The New Trend of Travel Demand Model

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The New Trend of Travel Demand Model Lessons
learned from the New York Best Practice Model
Presentation at Taipei Department of
Transportation
Kuo-Ann Chiao Director of Technical Services New
York Metropolitan Transportation Council
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NYBPM Study Area

• 20,000,000 population
• 100 population segments
• 4,000 Transportation Analysis Zones
• 4 time periods
• 6 trip purposes
• 10 motorized modes
• 4 urban types

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Location Distribution 1997 Household Travel
Survey A joint project between NYMTC and NJTPA

• Location-based
• 11,000 households
• 28,000 people
• 118,000 trips

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Highway Network
Uni-directional coding Ramps

• Very large network (52,794 links in 28 county 3
  state NY metro area)
• 4,950 High-level facilities
• 26,385 Arterials
• 10,694 Centroid and external connectors
• 10,765 Other
• Unidirectional / dualized coding
• Conflated the network geography
• GIS Street Network TIGER (or LION) Developed in
  TransCAD Software
• SOV, HOV2, HOV3, taxi, truck, other commercial
• Classified by 21 Primary Link Types for
  capacities, initial speeds and VDFs

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Zones SystemCensus Tract Based
BPM zone boundaries
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Transit Network

• Extremely detailed transit coding based on
  information from MTA and NJ Transit
• Developed in TransCAD 4.0
• Each route variation coded as a distinct route
• 100 NYC subway routes
• 900 Commuter rail routes
• 2,300 bus routes
• 73,000 transit stops.
• 50 ferry routes
• Includes sidewalk network in Manhattan
• Walk access/egress links
• Park - and - Ride

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Transit Network
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Highlights of NYBPM

• Micro-Simulation choice models
• Population synthesis and intra-household travel
  interactions
• Journey-based travel units modeled
• Non-motorized (pre-mode choice)
• Mode-Destination Choice (nested logit)
• Stop frequency and location sub-model
• Full multi-modal analysis / assignment

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Route-Deviation Concept
Stop k
dik
dkj
Origin i
Destin j
dij
Combined impedance dik dkj
Absolute route deviation dik dkj - dij
Relative route deviation (dik dkj dij)/ dij
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General Modeling Structure
Journey Generation
Micro-Simulation
Mode Destination
Time of Day
Assignment
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Journey Generation
Seed PUMS
Synthetic Population
Journey Generation
Socio-Economic Targets
Mode Destination
LUM
Auto Ownership
Accessibility
Time of Day
Journey Frequency
Assignment
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Journey Frequency Model
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Mode Destination
Pre-Mode
Journey Generation
Density
Mot. Dest.
NM Dest.
Mode Destination
Mode
Land Use Attractors
LOS Skims
Time of Day
Stop Frequency
Stop Location
Assignment
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Pre-mode Choice Nested Structure
Non-motorized Mode
Motorized Mode
Density of attractions
Destination Choice
Drive Alone
Transit/ Shared Ride
Taxi
Purpose-specific attractions
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Mode Choice to WorkNested Structure
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Mode Choice to WorkMode Availability
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Mode Destination Choice
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Destination-Choice ModelUtility Components

• Attraction-size variable
• Mode-choice log-sum
• 3 River-crossing dummies
• Intra-county dummy
• Distance-based term
• 4 To-Manhattan dummies
• County-to-county k-factors

