SPR 788 Task 4: Model Testing
Liming Wang
05/25/2017
Task Description
PSU researchers shall apply the newly incorporated mode shift module (in the updated RSPM tool) in the Corvallis Area Metropolitan Planning Organization (CAMPO) to assess how it can inform decision-making and to adjust the model as needed to provide accurate and helpful information. ODOT staff will assist in assembling the necessary data for sensitivity test. Initial testing will be documented by the PSU researchers.
The phases of the testing task are:
Phase 1: Test modules on their own using SLD/NHTS data used in estimation; Test module sensitivity, vary SLD/NHTS inputs one at a time – elasticity response vs. Literature VMT, PMT by mode, total and split by HH income, density, urban form groups
Phase 2: Test module in RVMPO RSPM (using a code wrapper and supplemental RVMPO block group place type inputs) comparing current vs. new outputs, VMT/Alt mode trips at MPO/district geographies (maps) and HH attributes (place types, income, …) – tests full model performance improvement over existing tool using built form variables
Phase 3: Test module in VisionEval (written up to 1st call of this module) – tests to see if module will work in future VisionEval tool
Phase I
For Phase I of Task 4, elasticities of AADVMT and PMT with regard to density (D1B), household income, freeway supply (Freeway lane miles per caipta), transit supply (transit revenue miles per capita) are computed using the 2009 NHTS data. Except for a few unexpected couterintuitive direction of elasticities (bike PMT elasticities wrt D1B), the elasticities are inline with what has been documented in research literature: travel behavior responses to density change is small in magitude. Given the non-linear nature of the models, the elasticities vary by different segments - such as income group, development type, and current density level. Those segments are adopted from what Brian Gregor used in his sensitivity testing for GreenSTEP.
Annual Average Daily VMT (AADVMT)
Model Specification
The specification for the AADVMT model has been documented in Task2. It is replicated here for quick reference.
| metro | nonmetro | |
| (1) | (2) | |
| Drivers | 0.704*** | 0.750*** |
| (0.009) | (0.011) | |
| HhSize | 0.015* | |
| (0.009) | ||
| Workers | 0.186*** | 0.176*** |
| (0.008) | (0.007) | |
| LogIncome | 0.265*** | 0.294*** |
| (0.007) | (0.006) | |
| Age0to14 | 0.104*** | 0.104*** |
| (0.009) | (0.011) | |
| Age65Plus | -0.072*** | -0.077*** |
| (0.008) | (0.007) | |
| log1p(VehPerDriver) | 1.810*** | 1.840*** |
| (0.026) | (0.021) | |
| LifeCycleEmpty Nester | -0.222*** | -0.191*** |
| (0.016) | (0.015) | |
| LifeCycleParents w/ children | 0.040*** | 0.012 |
| (0.015) | (0.017) | |
| LifeCycleSingle | -0.199*** | -0.198*** |
| (0.019) | (0.020) | |
| CENSUS_RNE | -0.108*** | -0.121*** |
| (0.023) | (0.017) | |
| CENSUS_RS | 0.050** | 0.060*** |
| (0.021) | (0.014) | |
| CENSUS_RW | -0.089*** | -0.167*** |
| (0.021) | (0.018) | |
| FwyLaneMiPC | 103.000*** | |
| (20.500) | ||
| D1B | -0.003*** | -0.008** |
| (0.0003) | (0.003) | |
| D2A_WRKEMP | -0.0002 | |
| (0.0001) | ||
| D3bpo4 | -0.001*** | |
| (0.0002) | ||
| TranRevMiPC:D4c | -0.020*** | |
| (0.003) | ||
| D2A_EPHHM | -0.084*** | |
| (0.023) | ||
| D1B:D2A_EPHHM | -0.026*** | |
| (0.007) | ||
| Constant | -1.350*** | -1.480*** |
| (0.075) | (0.066) | |
| Observations | 47,288 | 55,103 |
| R2 | 0.446 | 0.458 |
| Adjusted R2 | 0.446 | 0.458 |
| Residual Std. Error | 0.987 (df = 47270) | 1.010 (df = 55086) |
| F Statistic | 2,241.000*** (df = 17; 47270) | 2,908.000*** (df = 16; 55086) |
| Note: | p<0.1; p<0.05; p<0.01 | |
Population Density (D1B) Sensitivity
Both the table and figures below demonstrate small negative elasticities of AADVMT to local population density (D1B from Smart Location Database population density at block group level). Non-metropolitan areas have larger elasticities; higher density areas have larger elasticities, and TODs have larger elasticities.
| Δ AADVMT wrt Δ D1B | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | AADVMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 46.7 | -0.076 | -0.150 | -0.224 | -0.292 | -0.361 | ||
| non_metro | 58557 | 56.9 | -0.079 | -0.157 | -0.234 | -0.313 | -0.391 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 55.3 | -0.009 | -0.018 | -0.027 | -0.036 | -0.045 | |
| metro | 1k-5k | 42833 | 50.1 | -0.041 | -0.081 | -0.122 | -0.162 | -0.203 | |
| metro | 5k-10k | 19565 | 46.1 | -0.090 | -0.179 | -0.268 | -0.358 | -0.447 | |
| metro | >10k | 8588 | 33.4 | -0.195 | -0.380 | -0.567 | -0.723 | -0.885 | |
| non_metro | <1k | 44365 | 59.2 | -0.024 | -0.048 | -0.072 | -0.096 | -0.120 | |
| non_metro | 1k-5k | 12420 | 50.5 | -0.209 | -0.418 | -0.626 | -0.833 | -1.040 | |
| non_metro | 5k-10k | 1536 | 45.7 | -0.528 | -1.023 | -1.542 | -2.056 | -2.566 | |
| non_metro | >10k | 236 | 32.2 | -0.695 | -1.507 | -2.041 | -2.820 | -3.455 | |
| Income | |||||||||
| metro | <$40k | 28933 | 26.2 | -0.059 | -0.115 | -0.171 | -0.218 | -0.267 | |
| metro | $40k-$80k | 24666 | 47.2 | -0.081 | -0.162 | -0.243 | -0.320 | -0.400 | |
| metro | >$80k | 25780 | 65.6 | -0.092 | -0.184 | -0.276 | -0.366 | -0.457 | |
| non_metro | <$40k | 25270 | 37.2 | -0.058 | -0.116 | -0.172 | -0.230 | -0.287 | |
| non_metro | $40k-$80k | 19280 | 64.7 | -0.085 | -0.169 | -0.254 | -0.337 | -0.420 | |
| non_metro | >$80k | 14007 | 81.8 | -0.110 | -0.219 | -0.328 | -0.436 | -0.544 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 47.3 | -0.044 | -0.089 | -0.133 | -0.177 | -0.221 | |
| metro | Low Density/Rural | 8122 | 56.3 | -0.027 | -0.053 | -0.080 | -0.107 | -0.133 | |
| metro | Mixed | 4441 | 41.6 | -0.086 | -0.171 | -0.257 | -0.342 | -0.427 | |
| metro | Mixed High | 1074 | 31.6 | -0.156 | -0.308 | -0.457 | -0.570 | -0.679 | |
| metro | Residential | 50684 | 46.6 | -0.085 | -0.167 | -0.249 | -0.324 | -0.400 | |
| metro | TOD | 586 | 26.6 | -0.173 | -0.344 | -0.512 | -0.679 | -0.843 | |
| non_metro | Employment | 10841 | 52.5 | -0.128 | -0.250 | -0.371 | -0.497 | -0.622 | |
| non_metro | Low Density/Rural | 36143 | 59.8 | -0.026 | -0.052 | -0.078 | -0.104 | -0.128 | |
| non_metro | Mixed | 98 | 43.1 | -0.011 | -0.459 | -0.898 | -1.329 | -1.753 | |
| non_metro | Mixed High | 4 | 21.3 | -0.872 | -1.687 | -2.446 | -3.152 | -3.806 | |
| non_metro | Residential | 11466 | 52.3 | -0.200 | -0.400 | -0.594 | -0.791 | -0.987 | |
| non_metro | TOD | 5 | 20.1 | -0.585 | -1.151 | -1.699 | -2.229 | -2.742 | |
Household Income Sensitivity
As expected, household income has positive elasticities to AADVMT. The elasticities to income is most stable across segments.
| Δ AADVMT wrt Δ income | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | AADVMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 46.7 | 0.686 | 1.318 | 1.900 | 2.450 | 2.960 | ||
| non_metro | 58557 | 56.9 | 0.869 | 1.670 | 2.410 | 3.110 | 3.760 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 55.3 | 0.776 | 1.491 | 2.150 | 2.770 | 3.350 | |
| metro | 1k-5k | 42833 | 50.1 | 0.727 | 1.398 | 2.020 | 2.600 | 3.140 | |
| metro | 5k-10k | 19565 | 46.1 | 0.686 | 1.317 | 1.900 | 2.450 | 2.960 | |
| metro | >10k | 8588 | 33.4 | 0.524 | 1.010 | 1.460 | 1.880 | 2.280 | |
| non_metro | <1k | 44365 | 59.2 | 0.894 | 1.717 | 2.480 | 3.190 | 3.860 | |
| non_metro | 1k-5k | 12420 | 50.5 | 0.802 | 1.542 | 2.230 | 2.870 | 3.470 | |
| non_metro | 5k-10k | 1536 | 45.7 | 0.746 | 1.434 | 2.070 | 2.670 | 3.230 | |
| non_metro | >10k | 236 | 32.2 | 0.595 | 1.145 | 1.660 | 2.130 | 2.440 | |
| Income | |||||||||
| metro | <$40k | 28933 | 26.2 | 0.466 | 0.896 | 1.290 | 1.670 | 2.020 | |
| metro | $40k-$80k | 24666 | 47.2 | 0.709 | 1.362 | 1.970 | 2.530 | 3.060 | |
| metro | >$80k | 25780 | 65.6 | 0.878 | 1.686 | 2.440 | 3.130 | 3.790 | |
| non_metro | <$40k | 25270 | 37.2 | 0.661 | 1.272 | 1.840 | 2.370 | 2.860 | |
| non_metro | $40k-$80k | 19280 | 64.7 | 0.961 | 1.847 | 2.670 | 3.430 | 4.150 | |
| non_metro | >$80k | 14007 | 81.8 | 1.118 | 2.146 | 3.100 | 3.990 | 4.820 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 47.3 | 0.696 | 1.338 | 1.930 | 2.490 | 3.010 | |
| metro | Low Density/Rural | 8122 | 56.3 | 0.788 | 1.513 | 2.190 | 2.810 | 3.400 | |
| metro | Mixed | 4441 | 41.6 | 0.639 | 1.227 | 1.770 | 2.280 | 2.760 | |
| metro | Mixed High | 1074 | 31.6 | 0.455 | 0.937 | 1.350 | 1.770 | 2.160 | |
| metro | Residential | 50684 | 46.6 | 0.686 | 1.318 | 1.900 | 2.450 | 2.960 | |
| metro | TOD | 586 | 26.6 | 0.461 | 0.839 | 1.190 | 1.550 | 1.900 | |
| non_metro | Employment | 10841 | 52.5 | 0.821 | 1.577 | 2.280 | 2.930 | 3.540 | |
| non_metro | Low Density/Rural | 36143 | 59.8 | 0.899 | 1.728 | 2.500 | 3.210 | 3.890 | |
| non_metro | Mixed | 98 | 43.1 | 0.712 | 1.368 | 1.980 | 2.550 | 3.080 | |
| non_metro | Mixed High | 4 | 21.3 | 0.453 | 0.873 | 1.260 | 1.630 | 1.970 | |
| non_metro | Residential | 11466 | 52.3 | 0.821 | 1.578 | 2.280 | 2.940 | 3.550 | |
| non_metro | TOD | 5 | 20.1 | 0.435 | 0.837 | 1.210 | 1.560 | 1.890 | |
Freeway Supply Sensitivity
Also corraborating previous research and Brian’s finding, the elasticities to freeway supply is positive but small, mostly because most places in the US already have good mobility by vehicle, additional freeways lead households to drive slightly more miles.
