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From Academia to Application:From Academia to Application:
Results from the Development of the Results from the Development of the First Accessibility-Based ModelFirst Accessibility-Based Model
From Academia to Application:From Academia to Application:
Results from the Development of the Results from the Development of the First Accessibility-Based ModelFirst Accessibility-Based Model
Mike Conger, P.E.Mike Conger, P.E.Knoxville Regional Transportation Planning OrganizationKnoxville Regional Transportation Planning Organization
Vince Bernardin, Jr., Ph.D.Vince Bernardin, Jr., Ph.D.Bernardin, Lochmueller & Associates, Inc.Bernardin, Lochmueller & Associates, Inc.
Mike Conger, P.E.Mike Conger, P.E.Knoxville Regional Transportation Planning OrganizationKnoxville Regional Transportation Planning Organization
Vince Bernardin, Jr., Ph.D.Vince Bernardin, Jr., Ph.D.Bernardin, Lochmueller & Associates, Inc.Bernardin, Lochmueller & Associates, Inc.
Background & Motivation Overview of Model Design Progress Update Initial Results
Contributions to the State-of-the-Art New Policy Variables and Sensitivity
Agenda
Background & MotivationBackground & Motivation Overview of Model Design Progress Update Initial Results
Contributions to the State-of-the-Art New Policy Variables and Sensitivity
Agenda
Knoxville Area Population: 863,000 Area: 3,425 sq. mi. Network: 6,626 lane miles TAZ: 1019 zones
Background
Knoxville Area Multinucleated
Knoxville Maryville Oak Ridge Smoky Mountains
/ Gatlinburg, etc.
Background
Knoxville Area Multinucleated Topography
Background
2000 Household Travel Survey
2002 New Trip-based Model
2005 Model Peer-Review
2007 External Cordon Line Survey
2008 Land Use Model (ULAM)
2008 Household Travel Survey
2008 Transit On-board Survey
2009 New Hybrid Trip/Tour-based Model
Background
Model Peer Review Noted poor distribution and k-factors
Policy and Planning Interests Built environment / land use interactions Importance of transit and walking Future tolling / pricing scenarios?
Motivation
Hybrid Trip/Tour-based Model promised: Improved fundamentals of travel behavior Sensitivity to new planning / policy issues Reasonable model run times Reasonable development costs and
timeframe
New Model
Background & Motivation Overview of Model DesignOverview of Model Design Progress Update Initial Results
Contributions to the State-of-the-Art New Policy Variables and Sensitivity
Agenda
Methodology1. A hybrid disaggregatedisaggregate / aggregateaggregate system
To maximize model fidelity and minimize run time
A New, Alternative Model Design
Network
TAZ
Flow Averaging
TrafficAssignment
HOV and TollChoices
Stop SequenceChoice
Stop LocationChoice
Tour ModeChoice
Activity / TourGeneration
PopulationSynthesizer
Accessibility
Travel Times
LinkFlows
Departure TimeChoice
Variables Models
Disa
ggregate M
odelsA
ggregate M
odels
Vehicle AvailabilityChoice
Methodology1. A hybrid disaggregatedisaggregate / aggregateaggregate system
To maximize model fidelity and minimize run time
2.2. Disaggregate vehicle & tour mode choicesDisaggregate vehicle & tour mode choices
3.3. Departure time choiceDeparture time choice
A New, Alternative Model Design
Network
TAZ
Flow Averaging
TrafficAssignment
HOV and TollChoices
Stop SequenceChoice
Stop LocationChoice
Tour ModeChoice
Activity / TourGeneration
PopulationSynthesizer
Accessibility
Travel Times
LinkFlows
Departure TimeChoice
Variables Models
Disa
ggregate M
odelsA
ggregate M
odels
Vehicle AvailabilityChoice
Methodology1. A hybrid disaggregatedisaggregate / aggregateaggregate system
To maximize model fidelity and minimize run time
2.2. Disaggregate vehicle & tour mode choiceDisaggregate vehicle & tour mode choice
3.3. Departure time choiceDeparture time choice
4. Feedback of ACCESSIBILITYACCESSIBILITY as well as travel time To introduce sensitivity to ‘lower level’ choices in
‘upper level’ decisions
A New, Alternative Model Design
Network
TAZ
Flow Averaging
TrafficAssignment
HOV and TollChoices
Stop SequenceChoice
Stop LocationChoice
Tour ModeChoice
Activity / TourGeneration
PopulationSynthesizer
Accessibility
Travel Times
LinkFlows
Departure TimeChoice
Variables Models
Disa
ggregate M
odelsA
ggregate M
odels
Vehicle AvailabilityChoice
Methodology1. A hybrid disaggregatedisaggregate / aggregateaggregate system
To maximize model fidelity and minimize run time