Disaggregate Calibration
Aggregate Adjustment
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Stop Frequency by Purpose
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Stop Frequency by Mode
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Stop Distribution by Duration
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Time of Day
Journey Generation
Predetermined Set of TOD Distributions
Mode Destination
Stage 1 Journey Split by Legs and Periods
Stage 2 (Current)Journey Split by Trips and
Periods
Stage 3 TOD Choice Model
Timing Durational Utility
Time of Day
LOS Skims
Assignment
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Stages of Calibrationand Validation Sources
Disaggregate Calibration by Purpose
Household Survey
Aggregate Calibration Of Destination Choice
Household Survey PUMS
Aggregate Calibration Of Mode Shares
Household Survey PUMS
Highway and Transit Assignment
Traffic Counts Screenline Database MATRIX HPMS
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Fractional Probability
Mode 1 (0.05)
Destination 1 (0.15)
Mode 2 (0.03)
Mode 3 (0.07)
Mode 1 (0.15)
Tour
Destination 2 (0.75)
Mode 2 (0.25)
Mode 3 (0.35)
Mode 1 (0.05)
Destination 3 (0.10)
Mode 2 (0.02)
Mode 3 (0.03)
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Micro-Simulation
X
Destination 1 (0.15)
X
Mode 1 (0.15)
Tour
X
Destination 2
Mode 2 (0.25)
Mode 3
X
Destination 3 (0.10)
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Aspects of Micro-Simulation for NYBPM Processing

• Nearly 9 million households in base year
• Journey productions file over 500 Meg
• Mode destination choice stops model processes
  over 25 million paired journeys by 8 trip
  purposes
• Output files over 300 Meg
• 6 highway classes and 4 transit trip tables for
  each of 4 time periods
• Combined file size about 2.5 Gig
• Hardware 4 GB RAM / Dual Processor / 1.5 Ghz /
  120 GB Hard Drive

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Dimension of Choice Probability in NYBPM
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Processing Time For BPM Model Run
12 hrs
current improvements
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Status of On-Going Improvements

• Speed up the running time
• Software Engineering
• Memory Handling
• allocated the memory only once, using a flag to
  determine if the memory had already been
  allocated
• memory could be allocated in one block
• Input/Output
• Remove messages (one per 33 million lines in the
  HAJ trip file) to the screen, reduced processing
  time from 22 minutes to 20 seconds
• Parameter Passing
• Passing information of a pointer to a structure
  rather than an entire structure (e.g., the memory
  used to call about 260,000 times of one function
  with 92 bytes could be reduced significantly by
  passing a pointer to the structure that only
  requires 4 bytes)
• In-lining Function Calls
• Very short functions that are called frequently
  can cause bottlenecks (function consists of just
  a few lines (e.g., Calling a function, which was
  being called between 300,000 to 600,000 times,
  was taking up 10 of the total program time.
  In-lining the function reduced it to 0.3 of the
  total program time)
• Additional optimization
• Hardware optimization

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BPM Structure GUI for User Documentation
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Applications of BPM at NYMTC

• Conformity Analysis
• Regional Transportation Plan
• Congestion Management Systems
• Testing Scenarios for emission reduction
  strategies
• Request for Data Manipulation and Runs from other
  agencies

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Applications of BPM .. Projects

• Tappan Zee Bridge
• Gowanus Expressway
• Bronx Arterial Needs
• Bruckner Sheriden Expressway
• Long Island East Side Study
• Canal Area Transportation Study
• Lower Manhattan Development Corporation
• Southern Brooklyn Transportation Study
• Regional Freight Plan Study
• Hackensack Meadowland Development Corp.

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Model Update

• Study of Post 9/11 Travel Pattern Changes
• New Set of Socioeconomic and Demographic
  Forecasts
• Collection of 2002 traffic and transit data
• Updated 2002 base year Model

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Model Improvements

• Better Highway -Transit Connection
• Improve transit models
• Integrate BPM with the Land Use Model
• Web Applications
• Model output analysis
• Model runs
• Distributed Process
• Better GUI (flowchart-based, on-line help
  document)
• More project applications
• BPM Users Group Support Meetings

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Advisory Committee

• Patrick T. Decorla-Souza, Federal Highway
  Administration
• Frederick W. Ducca, Federal Highway
  Administration
• Ron Jensen-Fisher, Federal Transit Administration
• T. Keith Lawton, Metro, Portland, Oregon
• Arnim H. Meyburg, Cornell University
• Elaine Murakami, Federal Highway Administration
• The Late Eric Paas, Duke University
• Charles Purvis, Metropolitan Transportation
  Commission
• Bruce Spear, Federal Highway Administration
• Frank Spielberg, S. G. Associates
• John Thomas, Environmental Protection Agency
• David Zavattero, Chicago Area Transportation Study