| Δ AADVMT wrt Δ FwyLaneMiPC | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | AADVMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 46.7 | 0.169 | 0.339 | 0.508 | 0.678 | 0.848 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 55.3 | 0.224 | 0.448 | 0.673 | 0.898 | 1.125 | |
| metro | 1k-5k | 42833 | 50.1 | 0.185 | 0.370 | 0.556 | 0.742 | 0.929 | |
| metro | 5k-10k | 19565 | 46.1 | 0.160 | 0.320 | 0.481 | 0.642 | 0.803 | |
| metro | >10k | 8588 | 33.4 | 0.117 | 0.234 | 0.342 | 0.456 | 0.569 | |
| Income | |||||||||
| metro | <$40k | 28933 | 26.2 | 0.115 | 0.230 | 0.343 | 0.457 | 0.572 | |
| metro | $40k-$80k | 24666 | 47.2 | 0.175 | 0.351 | 0.527 | 0.704 | 0.882 | |
| metro | >$80k | 25780 | 65.6 | 0.216 | 0.433 | 0.650 | 0.867 | 1.085 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 47.3 | 0.180 | 0.361 | 0.542 | 0.723 | 0.905 | |
| metro | Low Density/Rural | 8122 | 56.3 | 0.211 | 0.423 | 0.636 | 0.849 | 1.063 | |
| metro | Mixed | 4441 | 41.6 | 0.148 | 0.295 | 0.444 | 0.592 | 0.741 | |
| metro | Mixed High | 1074 | 31.6 | 0.115 | 0.230 | 0.312 | 0.428 | 0.510 | |
| metro | Residential | 50684 | 46.6 | 0.167 | 0.334 | 0.500 | 0.667 | 0.835 | |
| metro | TOD | 586 | 26.6 | 0.104 | 0.208 | 0.313 | 0.417 | 0.522 | |
Transit Supply Sensitivity
As expected, transit supply (transit revenue miles per captia) has negative elasticities to AADVMT. The elasticities are inline with Brian’s numbers. And elasticities are larger for dense areas and for TODs.
| Δ AADVMT wrt Δ TranRevMiPC | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | AADVMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 46.7 | -0.032 | -0.064 | -0.096 | -0.126 | -0.157 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 55.3 | -0.010 | -0.019 | -0.029 | -0.038 | -0.048 | |
| metro | 1k-5k | 42833 | 50.1 | -0.019 | -0.037 | -0.055 | -0.074 | -0.092 | |
| metro | 5k-10k | 19565 | 46.1 | -0.034 | -0.069 | -0.103 | -0.137 | -0.171 | |
| metro | >10k | 8588 | 33.4 | -0.078 | -0.160 | -0.240 | -0.308 | -0.384 | |
| Income | |||||||||
| metro | <$40k | 28933 | 26.2 | -0.024 | -0.049 | -0.075 | -0.095 | -0.119 | |
| metro | $40k-$80k | 24666 | 47.2 | -0.032 | -0.063 | -0.094 | -0.125 | -0.156 | |
| metro | >$80k | 25780 | 65.6 | -0.040 | -0.080 | -0.120 | -0.159 | -0.198 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 47.3 | -0.028 | -0.057 | -0.085 | -0.113 | -0.141 | |
| metro | Low Density/Rural | 8122 | 56.3 | -0.004 | -0.008 | -0.012 | -0.016 | -0.020 | |
| metro | Mixed | 4441 | 41.6 | -0.067 | -0.134 | -0.201 | -0.268 | -0.334 | |
| metro | Mixed High | 1074 | 31.6 | -0.060 | -0.120 | -0.180 | -0.207 | -0.266 | |
| metro | Residential | 50684 | 46.6 | -0.027 | -0.055 | -0.084 | -0.109 | -0.137 | |
| metro | TOD | 586 | 26.6 | -0.306 | -0.607 | -0.904 | -1.196 | -1.440 | |
Bike PMT
Model specification
The specification for the Bike PMT model has been documented in Task2. Here it is replicated for a quick reference.
## $metro
##
## Call:
## pscl::hurdle(formula = int_cround(td.miles.Bike) ~ AADVMT + Workers +
## LogIncome + LifeCycle + Age0to14 + CENSUS_R + FwyLaneMiPC +
## D4c + TranRevMiPC:D4c + D1B + D3apo | AADVMT + LogIncome + Workers +
## LifeCycle + Age0to14 + CENSUS_R + D1B + D2A_EPHHM + D5 + FwyLaneMiPC +
## TranRevMiPC, data = ., na.action = na.exclude, weights = .$hhwgt)
##
## Pearson residuals:
## Min 1Q Median 3Q Max
## -2.0657 -0.1517 -0.0863 -0.0483 79.6037
##
## Count model coefficients (truncated poisson with log link):
## Estimate Std. Error z value
## (Intercept) -0.567582 0.190773 -2.98
## AADVMT 0.001005 0.000193 5.21
## Workers 0.119271 0.013986 8.53
## LogIncome 0.214267 0.016025 13.37
## LifeCycleEmpty Nester -0.388335 0.043277 -8.97
## LifeCycleParents w/ children -0.572609 0.028037 -20.42
## LifeCycleSingle -0.349925 0.057189 -6.12
## Age0to14 -0.137315 0.014726 -9.32
## CENSUS_RNE -0.087857 0.047447 -1.85
## CENSUS_RS 0.244428 0.032260 7.58
## CENSUS_RW 0.192837 0.030930 6.23
## FwyLaneMiPC -258.392574 53.691204 -4.81
## D4c -0.001647 0.000328 -5.01
## D1B -0.004132 0.000780 -5.30
## D3apo 0.012828 0.001857 6.91
## D4c:TranRevMiPC 0.118659 0.012436 9.54
## Pr(>|z|)
## (Intercept) 0.0029 **
## AADVMT 0.000000186288460 ***
## Workers < 0.0000000000000002 ***
## LogIncome < 0.0000000000000002 ***
## LifeCycleEmpty Nester < 0.0000000000000002 ***
## LifeCycleParents w/ children < 0.0000000000000002 ***
## LifeCycleSingle 0.000000000943047 ***
## Age0to14 < 0.0000000000000002 ***
## CENSUS_RNE 0.0641 .
## CENSUS_RS 0.000000000000035 ***
## CENSUS_RW 0.000000000452638 ***
## FwyLaneMiPC 0.000001490031131 ***
## D4c 0.000000530624244 ***
## D1B 0.000000117941179 ***
## D3apo 0.000000000004923 ***
## D4c:TranRevMiPC < 0.0000000000000002 ***
## Zero hurdle model coefficients (binomial with logit link):
## Estimate Std. Error z value
## (Intercept) -4.835948 0.423101 -11.43
## AADVMT -0.003486 0.000705 -4.94
## LogIncome 0.118683 0.036610 3.24
## Workers 0.306376 0.035728 8.58
## LifeCycleEmpty Nester -0.388293 0.109641 -3.54
## LifeCycleParents w/ children 0.441986 0.074992 5.89
## LifeCycleSingle -1.077227 0.138810 -7.76
## Age0to14 0.403422 0.029113 13.86
## CENSUS_RNE -0.756390 0.101977 -7.42
## CENSUS_RS 0.030118 0.073829 0.41
## CENSUS_RW 0.129064 0.072211 1.79
## D1B -0.005335 0.002037 -2.62
## D2A_EPHHM 0.237004 0.115529 2.05
## D5 0.024587 0.005309 4.63
## FwyLaneMiPC -570.955364 123.482977 -4.62
## TranRevMiPC -6.956893 2.556269 -2.72
## Pr(>|z|)
## (Intercept) < 0.0000000000000002 ***
## AADVMT 0.0000007675404394 ***
## LogIncome 0.0012 **
## Workers < 0.0000000000000002 ***
## LifeCycleEmpty Nester 0.0004 ***
## LifeCycleParents w/ children 0.0000000037751540 ***
## LifeCycleSingle 0.0000000000000085 ***
## Age0to14 < 0.0000000000000002 ***
## CENSUS_RNE 0.0000000000001196 ***
## CENSUS_RS 0.6833
## CENSUS_RW 0.0739 .
## D1B 0.0088 **
## D2A_EPHHM 0.0402 *
## D5 0.0000036354658086 ***
## FwyLaneMiPC 0.0000037685009293 ***
## TranRevMiPC 0.0065 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Number of iterations in BFGS optimization: 63
## Log-likelihood: -1.36e+04 on 32 Df
##
## $non_metro
##
## Call:
## pscl::hurdle(formula = int_cround(td.miles.Bike) ~ AADVMT + HhSize +
## LogIncome + HhSize + LifeCycle + Age0to14 + Age65Plus + D1B +
## D3bpo4 | AADVMT + LogIncome + Workers + LifeCycle + Age0to14 +
## D1B + D2A_EPHHM + D3bpo4, data = ., na.action = na.exclude,
## weights = .$hhwgt)
##
## Pearson residuals:
## Min 1Q Median 3Q Max
## -1.9620 -0.1139 -0.0636 -0.0383 123.5628
##
## Count model coefficients (truncated poisson with log link):
## Estimate Std. Error z value
## (Intercept) -2.955180 0.256183 -11.54
## AADVMT 0.000184 0.000286 0.64
## HhSize 0.136237 0.014777 9.22
## LogIncome 0.422927 0.022449 18.84
## LifeCycleEmpty Nester -0.119489 0.046946 -2.55
## LifeCycleParents w/ children -0.757636 0.046207 -16.40
## LifeCycleSingle -0.031625 0.058096 -0.54
## Age0to14 -0.250897 0.022489 -11.16
## Age65Plus 0.275630 0.025804 10.68
## D1B 0.006037 0.005147 1.17
## D3bpo4 0.005983 0.000533 11.23
## Pr(>|z|)
## (Intercept) <0.0000000000000002 ***
## AADVMT 0.522
## HhSize <0.0000000000000002 ***
## LogIncome <0.0000000000000002 ***
## LifeCycleEmpty Nester 0.011 *
## LifeCycleParents w/ children <0.0000000000000002 ***
## LifeCycleSingle 0.586
## Age0to14 <0.0000000000000002 ***
## Age65Plus <0.0000000000000002 ***
## D1B 0.241
## D3bpo4 <0.0000000000000002 ***
## Zero hurdle model coefficients (binomial with logit link):
## Estimate Std. Error z value
## (Intercept) -7.76666 0.46747 -16.61
## AADVMT -0.00442 0.00070 -6.32
## LogIncome 0.29680 0.04278 6.94
## Workers 0.12920 0.04006 3.23
## LifeCycleEmpty Nester 0.44051 0.12665 3.48
## LifeCycleParents w/ children 1.28041 0.10364 12.35
## LifeCycleSingle 0.17250 0.14750 1.17
## Age0to14 0.37213 0.03147 11.82
## D1B 0.02047 0.00920 2.23
## D2A_EPHHM 0.21657 0.13350 1.62
## D3bpo4 0.00484 0.00119 4.06
## Pr(>|z|)
## (Intercept) < 0.0000000000000002 ***
## AADVMT 0.000000000268 ***
## LogIncome 0.000000000004 ***
## Workers 0.0013 **
## LifeCycleEmpty Nester 0.0005 ***
## LifeCycleParents w/ children < 0.0000000000000002 ***
## LifeCycleSingle 0.2422
## Age0to14 < 0.0000000000000002 ***
## D1B 0.0260 *
## D2A_EPHHM 0.1048
## D3bpo4 0.000048278581 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Number of iterations in BFGS optimization: 36
## Log-likelihood: -1.02e+04 on 22 DfPopulation Density (D1B) Sensitivity
The elasticity estimates of bike person miles traveled per household with respect to population density (D1B) is negative due to the negative D1B coefficient in the model specification. Alternative model specifications have been tested with other density variables (D1C - job density, D1D - activity density) and interactions with D2 variables, the negative coefficient has been persistent.
