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less than $25,000 income group, the value of time was $10.64 and the equivalent minutes for a $3.00 toll were 16.9. The value of time for a heavy- duty truck was $40.00 and the equivalent minutes for a $3.00 toll were 4.4. ⢠The impact of pricing on model componentsâ trip distribution, mode choice, time- of- day choice, and trip assignmentâ was examined. The trip distribution com- ponent incorporates generalized cost in minutes for travel time. The cost was converted to time based on the value of time by market segment. Four feedback loops are used to equilibrate congested times. The modal representation in the distribution are work trips based on log- sum or weighted average of times and costs by mode. Nonwork carpool and transit trips are distributed based on no- toll travel patterns. In mode choice, travel time and cost are considered separately by mode and trip purpose. Lower values of time were used in the final assignments. ⢠A logit time- of- day choice model was applied after mode choice to automobile trips. There are 32 time peri- ods. The time periods are in half- hour increments, except for the first and last periods. Variables include demo- graphics, trip characteristics, and delay. The model also includes costs measured in units of time and the use of a nonlinear shift variable within three larger time periods. ⢠The time periods included the morning peak, mid- day, the afternoon peak, evening, and night. The morn- ing peak includes 10 time periods in 30-minute increments from 5:00 a.m. to 10:00 a.m. The midday includes 10 time periods in 30-minute increments from 10:00 a.m. to 3:00 p.m. The afternoon peak includes 10 time periods in 30-minute increments from 3:00 p.m. to 8:00 p.m. The evening includes one 3-hour time period from 8:00 p.m. to 11:00 p.m. The night includes one 6- hour time period from 11:00 p.m. to 5:00 a.m. ⢠The model specification is a multinomial logit structure with 32 alternatives. The trip assignment uses four feedback loops to equilibrate congested times based on lower values of time. Final iteration is based on higher values of time by market segment. The iterative assign- ments are based on the five time periods. The objective of the toll optimization tool is throughput or revenue maximization with the constraints of achieving a target level of service. ⢠A number of conclusions emerged from the study. First, the use of values of time by market segment enables better evaluation of pricing scenarios. Second, time- of- day choice models can be estimated with 30+ time peri- ods with existing data. Third, models are sensitive to time and cost trade- offs, as well as demographic factors and bridge constraints. Fourth, calibration by mode, trip purpose, and direction, as well as for volumes, provides more behavioral understanding of results. ⢠A number of areas for additional research were identified. These areas include examining the lack of rep- resentation of modal options in distribution models and the lack of representation of reliability in evaluating travel choices. The inability of static- demand models to represent dynamic pricing options represents another area for further research. The study identified the need to evaluate fairness as an important factor in implementa- tion and to represent overall societal benefits for road pricing strategies. It was also noted that there was a need to represent safety as a performance measure and to bet- ter understand and communicate risk and uncertainty. Rachel Gossen, Oakland Metropolitan Transportation Commission, moderated this session. 49EMERGING MODELING CONSIDERATIONS
