-zone trip tables (by five purposes) using a composite time for impedance where <br />Composite Time = 1/[(1/Highway Time) + (x/Transit Time)] where x is the transit share for the <br />stratum in the travel behavior survey. Variables used in addition to composite time include retail <br />and non retail employment, and households. In the case of the home based school purpose, <br />population was used as a variable. Before distributing trips, the trips are split into peak and off <br />peak periods based on the time of day analysis performed on the travel behavior survey data. <br />3.9 Mode choice and transit assignment <br />The mode choice for the Triangle Regional model is based on a nested LOGIT model. This <br />approach creates a predictive model that is responsive to changes in quality of service variables <br />such as travel time and cost. The different `nests' of the model reflect a traveler's choice between <br />local bus, express bus, rail, single occupancy vehicles, and multiple occupancy vehicles. The <br />coefficients for the mode choice model were asserted by consultant staff based on experience in <br />other regions and Federal Transit Administration guidance. The constants were derived from the <br />Triangle Travel Behavior survey and the Triangle On-Board transit survey through the calibration <br />process. <br />3.10 Iiighwav assignment and vehicle miles traveled <br />Once the total number of trips has been determined, and the mode by which the trip is made has <br />been chosen, the trips are assigned to the network. For the Triangle Regional Model, this is done <br />using amulti-class user equilibrium assignment. The classes are single occupant vehicles, high <br />occupancy vehicles, and commercial vehicles (trucks). User equilibrium employs an iterative <br />18 <br />
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