The elasticities are the largest for the densest (>10,000 person/sq mile) non-metro areas, with density increases 50%, the bike PMT more than doubled for households living in these areas.
| Δ BikePMT wrt Δ D1B | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | BikePMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 0.1810 | -0.002 | -0.003 | -0.005 | -0.006 | -0.008 | ||
| non_metro | 58557 | 0.1423 | 0.001 | 0.002 | 0.003 | 0.004 | 0.005 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 0.1516 | 0.000 | 0.000 | 0.000 | -0.001 | -0.001 | |
| metro | 1k-5k | 42833 | 0.1777 | -0.001 | -0.002 | -0.002 | -0.003 | -0.004 | |
| metro | 5k-10k | 19565 | 0.1940 | -0.002 | -0.004 | -0.006 | -0.008 | -0.009 | |
| metro | >10k | 8588 | 0.1810 | -0.005 | -0.010 | -0.014 | -0.019 | -0.023 | |
| non_metro | <1k | 44365 | 0.1259 | 0.000 | 0.000 | 0.000 | 0.001 | 0.001 | |
| non_metro | 1k-5k | 12420 | 0.1806 | 0.002 | 0.004 | 0.005 | 0.007 | 0.009 | |
| non_metro | 5k-10k | 1536 | 0.2714 | 0.007 | 0.015 | 0.022 | 0.030 | 0.038 | |
| non_metro | >10k | 236 | 0.5041 | 0.053 | 0.113 | 0.178 | 0.248 | 0.324 | |
| Income | |||||||||
| metro | <$40k | 28933 | 0.0885 | -0.001 | -0.002 | -0.003 | -0.003 | -0.004 | |
| metro | $40k-$80k | 24666 | 0.1604 | -0.001 | -0.003 | -0.004 | -0.005 | -0.007 | |
| metro | >$80k | 25780 | 0.2717 | -0.002 | -0.005 | -0.007 | -0.009 | -0.012 | |
| non_metro | <$40k | 25270 | 0.0828 | 0.001 | 0.001 | 0.002 | 0.003 | 0.004 | |
| non_metro | $40k-$80k | 19280 | 0.1513 | 0.001 | 0.002 | 0.002 | 0.003 | 0.004 | |
| non_metro | >$80k | 14007 | 0.2283 | 0.001 | 0.002 | 0.004 | 0.005 | 0.006 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 0.1728 | -0.001 | -0.002 | -0.003 | -0.003 | -0.004 | |
| metro | Low Density/Rural | 8122 | 0.1651 | 0.000 | -0.001 | -0.001 | -0.002 | -0.002 | |
| metro | Mixed | 4441 | 0.2034 | -0.002 | -0.004 | -0.006 | -0.008 | -0.010 | |
| metro | Mixed High | 1074 | 0.1979 | -0.003 | -0.007 | -0.010 | -0.013 | -0.016 | |
| metro | Residential | 50684 | 0.1776 | -0.002 | -0.003 | -0.005 | -0.006 | -0.008 | |
| metro | TOD | 586 | 0.5757 | -0.019 | -0.038 | -0.055 | -0.071 | -0.087 | |
| non_metro | Employment | 10841 | 0.1575 | 0.001 | 0.002 | 0.003 | 0.004 | 0.005 | |
| non_metro | Low Density/Rural | 36143 | 0.1250 | 0.000 | 0.001 | 0.001 | 0.001 | 0.002 | |
| non_metro | Mixed | 98 | 0.2354 | 0.010 | 0.021 | 0.032 | 0.046 | 0.060 | |
| non_metro | Mixed High | 4 | 0.3105 | 0.027 | 0.057 | 0.090 | 0.127 | 0.167 | |
| non_metro | Residential | 11466 | 0.1830 | 0.002 | 0.005 | 0.007 | 0.010 | 0.012 | |
| non_metro | TOD | 5 | 0.3615 | 0.018 | 0.037 | 0.057 | 0.079 | 0.102 | |
Household AADVMT Sensitivity
To capture the relationship between driving and usage of other modes, we include AADVMT in models of non-driving modes. Bike PMT consistenly has a negative elasticity to AADVMT with relatively little variations across segments.
| Δ BikePMT wrt Δ AADVMT | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | BikePMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 0.1810 | -0.003 | -0.006 | -0.008 | -0.011 | -0.014 | ||
| non_metro | 58557 | 0.1423 | -0.004 | -0.008 | -0.011 | -0.015 | -0.018 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 0.1516 | -0.003 | -0.005 | -0.008 | -0.011 | -0.013 | |
| metro | 1k-5k | 42833 | 0.1777 | -0.003 | -0.006 | -0.008 | -0.011 | -0.014 | |
| metro | 5k-10k | 19565 | 0.1940 | -0.003 | -0.006 | -0.009 | -0.012 | -0.014 | |
| metro | >10k | 8588 | 0.1810 | -0.002 | -0.005 | -0.007 | -0.009 | -0.011 | |
| non_metro | <1k | 44365 | 0.1259 | -0.004 | -0.007 | -0.011 | -0.014 | -0.017 | |
| non_metro | 1k-5k | 12420 | 0.1806 | -0.004 | -0.009 | -0.013 | -0.017 | -0.021 | |
| non_metro | 5k-10k | 1536 | 0.2714 | -0.006 | -0.013 | -0.019 | -0.024 | -0.030 | |
| non_metro | >10k | 236 | 0.5041 | -0.010 | -0.019 | -0.028 | -0.037 | -0.046 | |
| Income | |||||||||
| metro | <$40k | 28933 | 0.0885 | -0.001 | -0.002 | -0.003 | -0.004 | -0.005 | |
| metro | $40k-$80k | 24666 | 0.1604 | -0.002 | -0.005 | -0.007 | -0.009 | -0.011 | |
| metro | >$80k | 25780 | 0.2717 | -0.005 | -0.009 | -0.014 | -0.018 | -0.022 | |
| non_metro | <$40k | 25270 | 0.0828 | -0.002 | -0.003 | -0.004 | -0.006 | -0.007 | |
| non_metro | $40k-$80k | 19280 | 0.1513 | -0.004 | -0.008 | -0.012 | -0.016 | -0.019 | |
| non_metro | >$80k | 14007 | 0.2283 | -0.008 | -0.015 | -0.022 | -0.028 | -0.035 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 0.1728 | -0.003 | -0.005 | -0.008 | -0.011 | -0.013 | |
| metro | Low Density/Rural | 8122 | 0.1651 | -0.003 | -0.006 | -0.009 | -0.012 | -0.015 | |
| metro | Mixed | 4441 | 0.2034 | -0.003 | -0.005 | -0.008 | -0.011 | -0.013 | |
| metro | Mixed High | 1074 | 0.1979 | -0.002 | -0.005 | -0.007 | -0.010 | -0.012 | |
| metro | Residential | 50684 | 0.1776 | -0.003 | -0.006 | -0.008 | -0.011 | -0.013 | |
| metro | TOD | 586 | 0.5757 | -0.005 | -0.010 | -0.015 | -0.020 | -0.025 | |
| non_metro | Employment | 10841 | 0.1575 | -0.004 | -0.008 | -0.012 | -0.015 | -0.019 | |
| non_metro | Low Density/Rural | 36143 | 0.1250 | -0.004 | -0.007 | -0.011 | -0.014 | -0.017 | |
| non_metro | Mixed | 98 | 0.2354 | -0.006 | -0.011 | -0.016 | -0.021 | -0.026 | |
| non_metro | Mixed High | 4 | 0.3105 | -0.004 | -0.008 | -0.011 | -0.015 | -0.019 | |
| non_metro | Residential | 11466 | 0.1830 | -0.005 | -0.009 | -0.013 | -0.017 | -0.021 | |
| non_metro | TOD | 5 | 0.3615 | -0.003 | -0.006 | -0.009 | -0.012 | -0.015 | |
Household Income Sensitivity
Bike PMT has a positive elasticity to household income.
