For each tour, the Metrolina model predicts the choice of forward and return time periods with the choices being Peak (PK) or Off-peak (OP). Therefore, every tour falls under one of four categories depending on the forward and return period, namely PK_PK, PK_OP, OP_PK, OP_OP. The previous version of the model reverts to a trip-based approach after destination choice. PK and OP matrices were generated by purpose on which the mode choice models were evaluated. A TOD model then subsequently splits the PK and OP mode choice output matrices by using PA/AP factors to generate subperiod (AM, MD, PM and NT) matrices.
The updated Metrolina model deviates slightly from this approach. Like in the previous model, the forward and return period (PK/OP) is predicted for each tour. However, the mode choice is also tour-based, and the time-of-day model is applied just before the creation of the OD matrices. Therefore, there is a need to generate 4 sets of matrices (AM, MD, PM and NT) from the tour level output.
This is done by analyzing the survey to apportion the appropriate combination of PK_PK, PK_OP, OP_PK and OP_OP tours into sub-periods. For example, the PK_PK combination has three possibilities (AM_AM, AM_PM and PM_PM). The survey was used to obtain percentages of tours in each subcategory by purpose. These are directly applied in the model.
The tables containing these factors are shown below.
| Work | School | University | Shop | Other | AtWork | |
|---|---|---|---|---|---|---|
| AM_AM | 21,450 | 43,915 | 1,073 | 12,444 | 162,307 | 4,376 |
| AM_PM | 245,819 | 117,975 | 11,933 | 14,554 | 103,305 | 919 |
| PM_PM | 5,490 | 3,523 | 139 | 47,762 | 144,099 | 3,304 |
| Total | 272,759 | 165,413 | 13,145 | 74,759 | 409,711 | 8,599 |
| Percentage Distribution | ||||||
| AM_AM | 7.9% | 26.5% | 8.2% | 16.6% | 39.6% | 50.9% |
| AM_PM | 90.1% | 71.3% | 90.8% | 19.5% | 25.2% | 10.7% |
| PM_PM | 2.0% | 2.1% | 1.1% | 63.9% | 35.2% | 38.4% |
| Work | School | University | Shop | Other | AtWork | |
|---|---|---|---|---|---|---|
| AM_MD | 50,499 | 58,609 | 10,349 | 43,509 | 135,633 | 2,785 |
| AM_NT | 99,474 | 13,508 | 5,368 | 13,297 | 39,825 | 36 |
| PM_NT | 19,378 | 4,182 | 4,959 | 52,959 | 193,032 | 564 |
| Total | 169,350 | 76,299 | 20,675 | 109,765 | 368,490 | 3,386 |
| Percentage Distribution | ||||||
| AM_MD | 29.8% | 76.58% | 50.1% | 39.6% | 36.8% | 82.3% |
| AM_NT | 58.7% | 17.7% | 26.0% | 12.1% | 10.8% | 1.1% |
| PM_NT | 11.4% | 5.5% | 24.0% | 48.2% | 52.4% | 16.7% |
| Work | School | University | Shop | Other | AtWork | |
|---|---|---|---|---|---|---|
| MD_PM | 32,206 | 3,243 | 1,002 | 62,524 | 155,120 | 5,407 |
| NT_AM | 7,567 | 1,866 | 568 | 2,653 | 15,894 | 72 |
| NT_PM | 76,713 | 13,621 | 133 | 5,241 | 28,077 | 0 |
| Total | 116,486 | 18,730 | 1,703 | 70,417 | 199,091 | 5,480 |
| Percentage Distribution | ||||||
| MD_PM | 27.6% | 17.3% | 58.8% | 88.8% | 77.9% | 98.7% |
| NT_AM | 6.5% | 10.0% | 33.3% | 3.8% | 8.0% | 1.3% |
| NT_PM | 65.9% | 72.7% | 7.8% | 7.4% | 14.1% | 0.0% |
| Work | School | University | Shop | Other | AtWork | |
|---|---|---|---|---|---|---|
| MD_MD | 11,955 | 6,686 | 2,167 | 156,742 | 310,301 | 57,697 |
| MD_NT | 45,843 | 788 | 2,958 | 17,405 | 53,755 | 32 |
| NT_MD | 22,337 | 4,046 | 425 | 751 | 10,608 | 34 |
| NT_NT | 53,916 | 3,380 | 4,681 | 48,629 | 187,114 | 1,950 |
| Total | 134,052 | 14,900 | 10,232 | 223,527 | 561,779 | 59,714 |
| Percentage Distribution | ||||||
| MD_MD | 8.9% | 44.9% | 21.2% | 70.1% | 55.2% | 96.6% |
| MD_NT | 34.2% | 5.3% | 28.9% | 7.8% | 9.6% | 0.1% |
| NT_MD | 16.7% | 27.2% | 4.2% | 0.3% | 1.9% | 0.1% |
| NT_NT | 40.2% | 22.7% | 45.7% | 21.8% | 33.3% | 3.3% |