Title: The New Trend of Travel Demand Model
1The 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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5NYBPM 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
6Location Distribution 1997 Household Travel
Survey A joint project between NYMTC and NJTPA
- Location-based
- 11,000 households
- 28,000 people
- 118,000 trips
7Highway 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
8Zones SystemCensus Tract Based
BPM zone boundaries
9Transit 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
10Transit Network
11Highlights 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
12Route-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
13General Modeling Structure
Journey Generation
Micro-Simulation
Mode Destination
Time of Day
Assignment
14Journey Generation
Seed PUMS
Synthetic Population
Journey Generation
Socio-Economic Targets
Mode Destination
LUM
Auto Ownership
Accessibility
Time of Day
Journey Frequency
Assignment
15Journey Frequency Model
16Mode 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
17Pre-mode Choice Nested Structure
Non-motorized Mode
Motorized Mode
Density of attractions
Destination Choice
Drive Alone
Transit/ Shared Ride
Taxi
Purpose-specific attractions
18Mode Choice to WorkNested Structure
19Mode Choice to WorkMode Availability
20Mode Destination Choice
21Destination-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
22Stop Frequency by Purpose
23Stop Frequency by Mode
24Stop Distribution by Duration
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27Time 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
28Stages 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
29Fractional 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)
30Micro-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)
31Aspects 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
32Dimension of Choice Probability in NYBPM
33Processing Time For BPM Model Run
12 hrs
current improvements
34Status 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
35BPM Structure GUI for User Documentation
36Applications 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
37Applications 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.
38Model 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
39Model 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
40Advisory 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