| Δ BikePMT wrt Δ income | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | BikePMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 0.1810 | 0.006 | 0.011 | 0.016 | 0.021 | 0.025 | ||
| non_metro | 58557 | 0.1423 | 0.010 | 0.019 | 0.028 | 0.037 | 0.046 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 0.1516 | 0.005 | 0.009 | 0.013 | 0.017 | 0.021 | |
| metro | 1k-5k | 42833 | 0.1777 | 0.006 | 0.011 | 0.016 | 0.020 | 0.025 | |
| metro | 5k-10k | 19565 | 0.1940 | 0.006 | 0.012 | 0.017 | 0.022 | 0.027 | |
| metro | >10k | 8588 | 0.1810 | 0.006 | 0.011 | 0.016 | 0.021 | 0.025 | |
| non_metro | <1k | 44365 | 0.1259 | 0.009 | 0.017 | 0.025 | 0.033 | 0.041 | |
| non_metro | 1k-5k | 12420 | 0.1806 | 0.012 | 0.024 | 0.036 | 0.048 | 0.059 | |
| non_metro | 5k-10k | 1536 | 0.2714 | 0.019 | 0.037 | 0.054 | 0.071 | 0.088 | |
| non_metro | >10k | 236 | 0.5041 | 0.034 | 0.066 | 0.098 | 0.129 | 0.159 | |
| Income | |||||||||
| metro | <$40k | 28933 | 0.0885 | 0.003 | 0.005 | 0.008 | 0.010 | 0.012 | |
| metro | $40k-$80k | 24666 | 0.1604 | 0.005 | 0.010 | 0.014 | 0.018 | 0.022 | |
| metro | >$80k | 25780 | 0.2717 | 0.009 | 0.017 | 0.024 | 0.031 | 0.038 | |
| non_metro | <$40k | 25270 | 0.0828 | 0.006 | 0.011 | 0.016 | 0.022 | 0.027 | |
| non_metro | $40k-$80k | 19280 | 0.1513 | 0.010 | 0.020 | 0.030 | 0.040 | 0.049 | |
| non_metro | >$80k | 14007 | 0.2283 | 0.016 | 0.031 | 0.046 | 0.060 | 0.075 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 0.1728 | 0.005 | 0.010 | 0.015 | 0.020 | 0.024 | |
| metro | Low Density/Rural | 8122 | 0.1651 | 0.005 | 0.010 | 0.015 | 0.019 | 0.023 | |
| metro | Mixed | 4441 | 0.2034 | 0.006 | 0.012 | 0.018 | 0.023 | 0.028 | |
| metro | Mixed High | 1074 | 0.1979 | 0.006 | 0.012 | 0.017 | 0.023 | 0.028 | |
| metro | Residential | 50684 | 0.1776 | 0.006 | 0.011 | 0.016 | 0.020 | 0.025 | |
| metro | TOD | 586 | 0.5757 | 0.018 | 0.035 | 0.051 | 0.067 | 0.081 | |
| non_metro | Employment | 10841 | 0.1575 | 0.011 | 0.021 | 0.031 | 0.041 | 0.051 | |
| non_metro | Low Density/Rural | 36143 | 0.1250 | 0.009 | 0.017 | 0.025 | 0.033 | 0.041 | |
| non_metro | Mixed | 98 | 0.2354 | 0.016 | 0.032 | 0.048 | 0.063 | 0.078 | |
| non_metro | Mixed High | 4 | 0.3105 | 0.021 | 0.042 | 0.063 | 0.083 | 0.102 | |
| non_metro | Residential | 11466 | 0.1830 | 0.013 | 0.025 | 0.037 | 0.048 | 0.060 | |
| non_metro | TOD | 5 | 0.3615 | 0.025 | 0.050 | 0.074 | 0.098 | 0.121 | |
Freeway Supply Sensitivity
| Δ BikePMT wrt Δ FwyLaneMiPC | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | BikePMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 0.1810 | -0.008 | -0.016 | -0.023 | -0.030 | -0.036 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 0.1516 | -0.007 | -0.014 | -0.021 | -0.027 | -0.033 | |
| metro | 1k-5k | 42833 | 0.1777 | -0.008 | -0.016 | -0.023 | -0.030 | -0.036 | |
| metro | 5k-10k | 19565 | 0.1940 | -0.008 | -0.016 | -0.024 | -0.031 | -0.038 | |
| metro | >10k | 8588 | 0.1810 | -0.008 | -0.015 | -0.022 | -0.028 | -0.035 | |
| Income | |||||||||
| metro | <$40k | 28933 | 0.0885 | -0.004 | -0.007 | -0.011 | -0.014 | -0.017 | |
| metro | $40k-$80k | 24666 | 0.1604 | -0.007 | -0.014 | -0.020 | -0.026 | -0.032 | |
| metro | >$80k | 25780 | 0.2717 | -0.012 | -0.024 | -0.035 | -0.045 | -0.055 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 0.1728 | -0.008 | -0.015 | -0.022 | -0.029 | -0.036 | |
| metro | Low Density/Rural | 8122 | 0.1651 | -0.008 | -0.015 | -0.022 | -0.028 | -0.034 | |
| metro | Mixed | 4441 | 0.2034 | -0.009 | -0.017 | -0.025 | -0.033 | -0.040 | |
| metro | Mixed High | 1074 | 0.1979 | -0.008 | -0.016 | -0.024 | -0.031 | -0.038 | |
| metro | Residential | 50684 | 0.1776 | -0.008 | -0.015 | -0.022 | -0.029 | -0.036 | |
| metro | TOD | 586 | 0.5757 | -0.024 | -0.047 | -0.069 | -0.090 | -0.110 | |
Transit Supply Sensitivity
| Δ BikePMT wrt Δ TranRevMiPC | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | BikePMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 0.1810 | 0.001 | 0.003 | 0.006 | 0.013 | 0.023 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 0.1516 | -0.001 | -0.002 | -0.003 | -0.004 | -0.005 | |
| metro | 1k-5k | 42833 | 0.1777 | -0.001 | -0.001 | -0.002 | -0.001 | -0.001 | |
| metro | 5k-10k | 19565 | 0.1940 | -0.001 | -0.001 | -0.001 | -0.001 | -0.002 | |
| metro | >10k | 8588 | 0.1810 | 0.012 | 0.030 | 0.058 | 0.103 | 0.177 | |
| Income | |||||||||
| metro | <$40k | 28933 | 0.0885 | 0.000 | 0.001 | 0.002 | 0.003 | 0.006 | |
| metro | $40k-$80k | 24666 | 0.1604 | 0.000 | 0.000 | 0.000 | 0.000 | 0.001 | |
| metro | >$80k | 25780 | 0.2717 | 0.003 | 0.007 | 0.016 | 0.030 | 0.054 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 0.1728 | -0.001 | -0.001 | -0.002 | -0.003 | -0.003 | |
| metro | Low Density/Rural | 8122 | 0.1651 | -0.001 | -0.003 | -0.004 | -0.006 | -0.007 | |
| metro | Mixed | 4441 | 0.2034 | 0.001 | 0.003 | 0.005 | 0.007 | 0.010 | |
| metro | Mixed High | 1074 | 0.1979 | 0.001 | 0.001 | 0.002 | 0.002 | 0.003 | |
| metro | Residential | 50684 | 0.1776 | 0.000 | -0.001 | -0.001 | -0.001 | 0.000 | |
| metro | TOD | 586 | 0.5757 | 0.174 | 0.447 | 0.883 | 1.597 | 2.783 | |
Transit PMT
Model specification
The specification for the Transit PMT model has been documented in Task2. Here it is replicated for a quick reference.
## $metro
##
## Call:
## pscl::hurdle(formula = int_cround(td.miles.Transit) ~ AADVMT + Workers +
## LogIncome + VehPerDriver + LifeCycle + Age0to14 + CENSUS_R +
## D1B + D2A_EPHHM + FwyLaneMiPC + TranRevMiPC + D4c + D5 + D3bpo4 |
## AADVMT + Workers + LogIncome + LifeCycle + Age0to14 + CENSUS_R +
## D1B:D2A_EPHHM + D3bpo4 + D5 + TranRevMiPC + TranRevMiPC:D4c,
## data = ., na.action = na.exclude, weights = .$hhwgt)
##
## Pearson residuals:
## Min 1Q Median 3Q Max
## -6.9662 -0.2432 -0.1227 -0.0611 120.9725
##
## Count model coefficients (truncated poisson with log link):
## Estimate Std. Error z value
## (Intercept) 1.4484295 0.0503290 28.78
## AADVMT 0.0009294 0.0000859 10.81
## Workers 0.0389454 0.0043707 8.91
## LogIncome 0.1482091 0.0044379 33.40
## VehPerDriver -0.1551878 0.0103344 -15.02
## LifeCycleEmpty Nester -0.1049879 0.0147795 -7.10
## LifeCycleParents w/ children -0.1528919 0.0092108 -16.60
## LifeCycleSingle -0.2180277 0.0172985 -12.60
## Age0to14 -0.0306390 0.0040321 -7.60
## CENSUS_RNE 0.0874998 0.0103880 8.42
## CENSUS_RS 0.1206543 0.0098923 12.20
## CENSUS_RW 0.0208724 0.0102187 2.04
## D1B 0.0015670 0.0000901 17.40
## D2A_EPHHM 0.0975817 0.0148810 6.56
## FwyLaneMiPC -428.9118658 17.3814664 -24.68
## TranRevMiPC 4.3409353 0.2850631 15.23
## D4c 0.0007678 0.0000296 25.98
## D5 -0.0186008 0.0005979 -31.11
## D3bpo4 -0.0013562 0.0001002 -13.54
## Pr(>|z|)
## (Intercept) < 0.0000000000000002 ***
## AADVMT < 0.0000000000000002 ***
## Workers < 0.0000000000000002 ***
## LogIncome < 0.0000000000000002 ***
## VehPerDriver < 0.0000000000000002 ***
## LifeCycleEmpty Nester 0.00000000000122 ***
## LifeCycleParents w/ children < 0.0000000000000002 ***
## LifeCycleSingle < 0.0000000000000002 ***
## Age0to14 0.00000000000003 ***
## CENSUS_RNE < 0.0000000000000002 ***
## CENSUS_RS < 0.0000000000000002 ***
## CENSUS_RW 0.041 *
## D1B < 0.0000000000000002 ***
## D2A_EPHHM 0.00000000005473 ***
## FwyLaneMiPC < 0.0000000000000002 ***
## TranRevMiPC < 0.0000000000000002 ***
## D4c < 0.0000000000000002 ***
## D5 < 0.0000000000000002 ***
## D3bpo4 < 0.0000000000000002 ***
## Zero hurdle model coefficients (binomial with logit link):
## Estimate Std. Error z value
## (Intercept) -1.652793 0.214736 -7.70
## AADVMT -0.007268 0.000452 -16.08
## Workers 0.425714 0.021271 20.01
## LogIncome -0.174743 0.019514 -8.95
## LifeCycleEmpty Nester -0.600849 0.068775 -8.74
## LifeCycleParents w/ children 0.971841 0.044953 21.62
## LifeCycleSingle -0.755009 0.072051 -10.48
## Age0to14 0.411591 0.018318 22.47
## CENSUS_RNE -0.120143 0.049510 -2.43
## CENSUS_RS -0.007993 0.045211 -0.18
## CENSUS_RW -0.524872 0.045946 -11.42
## D3bpo4 0.000830 0.000478 1.74
## D5 0.023379 0.003364 6.95
## TranRevMiPC 26.341848 1.252679 21.03
## D1B:D2A_EPHHM 0.011361 0.001467 7.75
## TranRevMiPC:D4c 0.038861 0.004311 9.01
## Pr(>|z|)
## (Intercept) 0.0000000000000139 ***
## AADVMT < 0.0000000000000002 ***
## Workers < 0.0000000000000002 ***
## LogIncome < 0.0000000000000002 ***
## LifeCycleEmpty Nester < 0.0000000000000002 ***
## LifeCycleParents w/ children < 0.0000000000000002 ***
## LifeCycleSingle < 0.0000000000000002 ***
## Age0to14 < 0.0000000000000002 ***
## CENSUS_RNE 0.015 *
## CENSUS_RS 0.860
## CENSUS_RW < 0.0000000000000002 ***
## D3bpo4 0.083 .
## D5 0.0000000000036766 ***
## TranRevMiPC < 0.0000000000000002 ***
## D1B:D2A_EPHHM 0.0000000000000095 ***
## TranRevMiPC:D4c < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Number of iterations in BFGS optimization: 41
## Log-likelihood: -8.66e+04 on 35 Df
##
## $non_metro
##
## Call:
## pscl::hurdle(formula = int_cround(td.miles.Transit) ~ AADVMT + HhSize +
## LogIncome + VehPerDriver + LifeCycle + Age0to14 + Age65Plus +
## CENSUS_R + D1B + D1B:D2A_EPHHM + D3bmm4 | AADVMT + Workers +
## LogIncome + HhSize + Age0to14 + CENSUS_R + D3bmm4 + D1B + D1B:D2A_EPHHM,
## data = ., na.action = na.exclude, weights = .$hhwgt)
##
## Pearson residuals:
## Min 1Q Median 3Q Max
## -12.9124 -0.1695 -0.0914 -0.0531 225.8459
##
## Count model coefficients (truncated poisson with log link):
## Estimate Std. Error z value
## (Intercept) 1.7373360 0.0654082 26.56
## AADVMT 0.0006579 0.0000673 9.78
## HhSize 0.2273830 0.0034535 65.84
## LogIncome 0.1043087 0.0054599 19.10
## VehPerDriver 0.1937941 0.0069926 27.71
## LifeCycleEmpty Nester -0.2257924 0.0297747 -7.58
## LifeCycleParents w/ children -0.9396273 0.0213277 -44.06
## LifeCycleSingle 0.0432160 0.0413201 1.05
## Age0to14 -0.0558367 0.0046421 -12.03
## Age65Plus 0.0608966 0.0110467 5.51
## CENSUS_RNE -0.0499994 0.0119126 -4.20
## CENSUS_RS 0.0149593 0.0091435 1.64
## CENSUS_RW -0.2977069 0.0130972 -22.73
## D1B 0.0025450 0.0031367 0.81
## D3bmm4 -0.0017626 0.0011449 -1.54
## D1B:D2A_EPHHM -0.0846760 0.0071142 -11.90
## Pr(>|z|)
## (Intercept) < 0.0000000000000002 ***
## AADVMT < 0.0000000000000002 ***
## HhSize < 0.0000000000000002 ***
## LogIncome < 0.0000000000000002 ***
## VehPerDriver < 0.0000000000000002 ***
## LifeCycleEmpty Nester 0.000000000000034 ***
## LifeCycleParents w/ children < 0.0000000000000002 ***
## LifeCycleSingle 0.30
## Age0to14 < 0.0000000000000002 ***
## Age65Plus 0.000000035347943 ***
## CENSUS_RNE 0.000027024325131 ***
## CENSUS_RS 0.10
## CENSUS_RW < 0.0000000000000002 ***
## D1B 0.42
## D3bmm4 0.12
## D1B:D2A_EPHHM < 0.0000000000000002 ***
## Zero hurdle model coefficients (binomial with logit link):
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -5.000406 0.298377 -16.76 < 0.0000000000000002 ***
