Time of Day Modeling in
FSUTMS
Presented to
Time of Day Subcommittee
May 9, 2011
Background
► Currently
not a part of FSUTMS
► Identified as a top priority by Model Task Force
in 2008
► Essential in supporting MTF’s high-priority
activities
New Starts
Air Quality Analysis
Pricing studies
Transit Forecasting
Time of Day Modeling in FSUTMS
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Background
► TOD
research project divided into two phases
Phase I: Fixed TOD Factoring and Procedure
Development
Phase II: Development and implementation of
TOD peak spreading model.
Time of Day Modeling in FSUTMS
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Why Consider TOD Modeling in FSUTMS
► Characteristics
of travel
vary by time of day and
location
► Knowledge of temporal
distribution of travel
demand provides useful
insights for planning and
operations
► Daily models not
sensitive to time
dependent travel
behavior
Time of Day Modeling in FSUTMS
Source: FHWA, Our Nation’s Highway, 2010
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Why Consider TOD Modeling in FSUTMS
► Required
by FTA for New Starts Alternatives
Analysis
► Required by FHWA and EPA for Vehicle
Emissions Analysis
► Required for analysis of transportation policies
that have temporal sensitivity (e.g. Managed
Lanes, Pricing, Alternative Work Schedules)
Time of Day Modeling in FSUTMS
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Static Time of Day Model
► Fixed
TOD factors derived from local travel
patterns. (The common practice)
Relatively easy to implement
Assumes travel patterns will remain the same in
the future
Not sensitive to LOS changes
► Adequate
for regions where congestion growth
is limited or negligible
► Essential for transit modeling to reflect
changes in transit service and fares from peak
to off-peak periods
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Time of Day Choice Feedback Model
► Dynamic
model, predicts shifts in time of travel
► Can model “peak spreading” over time.
► Sensitive to trip purposes and changes in LOS
on specific routes.
► Useful in regions where peak period is greater
than two hours and growing.
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Approach for FSUTMS TOD Modeling
► Implement
TOD model after Trip Generation
► Static TOD model for base year scenario
 Fixed TOD factors developed from observed local data.
► TOD
Choice feedback model for future year
scenarios
 Incremental logit model form
 Feedback of TOD choice to Trip Distribution
 Fixed TOD factors for initial TOD stratification
► TOD
periods of 1 hour to several hours
duration
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The Existing Model Structure
Any Scenario Year
Trip Generation
(Daily)
Trip Distribution
(Daily)
Mode Choice
(Daily)
Trip Assignment:
(Highway – Daily;
Transit – PK/OP)
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Base Year
Future Year
Trip Generation
Trip Generation
Factor P’s & A’s by Fixed
TOD Factors
Factor P’s & A’s by Fixed
TOD Factors
Trip Distribution by TOD
Trip Distribution by TOD
Mode Choice by TOD
Mode Choice by TOD
Highway Assignment by TOD
Assignment by TOD
Skim Base Year LOS by TOD
Skim Future Year LOS by TOD
Transit Assignment
Apply TOD Choice (Peak Spreading)
Model by Trip Purpose
No
Yes
END
Time of Day Modeling in FSUTMS
Transit Assignment
Adjusted TOD Trips
and Updated TOD LOS
The Revised Model Structure (Draft)
Convergence?
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TOD Choice (Peak Spreading) Model
►
Incremental logit
model
► Driven by difference in
travel impedance
► Apply in future year
where significant
congestion growth is
expected
►
►
►
Requires all TOD periods to be modeled explicitly
Model applied for each trip purpose independently
Creates adjusted trip tables for iterative feedback through trip
distribution, mode choice and assignment
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Conclusion
► TOD
choice modeling in FSUTMS will provide:
 Improved understanding of temporal travel behavior
 Improved forecast of highway LOS by TOD
 Improved estimation of highway speeds for
modeling transit, resulting in improved transit
forecasts
► Logical
stepping stone to implementation in an
activity-based FSUTMS
 TOD choice more robust when implemented with
additional explanatory variables, such as family
structure, joint travel, income and mode constraints
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Questions?
Thank You!
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