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spreading model component that was used was trans- ferred from the Metropolitan Transportation Commis- sion (MTC) model. Some issues had to be addressed in transferring the model and expanding it for different trip purposes. The peak- spreading model has been updated based on the results of FHWA- sponsored research on integrating time- of- day models with activity- based mod- els. Due to limited resources, a traditional aggregate assignment was used for trip assignment rather than a microsimulation assignment. ⢠The model was developed for SFCTA. To maintain consistency with the regional model, the MTCâs regional trip- based model was used and integrated with the tour- based model for San Francisco County. This approach presents some limitations on the cross- county move- ment. Stated preferences surveys were used to collect data on crowding and reliability and the impacts of these two features on mode choice. Equilibrium measures of time were estimated for commuters and noncommuters to higher and lower levels of crowding and reliability. Although there were significant effects from these mea- sures, the results were not intuitive to the transit board- ing data available at the time. As a result, they were taken out of the model. ⢠The model validation process required significant resources. A variety of traditional data sets were used for validation purposes. Validation was conducted for each model component separately. Additional validation was conducted by comparing the model to the trip- based regional model for each model component. The compar- ison to the four- step model was conducted for both the base year and the forecast year. The comparison, which was conducted for San Francisco County residents, included all the input data, the assumptions, and the model output for the base year and the forecast year. Because of the limitations in the trip- based model, which produced only trips and not tours, the comparisons were made at the trip level. ⢠The trip generation comparison included examin- ing the trip rates per household for different trip pur- poses. The other, non- home- based trip categories were overestimated in the San Francisco tour- based model, while the work and school trips were underestimated. These differences appear to be the result of using estima- tions based on two different surveys, rather than the models. A comparison of the district- to- district trip table summary showed very little difference in the two mod- els. One of the noticeable, although not significant, dif- ferences was in the higher percentage of trips in the San Francisco CBD zone for the San Francisco tour model. It appears that this difference also results from the under- lying survey data set and not the models. ⢠The mode share components in both models were estimated based on the same data sets. The differences in mode share appear to be a by- product of calibrating the San Francisco tour model with transit boardings in San Francisco, which may overestimate from the original model. These differences resulted in a reduction in transit trips in the tour model compared with the regional model and a corresponding increase in driving alone and walking. This difference was a calibration issue more than a differ- ence in the models. Tour- based models and trip- based mod- els are both validated to observed data. The differences that were identified in the validation process related to dif- ferences in the underlying data sets, not the models. ⢠There are differences in the outputs from the two models for the forecast year. A comparison of the trip tables for 2030 highlights one of these differences. Most of the differences by districts are small. The San Fran- cisco tour model shows a larger increase in trips in the suburban district and a drop in trips in the intradown- town district. The MTC trip- based model shows more growth in trips to the downtown district and more growth in intradowntown trips. ⢠In terms of mode share, both models show an increase in drive- alone trips for 2030. The growth in sub- urban portions of the county, which do not have good transit access, may account for this increase in drive- alone trips. The MTC trip- based model shows a more significant drop in walk trips, while the San Francisco tour model has a more significant decline in walk- to- transit trips. In the San Francisco model, walking is inte- grated as part of many different types of tours that people make during a day. As a trip- based model, the MTC model does not have this feature. Increases in trip distances impact the number of walk trips. ⢠The San Francisco tour model has been used for a number of different applications. The model has been well received by technical personnel, policy makers, and other groups. The model has been used for both tradi- tional planning studies, as well as projects utilizing the tour- based features. A disaggregate equity analysis was conducted to examine possible unintended consequences of countywide improvements being considered in the 30- year plan. The analysis focused primarily on two factors: mobility, as measured by total travel time for a group or total transit travel time for a group, and accessibility, as measured by the total amount of employment that could be reached within 30 minutes of a zone or the total amount of retail that could be reached within 30 minutes of a zone. The different groups examined in the analysis were households with no automobile available, low- income households, female- headed households with chil- dren, and single- parent households. The no- automobile households and the low- income households received most of the benefits from the countywide plan because the improvements focused primarily on the transit sys- tem. Female- headed households with children received few benefits from the plan. It may be that these house- holds are not making trips by transit. 16 INNOVATIONS IN TRAVEL DEMAND MODELING, VOLUME 1