## AADVMT 0.001016 0.000358 2.84 0.00453 **
## Workers 0.127624 0.025287 5.05 0.00000044893608 ***
## LogIncome 0.052404 0.027742 1.89 0.05889 .
## HhSize 0.479549 0.017788 26.96 < 0.0000000000000002 ***
## Age0to14 0.553886 0.025537 21.69 < 0.0000000000000002 ***
## CENSUS_RNE 0.164151 0.062552 2.62 0.00868 **
## CENSUS_RS -0.180735 0.048410 -3.73 0.00019 ***
## CENSUS_RW -0.488396 0.066043 -7.40 0.00000000000014 ***
## D3bmm4 -0.002395 0.004701 -0.51 0.61045
## D1B -0.069422 0.016790 -4.13 0.00003555271303 ***
## D1B:D2A_EPHHM 0.025521 0.033336 0.77 0.44394
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Number of iterations in BFGS optimization: 28
## Log-likelihood: -5.67e+04 on 28 DfPopulation Density (D1B) Sensitivity
| Δ TransitPMT wrt Δ D1B | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | TransitPMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 1.3128 | 0.011 | 0.022 | 0.033 | 0.045 | 0.057 | ||
| non_metro | 58557 | 1.7076 | -0.013 | -0.025 | -0.037 | -0.049 | -0.060 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 1.1197 | 0.001 | 0.001 | 0.002 | 0.003 | 0.004 | |
| metro | 1k-5k | 42833 | 1.1651 | 0.003 | 0.007 | 0.010 | 0.014 | 0.017 | |
| metro | 5k-10k | 19565 | 1.2109 | 0.007 | 0.015 | 0.022 | 0.030 | 0.037 | |
| metro | >10k | 8588 | 2.1788 | 0.051 | 0.104 | 0.159 | 0.215 | 0.273 | |
| non_metro | <1k | 44365 | 1.8745 | -0.005 | -0.011 | -0.016 | -0.022 | -0.027 | |
| non_metro | 1k-5k | 12420 | 1.2397 | -0.034 | -0.067 | -0.099 | -0.130 | -0.160 | |
| non_metro | 5k-10k | 1536 | 0.7593 | -0.055 | -0.105 | -0.152 | -0.195 | -0.235 | |
| non_metro | >10k | 236 | 0.1749 | -0.026 | -0.048 | -0.067 | -0.083 | -0.096 | |
| Income | |||||||||
| metro | <$40k | 28933 | 0.8780 | 0.008 | 0.017 | 0.025 | 0.034 | 0.043 | |
| metro | $40k-$80k | 24666 | 1.1868 | 0.010 | 0.020 | 0.030 | 0.041 | 0.052 | |
| metro | >$80k | 25780 | 1.7633 | 0.014 | 0.028 | 0.042 | 0.057 | 0.072 | |
| non_metro | <$40k | 25270 | 1.0982 | -0.008 | -0.016 | -0.024 | -0.031 | -0.039 | |
| non_metro | $40k-$80k | 19280 | 1.8646 | -0.013 | -0.026 | -0.039 | -0.051 | -0.062 | |
| non_metro | >$80k | 14007 | 2.4970 | -0.020 | -0.039 | -0.057 | -0.076 | -0.093 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 1.3258 | 0.007 | 0.013 | 0.020 | 0.027 | 0.034 | |
| metro | Low Density/Rural | 8122 | 1.1310 | 0.001 | 0.003 | 0.004 | 0.005 | 0.007 | |
| metro | Mixed | 4441 | 1.3930 | 0.015 | 0.030 | 0.045 | 0.060 | 0.076 | |
| metro | Mixed High | 1074 | 2.0846 | 0.079 | 0.160 | 0.243 | 0.329 | 0.417 | |
| metro | Residential | 50684 | 1.2846 | 0.010 | 0.021 | 0.032 | 0.043 | 0.054 | |
| metro | TOD | 586 | 3.1406 | 0.078 | 0.158 | 0.240 | 0.323 | 0.408 | |
| non_metro | Employment | 10841 | 1.5302 | -0.019 | -0.036 | -0.054 | -0.071 | -0.087 | |
| non_metro | Low Density/Rural | 36143 | 1.8769 | -0.006 | -0.012 | -0.017 | -0.023 | -0.029 | |
| non_metro | Mixed | 98 | 0.6074 | -0.027 | -0.053 | -0.076 | -0.098 | -0.119 | |
| non_metro | Mixed High | 4 | 0.0871 | -0.005 | -0.009 | -0.014 | -0.017 | -0.021 | |
| non_metro | Residential | 11466 | 1.3404 | -0.029 | -0.058 | -0.085 | -0.111 | -0.136 | |
| non_metro | TOD | 5 | 0.1409 | -0.010 | -0.018 | -0.026 | -0.034 | -0.040 | |
Household AADVMT Sensitivity
| Δ TransitPMT wrt Δ AADVMT | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | TransitPMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 1.3128 | -0.040 | -0.079 | -0.116 | -0.152 | -0.186 | ||
| non_metro | 58557 | 1.7076 | 0.024 | 0.048 | 0.072 | 0.097 | 0.123 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 1.1197 | -0.043 | -0.084 | -0.124 | -0.161 | -0.197 | |
| metro | 1k-5k | 42833 | 1.1651 | -0.040 | -0.078 | -0.114 | -0.150 | -0.184 | |
| metro | 5k-10k | 19565 | 1.2109 | -0.038 | -0.075 | -0.110 | -0.144 | -0.177 | |
| metro | >10k | 8588 | 2.1788 | -0.044 | -0.087 | -0.129 | -0.169 | -0.209 | |
| non_metro | <1k | 44365 | 1.8745 | 0.026 | 0.053 | 0.081 | 0.109 | 0.138 | |
| non_metro | 1k-5k | 12420 | 1.2397 | 0.015 | 0.031 | 0.046 | 0.062 | 0.078 | |
| non_metro | 5k-10k | 1536 | 0.7593 | 0.010 | 0.019 | 0.029 | 0.040 | 0.050 | |
| non_metro | >10k | 236 | 0.1749 | 0.002 | 0.004 | 0.005 | 0.007 | 0.009 | |
| Income | |||||||||
| metro | <$40k | 28933 | 0.8780 | -0.018 | -0.036 | -0.054 | -0.071 | -0.087 | |
| metro | $40k-$80k | 24666 | 1.1868 | -0.035 | -0.069 | -0.101 | -0.132 | -0.163 | |
| metro | >$80k | 25780 | 1.7633 | -0.061 | -0.120 | -0.177 | -0.232 | -0.284 | |
| non_metro | <$40k | 25270 | 1.0982 | 0.012 | 0.023 | 0.035 | 0.048 | 0.060 | |
| non_metro | $40k-$80k | 19280 | 1.8646 | 0.026 | 0.052 | 0.079 | 0.106 | 0.133 | |
| non_metro | >$80k | 14007 | 2.4970 | 0.040 | 0.082 | 0.124 | 0.167 | 0.211 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 1.3258 | -0.042 | -0.082 | -0.121 | -0.159 | -0.195 | |
| metro | Low Density/Rural | 8122 | 1.1310 | -0.044 | -0.087 | -0.127 | -0.166 | -0.203 | |
| metro | Mixed | 4441 | 1.3930 | -0.037 | -0.073 | -0.107 | -0.141 | -0.173 | |
| metro | Mixed High | 1074 | 2.0846 | -0.034 | -0.067 | -0.100 | -0.131 | -0.162 | |
| metro | Residential | 50684 | 1.2846 | -0.039 | -0.077 | -0.114 | -0.149 | -0.183 | |
| metro | TOD | 586 | 3.1406 | -0.049 | -0.097 | -0.145 | -0.191 | -0.237 | |
| non_metro | Employment | 10841 | 1.5302 | 0.020 | 0.040 | 0.061 | 0.082 | 0.104 | |
| non_metro | Low Density/Rural | 36143 | 1.8769 | 0.027 | 0.054 | 0.082 | 0.111 | 0.140 | |
| non_metro | Mixed | 98 | 0.6074 | 0.010 | 0.020 | 0.030 | 0.040 | 0.050 | |
| non_metro | Mixed High | 4 | 0.0871 | 0.001 | 0.002 | 0.003 | 0.003 | 0.004 | |
| non_metro | Residential | 11466 | 1.3404 | 0.017 | 0.033 | 0.051 | 0.068 | 0.086 | |
| non_metro | TOD | 5 | 0.1409 | 0.001 | 0.001 | 0.002 | 0.003 | 0.004 | |
Household Income Sensitivity
| Δ TransitPMT wrt Δ income | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | TransitPMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 1.3128 | 0.001 | 0.001 | 0.002 | 0.002 | 0.003 | ||
| non_metro | 58557 | 1.7076 | 0.024 | 0.046 | 0.066 | 0.086 | 0.104 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 1.1197 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | |
| metro | 1k-5k | 42833 | 1.1651 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | |
| metro | 5k-10k | 19565 | 1.2109 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | |
| metro | >10k | 8588 | 2.1788 | 0.005 | 0.009 | 0.013 | 0.017 | 0.020 | |
| non_metro | <1k | 44365 | 1.8745 | 0.026 | 0.050 | 0.073 | 0.094 | 0.114 | |
| non_metro | 1k-5k | 12420 | 1.2397 | 0.017 | 0.034 | 0.049 | 0.063 | 0.076 | |
| non_metro | 5k-10k | 1536 | 0.7593 | 0.011 | 0.020 | 0.029 | 0.038 | 0.046 | |
| non_metro | >10k | 236 | 0.1749 | 0.003 | 0.005 | 0.007 | 0.009 | 0.011 | |
| Income | |||||||||
| metro | <$40k | 28933 | 0.8780 | 0.000 | 0.001 | 0.001 | 0.001 | 0.001 | |
| metro | $40k-$80k | 24666 | 1.1868 | 0.000 | 0.001 | 0.001 | 0.001 | 0.002 | |
| metro | >$80k | 25780 | 1.7633 | 0.001 | 0.002 | 0.003 | 0.004 | 0.005 | |
| non_metro | <$40k | 25270 | 1.0982 | 0.015 | 0.030 | 0.043 | 0.056 | 0.067 | |
| non_metro | $40k-$80k | 19280 | 1.8646 | 0.026 | 0.050 | 0.073 | 0.094 | 0.113 | |
| non_metro | >$80k | 14007 | 2.4970 | 0.035 | 0.067 | 0.096 | 0.124 | 0.151 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 1.3258 | 0.000 | 0.001 | 0.001 | 0.001 | 0.002 | |
| metro | Low Density/Rural | 8122 | 1.1310 | 0.000 | 0.000 | 0.000 | 0.000 | -0.001 | |
| metro | Mixed | 4441 | 1.3930 | 0.001 | 0.002 | 0.002 | 0.003 | 0.003 | |
| metro | Mixed High | 1074 | 2.0846 | 0.008 | 0.015 | 0.021 | 0.027 | 0.032 | |
| metro | Residential | 50684 | 1.2846 | 0.001 | 0.001 | 0.002 | 0.002 | 0.002 | |
| metro | TOD | 586 | 3.1406 | 0.011 | 0.020 | 0.029 | 0.037 | 0.044 | |
| non_metro | Employment | 10841 | 1.5302 | 0.021 | 0.041 | 0.060 | 0.077 | 0.093 | |
| non_metro | Low Density/Rural | 36143 | 1.8769 | 0.026 | 0.050 | 0.073 | 0.094 | 0.114 | |
| non_metro | Mixed | 98 | 0.6074 | 0.009 | 0.017 | 0.025 | 0.032 | 0.039 | |
| non_metro | Mixed High | 4 | 0.0871 | 0.001 | 0.002 | 0.004 | 0.005 | 0.006 | |
