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3 opening day travel time improvements. It is assumed that the The Growth Redistribution Module predicts the impacts traveler behavior effects cannot completely eliminate the of traffic-flow improvements on growth patterns within "opening day" travel time improvements; otherwise, there is the region. Subareas within the region that have better- no longer a stimulus to cause the traveler behavior effects. than-average accessibility improvements will have The fourth effect of traffic-flow improvements is a redistri- greater-than-average growth rates in the region. bution of growth (i.e., new homes and jobs) within the region The Modal Activity Module translates the mean speeds to areas that benefit from the travel time savings attributable and volumes predicted by the previous modules into a to a traffic-flow improvement. This effect will be called the distribution vehicle-hours of travel (VHT) by speed cat- "growth redistribution" effect. It is possible that the traffic- egory and acceleration/deceleration rate category. flow improvement might also enhance the relative competi- The Air Quality Module translates the modal activity tiveness of the entire metropolitan region for new jobs and new data into estimates of vehicle emissions. homes, thus influencing overall growth of the region. How- ever, this global effect is beyond the scope of this research The methodology employs macroscopic approximations project and methodology. It would require a full-blown socio- of microscopic behavior throughout each of the modules. USER'S GUIDE economic forecasting model plus some kind of assumption The intent is to obtain a practical methodology that can be regarding the pace of traffic-flow improvements in other employed by a wide range of agencies while retaining as competing metropolitan areas of the United States, Mexico, much as possible the behavioral accuracy of a microscopic and Canada. analytical approach. The research team assumes for the sake of this research The proposed methodology predicts the change in demand project that all competing metropolitan areas have similar and vehicle emissions caused by traffic-flow improvements policies for implementing traffic-flow improvements. Thus, at two points in time: short term (5 to 10 years) and long term a specific set of traffic-flow improvements would likely also (25+ years). Figure 1 provides a flow chart overview of the be implemented in all metro regions. Thus, the relative com- methodology. petitiveness of the metro regions would be unaffected. The The methodology requires as input methodology will focus on redistribution impacts within a region, not total growth impacts for the entire region. A set of baseline travel demand tables (OD tables) for The foundation of the NCHRP 25-21 methodology is that AM, PM, and off-peak periods; traveler behavior response and growth redistribution occur A set of baseline highway and transit networks for the only if the traffic-flow improvement results in a net change in AM, PM, and off-peak periods; and trip travel time. Thus, travel behavior responses and growth The proposed traffic-flow improvement characterized in redistribution can never drive travel time savings to zero. terms of its impact on mean free-flow speeds and capac- This research will not account for possible effects of a ities in the baseline networks. traffic-flow improvement that do not relate to travel time, such as operating cost improvements. Vehicle operating cost The first round of analysis (i.e., the base) assigns the base- (which can also affect travel demand) is correlated with travel line OD tables (by mode of travel and time period) to the time and is not treated separately here, since the research baseline (i.e., no improvement) transportation networks for team is not considering toll changes. The marginal effects each time period and mode. The methodology then computes of reduced acceleration/deceleration events on vehicle wear the mean speed and flow for each highway link. This link and tear (and thus vehicle operating costs) also will be unac- information is fed to the Vehicle Modal Activity Module, counted for. which outputs tables of vehicle activity (VHT) by speed and acceleration/deceleration category. The modal activity infor- mation is fed to the Vehicle Emissions Module (VOC, CO, 2.2 OUTLINE OF THE METHODOLOGY NOX, and PM), which computes the vehicular emissions. The second round of analysis (short term) adds the traffic- The recommended methodology is a blended macroscopic- flow improvement to the baseline network and computes new microscopic approach composed of five modules: vehicle trip travel times for the improved network. The new travel times are compared with the baseline travel times to The HCM Assignment Module predicts the highway determine the changes in travel times. The changed travel travel times based upon traffic operations analysis speed- times are entered into the Traveler Behavior Response Mod- flow equations contained in the 2000 Highway Capac- ule, which modifies the baseline OD tables to produce revised ity Manual (HCM). OD tables. The revised OD tables are assigned to the high- The Traveler Behavior Response Module uses elastici- way network to produce mean speed and flow for each high- ties derived from the Portland Tour-Based Model to pre- way link. The information is then fed to the Vehicle Modal dict the impact of travel time changes on trip making by Activity and Vehicle Emissions Modules to obtain emissions peak period and by mode of travel. for the short term.