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5 peak hour, and this increase in peak capacity may impact period of the day based on the estimated changes in travel downstream capacity bottlenecks. times by mode and by time period. The module employs The HCM Assignment Module predicts the highway vehi- direct elasticities and cross-elasticities derived from the Port- cle travel time effects of the traffic-flow improvement for a land Tour-Based Model. An example of a direct elasticity is fixed level of demand. Inputting the base demand to the mod- the percentage change in HOV demand during the AM peak ule is equivalent to predicting travel times for the day that a for each percentage change in HOV travel time during the traffic-flow improvement is first opened to traffic. Travelers AM peak. An example of a cross-elasticity is the percentage have not had time to adjust to the travel time savings, so, at change in HOV demand during the AM peak for each per- this stage in time, there is no demand response. If future centage change in single-occupancy vehicle (SOV) travel demands are input to the module, then the module will pre- time during the AM peak. Cross-elasticities are also used to dict future travel times and delays for that level of demand. account for shifting of travel between peak and off peak for This module has multiple uses in the methodology, being each mode of travel. applied to the base case, short-term, and long-term analyses. Heavy-duty vehicles (e.g., trucks) are presumed to respond The required inputs for the HCM Module are vehicle OD in the same manner as light-duty SOVs to travel changes in USER'S GUIDE tables (by mode and time period), the baseline geometric char- this module. They are not modeled separately. acteristics of the regional highway network (facility type, free- If a metropolitan planning organization already has a tour- flow speeds, capacity characteristics, and segment lengths), and based model in place that can predict the impacts of travel time similar geometric information for the traffic-flow improve- and cost changes on out-of-home trip making, time of day, and ment. The module computes the highway link operating char- mode choice, then that model can be used in place of the sim- acteristics: volume/capacity and mean speed. pler Traveler Behavior Response Module described here. The module uses the 2000 HCM Chapter 30 speed-flow equations (sometimes called the Akcelik equations in the lit- erature) and capacities to estimate the mean speed of traffic 2.5 GROWTH REDISTRIBUTION MODULE on each link of the highway network. A standard static users Significant improvements in transportation infrastructure equilibrium (SUE) assignment of the OD table is performed in one part of the urban region will impact the geographic in this module using the HCM equations for each period of distribution of housing and job growth in the region over the the day (typically AM, PM, and off-peak). very long term (25+ years). Significant infrastructure invest- It should be noted that the travel time savings on the ments may also affect the total growth rate for the region by improved segment may be partially compensated by increased changing the attractiveness of the region to migrants from delays at downstream bottlenecks. This "downstream" effect other regions. This latter effect, however, requires a model at of traffic-flow improvements are neglected by this module. the national level to properly account for migration between (Tests with the PSRC model show that this effect is not sig- regions. Therefore, this overall affect on total regional growth nificant for the conditions of the PSRC model. See Chap- will be excluded from the methodology. ter 12 of the final report for more details.) The Growth Redistribution Module will predict the very The module computes only highway travel times for mixed- long-term impacts of localized travel time changes (caused flow and high-occupancy vehicle (HOV) lanes. Transit, bicy- by traffic-flow improvements) on the geographic distribution cle, and pedestrian travel times (if needed) must be computed of growth in a metropolitan area. There are already several using some standard travel demand modeling procedure con- sophisticated land-use models available (such as UrbanSim) sistent with the procedure used to estimate the baseline OD that could be used for the purpose of this module. However, tables by time period for each of these nonauto modes of these models require a great deal of specialized economic travel. data and effort to set up for a region (which may be beyond the resources of many metropolitan planning organizations). 2.4 TRAVELER BEHAVIOR When a sophisticated land-use model exists in a region, it can RESPONSE MODULE be used to predict the long-term effects. When such a model is not available, the simple Growth Redistribution Module Travelers will adjust their demand schedule for travel is proposed for use to approximate the long-range land-use in response to changes in the travel time required to reach effects of traffic-flow improvements. their daily activity locations. Demand responses may include The Growth Redistribution Module requires that a base- changes in trip lengths (i.e., trip distribution), number of trips line 20- to 25-year forecast of land-use growth (households (i.e., trip generation), time of day (i.e., peaking), and mode of and employment changes) be available for the metropolitan travel (i.e., mode choice). The Traveler Behavior Response area. This baseline forecast should have been prepared either Module predicts how travel demand will react to the travel manually or with a model taking into account accessibility time savings created by traffic-flow improvements. changes as well as all of the other factors that commonly The module computes estimated changes in demand for affect the distribution of growth within a region. A simple lin- each entry in the OD table for each mode of travel and each ear regression model is fitted to the baseline land-use forecast.