| non_metro | Residential | 11466 | 1.3404 | 0.019 | 0.036 | 0.053 | 0.068 | 0.082 | |
| non_metro | TOD | 5 | 0.1409 | 0.002 | 0.004 | 0.006 | 0.008 | 0.009 | |
Freeway Supply Sensitivity
| Δ TransitPMT wrt Δ FwyLaneMiPC | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | TransitPMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 1.313 | -0.031 | -0.061 | -0.090 | -0.119 | -0.147 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 1.120 | -0.030 | -0.058 | -0.086 | -0.113 | -0.139 | |
| metro | 1k-5k | 42833 | 1.165 | -0.029 | -0.057 | -0.084 | -0.111 | -0.137 | |
| metro | 5k-10k | 19565 | 1.211 | -0.028 | -0.056 | -0.083 | -0.109 | -0.134 | |
| metro | >10k | 8588 | 2.179 | -0.045 | -0.089 | -0.132 | -0.174 | -0.216 | |
| Income | |||||||||
| metro | <$40k | 28933 | 0.878 | -0.021 | -0.041 | -0.061 | -0.080 | -0.098 | |
| metro | $40k-$80k | 24666 | 1.187 | -0.028 | -0.056 | -0.083 | -0.109 | -0.134 | |
| metro | >$80k | 25780 | 1.763 | -0.041 | -0.082 | -0.121 | -0.159 | -0.196 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 1.326 | -0.032 | -0.063 | -0.094 | -0.123 | -0.152 | |
| metro | Low Density/Rural | 8122 | 1.131 | -0.029 | -0.057 | -0.085 | -0.111 | -0.137 | |
| metro | Mixed | 4441 | 1.393 | -0.032 | -0.064 | -0.095 | -0.124 | -0.154 | |
| metro | Mixed High | 1074 | 2.085 | -0.042 | -0.084 | -0.124 | -0.164 | -0.202 | |
| metro | Residential | 50684 | 1.285 | -0.030 | -0.059 | -0.088 | -0.116 | -0.143 | |
| metro | TOD | 586 | 3.141 | -0.070 | -0.139 | -0.206 | -0.272 | -0.336 | |
Transit Supply Sensitivity
| Δ TransitPMT wrt Δ TranRevMiPC | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | TransitPMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 1.313 | 0.093 | 0.193 | 0.301 | 0.415 | 0.538 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 1.120 | 0.070 | 0.146 | 0.227 | 0.314 | 0.407 | |
| metro | 1k-5k | 42833 | 1.165 | 0.071 | 0.148 | 0.229 | 0.316 | 0.409 | |
| metro | 5k-10k | 19565 | 1.211 | 0.081 | 0.168 | 0.261 | 0.360 | 0.466 | |
| metro | >10k | 8588 | 2.179 | 0.212 | 0.441 | 0.688 | 0.952 | 1.235 | |
| Income | |||||||||
| metro | <$40k | 28933 | 0.878 | 0.057 | 0.118 | 0.183 | 0.253 | 0.327 | |
| metro | $40k-$80k | 24666 | 1.187 | 0.080 | 0.167 | 0.260 | 0.359 | 0.466 | |
| metro | >$80k | 25780 | 1.763 | 0.133 | 0.275 | 0.428 | 0.591 | 0.765 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 1.326 | 0.092 | 0.192 | 0.298 | 0.413 | 0.535 | |
| metro | Low Density/Rural | 8122 | 1.131 | 0.067 | 0.139 | 0.215 | 0.297 | 0.385 | |
| metro | Mixed | 4441 | 1.393 | 0.107 | 0.223 | 0.346 | 0.479 | 0.621 | |
| metro | Mixed High | 1074 | 2.085 | 0.163 | 0.337 | 0.521 | 0.716 | 0.922 | |
| metro | Residential | 50684 | 1.285 | 0.091 | 0.188 | 0.293 | 0.405 | 0.525 | |
| metro | TOD | 586 | 3.141 | 0.327 | 0.675 | 1.045 | 1.436 | 1.845 | |
Walk PMT
Model specification
The specification for the Bike PMT model has been documented in Task2. Here it is replicated for a quick reference.
## $metro
##
## Call:
## pscl::hurdle(formula = int_cround(td.miles.Walk) ~ AADVMT + Workers +
## LogIncome + VehPerDriver + LifeCycle + Age0to14 + CENSUS_R +
## D1B + D2A_EPHHM + FwyLaneMiPC + TranRevMiPC:D4c + D5 + D3apo |
## AADVMT + Workers + LogIncome + LifeCycle + Age0to14 + CENSUS_R +
## D1B:D2A_EPHHM + D3apo + D5 + TranRevMiPC, data = ., na.action = na.exclude,
## weights = .$hhwgt)
##
## Pearson residuals:
## Min 1Q Median 3Q Max
## -6.7636 -0.4283 -0.2215 0.0601 51.9962
##
## Count model coefficients (truncated poisson with log link):
## Estimate Std. Error z value
## (Intercept) -0.6488179 0.1105087 -5.87
## AADVMT 0.0014837 0.0001584 9.37
## Workers 0.0616318 0.0093248 6.61
## LogIncome 0.0780546 0.0091001 8.58
## VehPerDriver -0.1456886 0.0186177 -7.83
## LifeCycleEmpty Nester -0.0704215 0.0260876 -2.70
## LifeCycleParents w/ children 0.0161961 0.0191152 0.85
## LifeCycleSingle -0.4081860 0.0323055 -12.64
## Age0to14 0.1396879 0.0081045 17.24
## CENSUS_RNE 0.0562287 0.0217137 2.59
## CENSUS_RS -0.0583854 0.0223394 -2.61
## CENSUS_RW 0.0767683 0.0203759 3.77
## D1B 0.0002638 0.0002473 1.07
## D2A_EPHHM 0.0396523 0.0317386 1.25
## FwyLaneMiPC -48.8597671 30.9271211 -1.58
## D5 0.0065928 0.0008982 7.34
## D3apo 0.0141454 0.0010171 13.91
## TranRevMiPC:D4c -0.0000474 0.0021946 -0.02
## Pr(>|z|)
## (Intercept) 0.0000000043266560 ***
## AADVMT < 0.0000000000000002 ***
## Workers 0.0000000000385677 ***
## LogIncome < 0.0000000000000002 ***
## VehPerDriver 0.0000000000000051 ***
## LifeCycleEmpty Nester 0.00695 **
## LifeCycleParents w/ children 0.39683
## LifeCycleSingle < 0.0000000000000002 ***
## Age0to14 < 0.0000000000000002 ***
## CENSUS_RNE 0.00961 **
## CENSUS_RS 0.00896 **
## CENSUS_RW 0.00016 ***
## D1B 0.28614
## D2A_EPHHM 0.21154
## FwyLaneMiPC 0.11414
## D5 0.0000000000002136 ***
## D3apo < 0.0000000000000002 ***
## TranRevMiPC:D4c 0.98278
## Zero hurdle model coefficients (binomial with logit link):
## Estimate Std. Error z value
## (Intercept) -2.151050 0.146879 -14.65
## AADVMT -0.003390 0.000271 -12.49
## Workers 0.191723 0.014475 13.25
## LogIncome 0.048083 0.013202 3.64
## LifeCycleEmpty Nester -0.188841 0.034361 -5.50
## LifeCycleParents w/ children 0.397593 0.028188 14.11
## LifeCycleSingle -0.388532 0.035113 -11.07
## Age0to14 0.209363 0.015242 13.74
## CENSUS_RNE 0.053514 0.032478 1.65
## CENSUS_RS -0.060649 0.029152 -2.08
## CENSUS_RW 0.146182 0.028127 5.20
## D3apo 0.017173 0.001531 11.22
## D5 0.042253 0.004146 10.19
## TranRevMiPC 8.926065 0.829873 10.76
## D1B:D2A_EPHHM 0.014200 0.001602 8.86
## Pr(>|z|)
## (Intercept) < 0.0000000000000002 ***
## AADVMT < 0.0000000000000002 ***
## Workers < 0.0000000000000002 ***
## LogIncome 0.00027 ***
## LifeCycleEmpty Nester 0.000000039 ***
## LifeCycleParents w/ children < 0.0000000000000002 ***
## LifeCycleSingle < 0.0000000000000002 ***
## Age0to14 < 0.0000000000000002 ***
## CENSUS_RNE 0.09942 .
## CENSUS_RS 0.03749 *
## CENSUS_RW 0.000000202 ***
## D3apo < 0.0000000000000002 ***
## D5 < 0.0000000000000002 ***
## TranRevMiPC < 0.0000000000000002 ***
## D1B:D2A_EPHHM < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Number of iterations in BFGS optimization: 39
## Log-likelihood: -5.92e+04 on 33 Df
##
## $non_metro
##
## Call:
## pscl::hurdle(formula = int_cround(td.miles.Walk) ~ AADVMT + HhSize +
## LogIncome + VehPerDriver + LifeCycle + Age0to14 + Age65Plus +
## CENSUS_R + D1B + D1B:D2A_EPHHM + D3bpo4 | AADVMT + Workers +
## LogIncome + HhSize + Age0to14 + CENSUS_R + D3apo + D5, data = .,
## na.action = na.exclude, weights = .$hhwgt)
##
## Pearson residuals:
## Min 1Q Median 3Q Max
## -4.2520 -0.3054 -0.1698 -0.0793 34.9414
##
## Count model coefficients (truncated poisson with log link):
## Estimate Std. Error z value
## (Intercept) -1.6498788 0.1553895 -10.62
## AADVMT 0.0000155 0.0002101 0.07
## HhSize 0.0513759 0.0107195 4.79
## LogIncome 0.1793585 0.0138946 12.91
## VehPerDriver -0.0518063 0.0195835 -2.65
## LifeCycleEmpty Nester 0.1427695 0.0354230 4.03
## LifeCycleParents w/ children 0.0060147 0.0312679 0.19
## LifeCycleSingle 0.2164994 0.0397087 5.45
## Age0to14 0.0486270 0.0144491 3.37
## Age65Plus -0.1490085 0.0215246 -6.92
## CENSUS_RNE -0.0774248 0.0331592 -2.33
## CENSUS_RS -0.0501908 0.0255434 -1.96
## CENSUS_RW 0.1924132 0.0267240 7.20
## D1B -0.0141861 0.0056009 -2.53
## D3bpo4 -0.0008351 0.0005526 -1.51
## D1B:D2A_EPHHM 0.0355723 0.0099448 3.58
## Pr(>|z|)
## (Intercept) < 0.0000000000000002 ***
## AADVMT 0.94138
## HhSize 0.0000016449391 ***
## LogIncome < 0.0000000000000002 ***
## VehPerDriver 0.00816 **
## LifeCycleEmpty Nester 0.0000556786694 ***
## LifeCycleParents w/ children 0.84746
## LifeCycleSingle 0.0000000497533 ***
## Age0to14 0.00076 ***
## Age65Plus 0.0000000000044 ***
## CENSUS_RNE 0.01955 *
## CENSUS_RS 0.04942 *
## CENSUS_RW 0.0000000000006 ***
## D1B 0.01131 *
## D3bpo4 0.13074
## D1B:D2A_EPHHM 0.00035 ***
## Zero hurdle model coefficients (binomial with logit link):
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -3.559457 0.171599 -20.74 < 0.0000000000000002 ***