2.2. Disaggregate tour mode choiceDisaggregate tour mode choice
3.3. Departure time choiceDeparture time choice
4. Feedback of ACCESSIBILITYACCESSIBILITY as well as travel time To introduce sensitivity to ‘lower level’ choices in
‘upper level’ decisions
5. A ‘double destination choicedouble destination choice’ framework Produce trips consistent w/ tours & trip-chaining behavior
A New, Alternative Model Design
Network
TAZ
Flow Averaging
TrafficAssignment
HOV and TollChoices
Stop SequenceChoice
Stop LocationChoice
Tour ModeChoice
Activity / TourGeneration
PopulationSynthesizer
Accessibility
Travel Times
LinkFlows
Departure TimeChoice
Variables Models
Disa
ggregate M
odelsA
ggregate M
odels
Vehicle AvailabilityChoice
Background & Motivation Overview of Model Design Progress UpdateProgress Update Initial Results
Contributions to the State-of-the-Art New Policy Variables and Sensitivity
Agenda
Since development began in earnest in January: All model estimation is complete Model implementation is nearly complete Model validation is currently underway
Progress
Background & Motivation Overview of Model Design Progress Update Initial ResultsInitial Results
Contributions to the State-of-the-ArtContributions to the State-of-the-Art New Policy Variables and Sensitivity
Agenda
Choice Hierarchy
In traditional four-step models, mode choice was modeled conditional on (after) destination choice (due to a preoccupation with choice riders and commuting).
Instead, we modeled stop location or destination choice conditional on (after) mode choice
March 12, 2009
Network
TAZ
Flow Averaging
TrafficAssignment
HOV and TollChoices
Stop SequenceChoice
Stop LocationChoice
Tour ModeChoice
Activity / TourGeneration
PopulationSynthesizer
Accessibility
Travel Times
LinkFlows
Departure TimeChoice
Variables Models
Disa
ggregate M
odelsA
ggregate M
odels
Vehicle AvailabilityChoice
Choice Hierarchy
In traditional four-step models, mode choice was modeled conditional on (after) destination choice (due to a preoccupation with choice riders and commuting).
Instead, we modeled stop location or destination choice conditional on (after) mode choice We sequentially estimated combined (nested logit) combined (nested logit)
mode and stop location (and sequence) choice modelsmode and stop location (and sequence) choice models And all the logsum / nesting parameters were in the
acceptable ranges without using constraintswithout using constraints, suggesting that this may be the correct choice hierarchy
Choice Hierarchy
This reverse choice hierarchy reflects the fact that many travelers are more likely to change many travelers are more likely to change destinations than switch modesdestinations than switch modes Even for work tours, the data suggests that in
Knoxville, people are more likely to change jobs than change their travel mode to work
This may not be as unreasonable as it seems, considering captive riderscaptive riders, dependent on the bus to get to work
Imposing the traditional hierarchy traditional hierarchy may be a source of “optimism bias” “optimism bias” in transit forecasts
The new model incorporates travelers’ tendency to group stops together into convenient chains
This convenience of locations to other stops is measured by special accessibilityaccessibility variables included in stop location (destination) choice
Trip-Chaining
Independence
In traditionaltraditional models, two equidistantequidistant, equal-sizeequal-size destinations are equally probableequally probable.
ComplementarityIn the Knoxville model, the more accessiblemore accessible one is more probable -
because you have to go a nearby destination anyway, and so it’s convenient.
Higher accessibility means the expected costexpected cost of a possible
subsequent trip is lower.
The new model incorporates travelers’ tendency to group stops together into convenient chains
This convenience of locations to other stops is measured by special accessibilityaccessibility variables included in stop location (destination) choice The models are extensions of Fotheringham’s
Competing Destinations (CD) model Incorporating recent research by Bernardin,
Koppelman and Boyce (2009)
Trip-Chaining
The model uses a “double destination choice” framework Generating trips guaranteed to be consistent
with tours Without generating the tours, themselves Allowing fast run times!
