Transferability of Activity-Based Model Parameters (2014) / Chapter Skim
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Pages 12-28
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12 As described in Chapter 1, assessment of the effectuality of transferring the Sacramento activity-based model specification to the Jacksonville and Tampa regions followed two primary avenues of inquiry. The first was a strict test of the transferability of estimated parameters, with the overall objective of finding out whether the behavioral sensitivities that drive model specification in one region (Sacramento)
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13 (Sacramento, Tampa, Jacksonville) and then compare the estimated coefficients along with the standard errors of those estimates to identify cases in which the estimated coefficients were significantly different across regions.
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14 Table 3.1. Number of Observations Used to Estimate Tampa and Jacksonville DaySim Models Tables in Appendix A Name of Choice Model Component Number of Observations (% of sample size of corresponding Sacramento model)
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15 system level-of-service variables, despite including a composite accessibility variable. As shown in Table 3.2, the "person exact number of tours model" in particular has more than 100 parameters, nearly all of which are constants that represent interactions between tour purposes or day-pattern dimensions and person types.
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16 which was also expected due to its larger sample sizes. The one noteworthy exception is the intermediate-stop destination choice model for which Jacksonville has 10 more significant parameters than the corresponding Tampa model, an observation that is explored in more detail in the next section.
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17 and for all three in combination, where P1 is observed proportion and P2 is the expected proportion under independence assumptions. As a rough indicator of correlation between common components, OE ratios indicate that the Jacksonville and Tampa models are more strongly correlated than either the Jacksonville-Sacramento combination or the Tampa- Sacramento combination.
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18 Statistically Significant Differences Statistically significant differences between statistically significant estimated parameter values are summarized in Table 3.5 for each of the possible pairs of models. This tally counts only estimated parameters that were statistically significant in both models.
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19 2 occupants (HOV2) , high-occupancy vehicle, 3 or more occupants (HOV3+)
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20 Tampa model and the Jacksonville model with respect to these parameters. These differences are likely due to the larger proportion of retirees, who are more likely to have a single car and live in a single-driver household.
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21 Work-based sub-tour mode choice (Appendix A, Table A.14)
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22 Trip-level mode choice (Appendix A, Tables A.31–A.32)
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23 paired with Sacramento. The most likely reason for this is the common NHTS surveys used in the Tampa and Jacksonville estimations.
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24 sub-tours. These types of issues tend to exacerbate the problem of limited sample sizes.
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25 of households fall into the $75,000+ income category. The corresponding statistics for the Tampa region are 48% and 17%, respectively (U.S.
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26 segment, which is more important in the Tampa region, was not well-represented in the original specification; therefore, parameters were added and calibrated to provide this additional variation across household and person types. Table B.5 in Appendix B presents calibration results for the work-based sub-tour generation model.
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27 eight parameters were on average adjusted by a greater distance (325% versus 50% APLD)
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28 Finally, Table 3.7 provides calibration results for the Jacksonville trip models. The calibration efforts were confined primarily to alternative-specific constants included in the trip time-of-day model, with only a single parameter calibrated in the trip-mode choice model (transit-walk access)
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