## AADVMT -0.000435 0.000246 -1.77 0.07696 .
## Workers 0.056298 0.015987 3.52 0.00043 ***
## LogIncome 0.158831 0.016306 9.74 < 0.0000000000000002 ***
## HhSize 0.147536 0.011770 12.54 < 0.0000000000000002 ***
## Age0to14 0.062440 0.020338 3.07 0.00214 **
## CENSUS_RNE 0.135686 0.038497 3.52 0.00042 ***
## CENSUS_RS -0.186997 0.029623 -6.31 0.00000000027463 ***
## CENSUS_RW 0.387029 0.034313 11.28 < 0.0000000000000002 ***
## D3apo 0.016134 0.002181 7.40 0.00000000000014 ***
## D5 -0.004164 0.024156 -0.17 0.86312
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Number of iterations in BFGS optimization: 29
## Log-likelihood: -3.69e+04 on 27 DfPopulation Density (D1B) Sensitivity
| Δ WalkPMT wrt Δ D1B | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | WalkPMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 0.578 | 0.003 | 0.005 | 0.008 | 0.010 | 0.013 | ||
| non_metro | 58557 | 0.378 | 0.000 | 0.000 | 0.000 | 0.000 | 0.001 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 0.414 | 0.000 | 0.000 | 0.001 | 0.001 | 0.001 | |
| metro | 1k-5k | 42833 | 0.502 | 0.001 | 0.002 | 0.003 | 0.005 | 0.006 | |
| metro | 5k-10k | 19565 | 0.626 | 0.003 | 0.005 | 0.008 | 0.011 | 0.014 | |
| metro | >10k | 8588 | 0.838 | 0.008 | 0.017 | 0.025 | 0.033 | 0.041 | |
| non_metro | <1k | 44365 | 0.360 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | |
| non_metro | 1k-5k | 12420 | 0.416 | 0.000 | 0.001 | 0.001 | 0.001 | 0.002 | |
| non_metro | 5k-10k | 1536 | 0.588 | 0.001 | 0.002 | 0.002 | 0.003 | 0.004 | |
| non_metro | >10k | 236 | 0.611 | 0.002 | 0.004 | 0.006 | 0.008 | 0.011 | |
| Income | |||||||||
| metro | <$40k | 28933 | 0.459 | 0.002 | 0.005 | 0.007 | 0.010 | 0.012 | |
| metro | $40k-$80k | 24666 | 0.551 | 0.002 | 0.005 | 0.007 | 0.010 | 0.012 | |
| metro | >$80k | 25780 | 0.694 | 0.003 | 0.005 | 0.008 | 0.010 | 0.013 | |
| non_metro | <$40k | 25270 | 0.286 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | |
| non_metro | $40k-$80k | 19280 | 0.399 | 0.000 | 0.000 | 0.000 | 0.001 | 0.001 | |
| non_metro | >$80k | 14007 | 0.503 | 0.000 | 0.000 | 0.000 | 0.001 | 0.001 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 0.525 | 0.002 | 0.004 | 0.007 | 0.009 | 0.011 | |
| metro | Low Density/Rural | 8122 | 0.453 | 0.000 | 0.001 | 0.001 | 0.001 | 0.002 | |
| metro | Mixed | 4441 | 0.641 | 0.005 | 0.009 | 0.014 | 0.019 | 0.023 | |
| metro | Mixed High | 1074 | 0.914 | 0.010 | 0.021 | 0.031 | 0.040 | 0.050 | |
| metro | Residential | 50684 | 0.585 | 0.002 | 0.005 | 0.007 | 0.010 | 0.012 | |
| metro | TOD | 586 | 1.119 | 0.012 | 0.024 | 0.035 | 0.047 | 0.058 | |
| non_metro | Employment | 10841 | 0.384 | 0.001 | 0.001 | 0.002 | 0.002 | 0.003 | |
| non_metro | Low Density/Rural | 36143 | 0.360 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | |
| non_metro | Mixed | 98 | 0.536 | 0.004 | 0.008 | 0.012 | 0.016 | 0.020 | |
| non_metro | Mixed High | 4 | 0.762 | 0.024 | 0.050 | 0.077 | 0.106 | 0.137 | |
| non_metro | Residential | 11466 | 0.429 | 0.000 | 0.000 | 0.000 | 0.000 | 0.001 | |
| non_metro | TOD | 5 | 0.656 | 0.009 | 0.019 | 0.029 | 0.039 | 0.050 | |
Household AADVMT Sensitivity
| Δ WalkPMT wrt Δ AADVMT | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | WalkPMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 0.578 | -0.004 | -0.009 | -0.013 | -0.018 | -0.022 | ||
| non_metro | 58557 | 0.378 | -0.001 | -0.002 | -0.003 | -0.004 | -0.004 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 0.414 | -0.005 | -0.010 | -0.014 | -0.019 | -0.023 | |
| metro | 1k-5k | 42833 | 0.502 | -0.005 | -0.009 | -0.014 | -0.018 | -0.023 | |
| metro | 5k-10k | 19565 | 0.626 | -0.005 | -0.009 | -0.014 | -0.018 | -0.023 | |
| metro | >10k | 8588 | 0.838 | -0.003 | -0.007 | -0.010 | -0.014 | -0.018 | |
| non_metro | <1k | 44365 | 0.360 | -0.001 | -0.002 | -0.003 | -0.004 | -0.004 | |
| non_metro | 1k-5k | 12420 | 0.416 | -0.001 | -0.002 | -0.003 | -0.003 | -0.004 | |
| non_metro | 5k-10k | 1536 | 0.588 | -0.001 | -0.002 | -0.003 | -0.004 | -0.005 | |
| non_metro | >10k | 236 | 0.611 | -0.001 | -0.002 | -0.003 | -0.003 | -0.004 | |
| Income | |||||||||
| metro | <$40k | 28933 | 0.459 | -0.003 | -0.005 | -0.008 | -0.011 | -0.013 | |
| metro | $40k-$80k | 24666 | 0.551 | -0.004 | -0.008 | -0.013 | -0.017 | -0.021 | |
| metro | >$80k | 25780 | 0.694 | -0.006 | -0.012 | -0.018 | -0.024 | -0.030 | |
| non_metro | <$40k | 25270 | 0.286 | 0.000 | -0.001 | -0.001 | -0.002 | -0.002 | |
| non_metro | $40k-$80k | 19280 | 0.399 | -0.001 | -0.002 | -0.003 | -0.004 | -0.005 | |
| non_metro | >$80k | 14007 | 0.503 | -0.001 | -0.003 | -0.004 | -0.006 | -0.007 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 0.525 | -0.004 | -0.009 | -0.013 | -0.017 | -0.022 | |
| metro | Low Density/Rural | 8122 | 0.453 | -0.005 | -0.010 | -0.015 | -0.020 | -0.025 | |
| metro | Mixed | 4441 | 0.641 | -0.004 | -0.008 | -0.012 | -0.016 | -0.020 | |
| metro | Mixed High | 1074 | 0.914 | -0.003 | -0.005 | -0.008 | -0.011 | -0.014 | |
| metro | Residential | 50684 | 0.585 | -0.004 | -0.009 | -0.013 | -0.018 | -0.022 | |
| metro | TOD | 586 | 1.119 | -0.001 | -0.002 | -0.004 | -0.005 | -0.007 | |
| non_metro | Employment | 10841 | 0.384 | -0.001 | -0.002 | -0.003 | -0.003 | -0.004 | |
| non_metro | Low Density/Rural | 36143 | 0.360 | -0.001 | -0.002 | -0.003 | -0.004 | -0.004 | |
| non_metro | Mixed | 98 | 0.536 | -0.001 | -0.002 | -0.003 | -0.005 | -0.006 | |
| non_metro | Mixed High | 4 | 0.762 | -0.001 | -0.001 | -0.002 | -0.003 | -0.004 | |
| non_metro | Residential | 11466 | 0.429 | -0.001 | -0.002 | -0.003 | -0.004 | -0.004 | |
| non_metro | TOD | 5 | 0.656 | 0.000 | -0.001 | -0.001 | -0.002 | -0.002 | |
Household Income Sensitivity
| Δ WalkPMT wrt Δ income | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | WalkPMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 0.578 | 0.004 | 0.008 | 0.012 | 0.016 | 0.019 | ||
| non_metro | 58557 | 0.378 | 0.008 | 0.016 | 0.023 | 0.030 | 0.036 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 0.414 | 0.003 | 0.006 | 0.009 | 0.011 | 0.013 | |
| metro | 1k-5k | 42833 | 0.502 | 0.004 | 0.007 | 0.011 | 0.014 | 0.017 | |
| metro | 5k-10k | 19565 | 0.626 | 0.005 | 0.009 | 0.013 | 0.017 | 0.021 | |
| metro | >10k | 8588 | 0.838 | 0.006 | 0.012 | 0.017 | 0.022 | 0.027 | |
| non_metro | <1k | 44365 | 0.360 | 0.008 | 0.015 | 0.022 | 0.029 | 0.035 | |
| non_metro | 1k-5k | 12420 | 0.416 | 0.009 | 0.017 | 0.025 | 0.033 | 0.040 | |
| non_metro | 5k-10k | 1536 | 0.588 | 0.012 | 0.024 | 0.035 | 0.045 | 0.055 | |
| non_metro | >10k | 236 | 0.611 | 0.013 | 0.025 | 0.037 | 0.048 | 0.058 | |
| Income | |||||||||
| metro | <$40k | 28933 | 0.459 | 0.003 | 0.006 | 0.009 | 0.012 | 0.014 | |
| metro | $40k-$80k | 24666 | 0.551 | 0.004 | 0.008 | 0.012 | 0.015 | 0.018 | |
| metro | >$80k | 25780 | 0.694 | 0.005 | 0.010 | 0.015 | 0.019 | 0.023 | |
| non_metro | <$40k | 25270 | 0.286 | 0.006 | 0.012 | 0.017 | 0.022 | 0.027 | |
| non_metro | $40k-$80k | 19280 | 0.399 | 0.009 | 0.017 | 0.024 | 0.032 | 0.038 | |
| non_metro | >$80k | 14007 | 0.503 | 0.011 | 0.022 | 0.032 | 0.041 | 0.050 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 0.525 | 0.004 | 0.008 | 0.011 | 0.014 | 0.017 | |
| metro | Low Density/Rural | 8122 | 0.453 | 0.003 | 0.007 | 0.010 | 0.012 | 0.015 | |
| metro | Mixed | 4441 | 0.641 | 0.005 | 0.009 | 0.013 | 0.017 | 0.021 | |
| metro | Mixed High | 1074 | 0.914 | 0.007 | 0.013 | 0.018 | 0.023 | 0.028 | |
| metro | Residential | 50684 | 0.585 | 0.004 | 0.009 | 0.012 | 0.016 | 0.019 | |
| metro | TOD | 586 | 1.119 | 0.008 | 0.015 | 0.022 | 0.028 | 0.034 | |
| non_metro | Employment | 10841 | 0.384 | 0.008 | 0.016 | 0.023 | 0.030 | 0.037 | |
| non_metro | Low Density/Rural | 36143 | 0.360 | 0.008 | 0.015 | 0.022 | 0.029 | 0.035 | |
| non_metro | Mixed | 98 | 0.536 | 0.012 | 0.023 | 0.034 | 0.044 | 0.053 | |
| non_metro | Mixed High | 4 | 0.762 | 0.019 | 0.037 | 0.054 | 0.070 | 0.085 | |
| non_metro | Residential | 11466 | 0.429 | 0.009 | 0.018 | 0.026 | 0.034 | 0.041 | |
| non_metro | TOD | 5 | 0.656 | 0.015 | 0.028 | 0.041 | 0.053 | 0.064 | |
Freeway Supply Sensitivity