Touring
Network
TAZ
Flow Averaging
TrafficAssignment
HOV and TollChoices
Stop SequenceChoice
Stop LocationChoice
Tour ModeChoice
Activity / TourGeneration
PopulationSynthesizer
Accessibility
Travel Times
LinkFlows
Departure TimeChoice
Variables Models
Disa
ggregate M
odelsA
ggregate M
odels
Vehicle AvailabilityChoice
Network
TAZ
Flow Averaging
TrafficAssignment
HOV and TollChoices
Stop SequenceChoice
Stop LocationChoice
Tour ModeChoice
Activity / TourGeneration
PopulationSynthesizer
Accessibility
Travel Times
LinkFlows
Departure TimeChoice
Variables Models
Disa
ggregate M
odelsA
ggregate M
odels
Vehicle AvailabilityChoice
Travel Cost Elasticity Found elasticities of out-of-home activities with
respect to accessibility of 0.13 - 0.16 Lower tour-making by residents of ruralrural (lower-
accessibility) areas, Decreased tour/stop-making in response to
congestioncongestion (decreased accessibility), Induced tour/stop-making in response to added added
network capacitynetwork capacity (increased accessibility), Induced tour/stop-making in response to new land new land
use developmentsuse developments in other nearby zones (increased accessibility)
Network
TAZ
Flow Averaging
TrafficAssignment
HOV and TollChoices
Stop SequenceChoice
Stop LocationChoice
Tour ModeChoice
Activity / TourGeneration
PopulationSynthesizer
Accessibility
Travel Times
LinkFlows
Departure TimeChoice
Variables Models
Disa
ggregate M
odelsA
ggregate M
odels
Vehicle AvailabilityChoice
Residence Effects on Trip Length
When people choose their residence location, they also choose how far they are willing to travel.
We allowed travelers’ willingness-to-travel, and hence, trip lengths to vary as a function of the accessibility of their residence location The willingness-to-travel of residents of the most urban most urban
(most accessible) areas was about 10% lower 10% lower than the regional average
The willingness-to-travel of residents of the most rural most rural (least accessible) areas was about 200% higher 200% higher or twice the regional average for most activity types
Cost Elasticity from Accessibility
Including accessibility in both activity generation and stop location choice reflects fewerfewer, but longerlonger ruralrural tours; more shorter urban more shorter urban tours
Background & Motivation Overview of Model Design Progress Update Initial ResultsInitial Results
Contributions to the State-of-the-Art New Policy Variables and SensitivityNew Policy Variables and Sensitivity
Agenda
Auto Availability Each individual household chooses how
many vehicles to own / lease Disaggregate ordered response logit model Vehicle ownership levels respond to
Demographics (household size, income, number of workers, students, etc.)
Gas PricesGas Prices Transit AvailabilityTransit Availability Urban Design Urban Design (intersection approach density
measuring grid vs. cul-de-sac network design)
No Veh
1 Veh
Nest
Nest
Root
2 Veh
Nest
3 Veh
4+ Veh
Tour & Stop Generation
Workers Non-Workers Students Seniors Vehicles Income Gas Price Access-
ibility
Work Tours + - +
Work Stops + - + - +
Non-UT Univ Stops + + - - +
Other Stops + - + - + - +
School Tours + +
School Stops + +
Other Stops + + +
Other Tours + + + +
Short Maintenance Stops + + + +
Long Maintenance Stops + - + + + +
Discretionary Stops + + + - +
Factors Affecting Mode Choice
Level of Service Costs Demographics Built Environment
Accessibility by mode
Distance to UT
% of TAZ Near Bus Gas Price Bus Fare Workers Students Senior
HH IncomeVehicles per
Person
Percent Sidewalks
Activity Diversity
Intersection Density
Work Tours Auto + - + + + + + - - Bus + + - - - + - - -
Walk + + + + - - - + + UT Tours
Auto + - - + - Bus - + + - -
Walk - - - - +
School Tours Auto + - + + Bus + + - + Walk + + - -
School Bus + + - -
Other Tours Auto + - + + + + + - -Bus + + - + - - - - -
Walk + + + - + - - + +
Stop Location Choice
Consistency with tourstours and trip-chaining trip-chaining behavior Reduced aggregation bias Improved policy sensitivitypolicy sensitivity Reasonable run times run times and development costsdevelopment costs!
Advantages of the New Approach
Thank You!