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52 I N N O VAT I O N S I N T R AV E L D E M A N D M O D E L I N G , V O L U M E 1 and demographic characteristics, and changes in multi- model. The model has a temporal resolution of 1 hour modal transportation network characteristics. Other for the modeled period between 5 a.m. and 11 p.m. The assessments might examine the impact of pricing policies, time-of-day model is applied sequentially among tours, alternative work schedules, development patterns, transit with mandatory work, university, and school tours fare changes, and other policy measures. The impact of scheduled first. The model determines the departure time new technologies on travel might also be examined. of each tour and the duration of the activity associated Many of the current tour-based models use the tra- with the tour. The 190 departure and arrival time com- ditional zone-based spatial representation of a region binations can be applied with relatively few variables. and discrete time-of-day periods. Although this In the development of the time-of-day model, a dis- approach is expected to continue, activity-based models aggregate validation was achieved using the Home Inter- have the potential to provide a more continuous repre- view Survey (HIS) data records. The model results sentation of the spacetime domain. These models may compared favorably with the observed values from the also be better able to accommodate emerging behavioral HIS. The time-of-day model has not yet been fully vali- paradigms and concepts. dated against external data because MORPC does not Potential areas for further work and research have a sufficient number of traffic counts by peak hour include the development of guidelines for validation and or peak period. assessing activity-based travel demand models, as well as The model area is divided into 1,805 internal and guidelines for model comparisons. There is also a need 72 external zones covering three counties and portions for designing and conducting comprehensive experi- of four other counties. The validation process in 2000 ments for performing controlled comparisons of activity- focused on the entire model area and Licking County based travel model outputs and existing four-step model only. Examples of elements included in the validation outputs under a variety of scenarios and policies. were work trip distribution, volumes, and transit trips. The results from the MORPC model were compared to the 2000 Census Transportation Planning Package MODELING OF PEAK-HOUR SPREADING WITH A (CTPP). On a regionwide basis, the MORPC model esti- DISAGGREGATE TOUR-BASED MODEL mated 660,031 work tours compared to 630,550 CTPP records--a difference of 4.7%. A comparison of district- Rebekah Anderson and Robert Donnelly to-district work tours revealed similarities and differ- ences between the MORPC model and the CTPP. The Rebekah Anderson discussed the basic elements of the MORPC model estimate of all work trips to the central Mid-Ohio Regional Planning Commission (MORPC) business district (CBD) was within 1% of the CTPP, model and the validation process. More detailed infor- whereas work trips in the North Corridor to the CBD mation on the development of the MORPC is provided in were underrepresented by 5%. Regionally, the model other sessions. Volume 2 provides a paper on the topic.3 overrepresented trips to Ohio State University (OSU) by The following points were covered in her presentation. 3%, but OSU trips in the North Corridor were overre- ported by 27%. The MORPC model is a disaggregate tour-based The MORPC model was also validated against traf- model applied with the microsimulation of each individ- fic counts processed to represent directional average daily ual household, person, or tour. The model consists of traffic for 2000. The criteria used to examine the accuracy nine separate models that are linked and applied sequen- of the MORPC model validation included the percent tially. In order, these nine models are population synthe- VMT error, the percent VMT root-mean-square error, and sis, automobile ownership, daily activity pattern, joint the percent volume root-mean-square error by facility type tour generation, individual nonmandatory tour genera- and volume group. The highway assignment validation tion, tour destination choice, time-of-day choice, tour was geographically structured by rings, sectors, and per mode choice, and stops and trip mode choice. districts. The results of this assessment indicate that model The choice mode hierarchy produces a record for results are comparable to observed volumes. every household and every person in the household. The Additional data and research are needed related to time-of-day model is based on the "time windows" con- validating the time-of-day feature and other elements of cept, accounting for the use of a person's time budget the MORPC model for planning and policy analysis. over the day, with 16 hours available per person. It is a Additional data on hourly traffic counts and vehicle clas- hybrid discrete choice departure time and duration sification counts are needed for more extensive validation. 3See Anderson, R. S., and R. M. Donnelly. Modeling of Peak-Hour Spreading with a Disaggregate Tour-Based Model. Volume 2, pp. 161164. Thomas Rossi moderated this session.