| Δ WalkPMT wrt Δ FwyLaneMiPC | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | WalkPMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 0.578 | -0.001 | -0.002 | -0.003 | -0.004 | -0.005 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 0.414 | -0.001 | -0.002 | -0.002 | -0.003 | -0.004 | |
| metro | 1k-5k | 42833 | 0.502 | -0.001 | -0.002 | -0.003 | -0.003 | -0.004 | |
| metro | 5k-10k | 19565 | 0.626 | -0.001 | -0.002 | -0.003 | -0.004 | -0.005 | |
| metro | >10k | 8588 | 0.838 | -0.001 | -0.003 | -0.004 | -0.006 | -0.007 | |
| Income | |||||||||
| metro | <$40k | 28933 | 0.459 | -0.001 | -0.001 | -0.002 | -0.003 | -0.003 | |
| metro | $40k-$80k | 24666 | 0.551 | -0.001 | -0.002 | -0.003 | -0.004 | -0.005 | |
| metro | >$80k | 25780 | 0.694 | -0.001 | -0.003 | -0.004 | -0.005 | -0.006 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 0.525 | -0.001 | -0.002 | -0.003 | -0.004 | -0.005 | |
| metro | Low Density/Rural | 8122 | 0.453 | -0.001 | -0.002 | -0.002 | -0.003 | -0.004 | |
| metro | Mixed | 4441 | 0.641 | -0.001 | -0.002 | -0.003 | -0.004 | -0.005 | |
| metro | Mixed High | 1074 | 0.914 | -0.001 | -0.003 | -0.004 | -0.006 | -0.007 | |
| metro | Residential | 50684 | 0.585 | -0.001 | -0.002 | -0.003 | -0.004 | -0.005 | |
| metro | TOD | 586 | 1.119 | -0.002 | -0.004 | -0.006 | -0.008 | -0.010 | |
Transit Supply Sensitivity
| Δ WalkPMT wrt Δ TranRevMiPC | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| metro | Category | n | WalkPMT | +10% | +20% | +30% | +40% | +50% | |
| overall | |||||||||
| metro | 79379 | 0.578 | 0.007 | 0.014 | 0.021 | 0.027 | 0.034 | ||
| population_per_sqm | |||||||||
| metro | <1k | 8393 | 0.414 | 0.005 | 0.009 | 0.014 | 0.019 | 0.024 | |
| metro | 1k-5k | 42833 | 0.502 | 0.006 | 0.011 | 0.017 | 0.022 | 0.028 | |
| metro | 5k-10k | 19565 | 0.626 | 0.007 | 0.014 | 0.022 | 0.029 | 0.036 | |
| metro | >10k | 8588 | 0.838 | 0.012 | 0.024 | 0.035 | 0.047 | 0.059 | |
| Income | |||||||||
| metro | <$40k | 28933 | 0.459 | 0.005 | 0.011 | 0.016 | 0.022 | 0.027 | |
| metro | $40k-$80k | 24666 | 0.551 | 0.006 | 0.013 | 0.019 | 0.026 | 0.033 | |
| metro | >$80k | 25780 | 0.694 | 0.008 | 0.017 | 0.025 | 0.033 | 0.042 | |
| DevelopmentType | |||||||||
| metro | Employment | 14472 | 0.525 | 0.006 | 0.013 | 0.019 | 0.025 | 0.032 | |
| metro | Low Density/Rural | 8122 | 0.453 | 0.005 | 0.010 | 0.015 | 0.020 | 0.025 | |
| metro | Mixed | 4441 | 0.641 | 0.008 | 0.016 | 0.024 | 0.032 | 0.040 | |
| metro | Mixed High | 1074 | 0.914 | 0.009 | 0.018 | 0.028 | 0.037 | 0.046 | |
| metro | Residential | 50684 | 0.585 | 0.007 | 0.014 | 0.021 | 0.028 | 0.035 | |
| metro | TOD | 586 | 1.119 | 0.010 | 0.021 | 0.031 | 0.041 | 0.051 | |
Phase II
The models (AADVMT model, trip frequency model and person mile traveled model for bike, walk, and transit) are applied to RVMPO data using the visioneval framework with RSPM/VisionEval sythesized households and supplemental block group built environment level inputs. Below are the prediction outputs from the new models and RSPM, and the comparison with OHAS (weighted averages).
Predictions from the New Models
| Trips | PMT | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Category | n | AADVMT | BikeTrips | WalkTrips | TransitTrips | BikePMT | WalkPMT | TransitPMT | ||
| Overall | ||||||||||
| RVMPO | 74045 | 41.800 | 0.146 | 0.891 | 0.144 | 0.290 | 0.578 | 0.751 | ||
| DevelopmentType | ||||||||||
| Rural | 6476 | 49.200 | 0.158 | 0.754 | 0.134 | 0.294 | 0.513 | 0.816 | ||
| Urban | 67569 | 41.100 | 0.145 | 0.905 | 0.145 | 0.290 | 0.584 | 0.745 | ||
| Income | ||||||||||
| <$40k | 31432 | 25.100 | 0.124 | 0.762 | 0.180 | 0.167 | 0.482 | 0.676 | ||
| $40k-$80k | 18071 | 43.800 | 0.149 | 0.907 | 0.125 | 0.288 | 0.586 | 0.754 | ||
| >$80k | 24542 | 61.800 | 0.172 | 1.045 | 0.111 | 0.449 | 0.694 | 0.844 | ||
| Popuplation per Square Mile | ||||||||||
| <1k | 19126 | 42.300 | 0.143 | 0.710 | 0.133 | 0.249 | 0.476 | 0.739 | ||
| 1k-5k | 35477 | 42.300 | 0.144 | 0.898 | 0.141 | 0.294 | 0.579 | 0.753 | ||
| 5k-10k | 18211 | 40.700 | 0.151 | 1.071 | 0.157 | 0.327 | 0.682 | 0.757 | ||
| >10k | 1231 | 36.900 | 0.157 | 0.876 | 0.202 | 0.258 | 0.575 | 0.792 | ||
RSPM Predictions
| Trips | ||||||
|---|---|---|---|---|---|---|
| Category | n | DVMT | BikeTrips | WalkTrips | TransitTrips | |
| Overall | ||||||
| RVMPO | 74045 | 52.400 | 0.088 | 0.689 | 0.039 | |
| DevelopmentType | ||||||
| Rural | 6476 | 67.900 | 0.084 | 0.650 | 0.016 | |
| Urban | 67569 | 50.900 | 0.088 | 0.692 | 0.041 | |
| Income | ||||||
| <$40k | 31432 | 31.300 | 0.088 | 0.653 | 0.066 | |
| $40k-$80k | 18071 | 54.200 | 0.088 | 0.656 | 0.022 | |
| >$80k | 24542 | 78.100 | 0.088 | 0.757 | 0.017 | |
| Popuplation per Square Mile | ||||||
| <1k | 19126 | 57.200 | 0.083 | 0.543 | 0.020 | |
| 1k-5k | 35477 | 52.900 | 0.089 | 0.693 | 0.037 | |
| 5k-10k | 18211 | 47.400 | 0.092 | 0.818 | 0.058 | |
| >10k | 1231 | 37.900 | 0.097 | 0.897 | 0.110 | |
OHAS Observations
Those are the weighted average trip and person mile traveled per household by mode from the 2012 Oregon Household Activity Survey for RVMPO.
| Trips | PMT | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Category | n | DVMT | BikeTrips | WalkTrips | TransitTrips | BikePMT | WalkPMT | TransitPMT | ||
| Overall | ||||||||||
| RVMPO | 931 | 36.700 | 0.232 | 0.870 | 0.094 | 0.395 | 0.276 | 0.538 | ||
| DevelopmentType | ||||||||||
| Rural | 69 | 48.200 | 0.064 | 0.697 | 0.067 | 0.151 | 0.166 | 0.370 | ||
| Urban | 862 | 36.000 | 0.242 | 0.881 | 0.095 | 0.410 | 0.283 | 0.548 | ||
| Income | ||||||||||
| <$40k | 367 | 27.200 | 0.138 | 0.798 | 0.144 | 0.164 | 0.222 | 0.762 | ||
| $40k-$80k | 329 | 39.100 | 0.455 | 0.777 | 0.014 | 0.763 | 0.313 | 0.050 | ||
| >$80k | 235 | 53.900 | 0.072 | 1.186 | 0.114 | 0.300 | 0.336 | 0.845 | ||
| Popuplation per Square Mile | ||||||||||
| <1k | 226 | 40.800 | 0.079 | 0.510 | 0.037 | 0.270 | 0.135 | 0.013 | ||
| 1k-5k | 480 | 36.100 | 0.345 | 0.886 | 0.079 | 0.564 | 0.297 | 0.466 | ||
| 5k-10k | 212 | 34.200 | 0.175 | 1.058 | 0.160 | 0.237 | 0.322 | 1.074 | ||
| >10k | 13 | 43.500 | 0.000 | 1.408 | 0.076 | 0.000 | 0.528 | 0.055 | ||
Comparison of Spatial Distribution (Census Tract)
VMT
The spatial distribution of (weighted) average VMT from the observed OHAS data is very noisy due to small sample size per census tract (min=4, mean=25.861 and max=81). There is also different in what is predicted. The new VETravelDemand module predicts Annual Average Daily VMT (AADVMT) for households, the RSPM simulates AADVMT from household DVMT predictions, while OHAS reports household VMT on the day of survey. The RSPM predictions are higher than AADVMT predictions from VETravelDemand.
Bike Trips and PMT
Similar to VMT, the spatial distribution of (weighted) average bike trips and PMT from the observed OHAS data is very noisy. The VETravelDemand has larger predictions than RSPM for all tracts, even though the magnitude of the difference is small.
Walk Trips and PMT
The spatial distribution of (weighted) average walk trips and PMT from the observed OHAS data is again very noisy. The VETravelDemand has slightly larger predictions than RSPM for all tracts. The VETravelDemand successfully predicts tracts with higher observed walk trips and PMT, even though the magnitude differs.
Transit Trips and PMT
There is a large number of tracts without any observed transit trips or PMT from the observed OHAS data, which seems reasonable as not all tracts have transit service in Rogue Valley. However, neither the VETravelDemand or the RSPM are able to replicate this pattern as variables for transit supply are not used in the prediction. The VETravelDemand predicts slightly larger quantity than RSPM for all tracts with little variation across census tracts.
Phase III
All modules in the VETravelDemand R package have been tested to work with the develop branch of VisionEval using the RVMPO data. Automated testing (continuous integration) have been put in place to make sure the code/package passes all tests and is in working condition with the latest version of VisionEval all the time. And if anything breaks automated tests, authors of the packages will be notified through email (see also Task 3).