2014 AMPO Annual Conference, Atlanta, GA
October 23, 2014
Freight Session
MAG New Generation Freight
Model
SHRP2 C20 IAP Project
Vladimir Livshits, Ph.D.
The Need
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• Planning efforts at ADOT, MAG
and PAG have to address new
scale of geography – Arizona’s Sun
Corridor Mega-Region
– Very significant growth in the
freight traffic
– Part of the global supply chain
Source: http://www.jpacaz.org/map.asp
• Modeling areas reflect
mega-regional approach.
MAG/PAG ABM includes
Maricopa, Pinal, Pima
and portions of Yavapai
and Gila counties
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Safety and
Efficiency
of shipping
Congestion
and
Hazards
Freight
Mobility
Land Use and
Environmental
Impact
Freight
Planning
Integration
with Regional
Planning –
Freight
Corridors
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Economic
Impact
Communities
and Social
Equity
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The Legacy
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•
State of the Practice Truck Models served us well
but fall short in answering future freight planning
needs
Aggregated model – does not provide for detailed land use, infrastructure,
community planning scenario analysis. Insensitive to agent-based economic
scenarios, does not account for evolutionary developments of economic agents in
the forecast, insensitive to fine-grained network changes.
•
Does not include supply chain models and is not suitable for development of
economic scenarios on mega-regional scale. Insensitive to mega-regional supply
chain scenarios and technological shifts.
•
Static model - does not provide for integration with dynamic traffic simulations,
detailed safety analysis, and agent-based passenger travel demand models with
continuous timeline.
•
Trip-based – is not consistent with operational behavior of carriers and as a result
insensitive to operational scenarios or relevant network improvements.
•
Does not account for multi-modal aspect of supply chains, does not forecast
multimodal freight flows and is not sensitive to multimodal freight issues.
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The Vision
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SHRP2 C20 Guidance
Strategic objectives of SHRP2-C20 project:
•
•
•
•
•
Improve and expand the knowledge base
Develop modeling methods to reflect actual supply chain management practices
Develop modeling methods based on sound economic principles
Maximize use of freight tools by public sector for planning and programming
Improve availability and visibility of data between public and private sectors
In order to achieve the above objectives, the following SHRP2
research initiatives will be addressed in this work:
•
•
•
•
•
Establish techniques and standard practices to validate freight forecasts.
Establish modeling approaches for “behavior-based” freight movement.
Establish analytical approaches that describe how elements of the freight transportation system operate, perform,
and impact the larger overall transportation system.
Determine how economic, demographic, and other factors/conditions drive freight patterns and characteristics.
Document economic and demographic changes related to freight choices.
Advance research to effectively integrate logistics practices (private sector) with transportation policy, planning,
and programming (public sector).
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The Approach
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Main Methodological Principles
• Agent-based micro-simulation model
• Multi-modal freight model
• Behavioral model, including economic
behavior of establishments, shiuppers, carriers
in travel generation and tour formation
• Integration with activity-based passenger
model
• Industry-specific model
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Tour Generation
Heavy truck
tour rates by
industry type
Stop Generation
1 stop
2 stops
……..
Tour Completion
Yes – return to
home base
No – does not
return
Stop Purpose
One of 10 stop
types
•Retail
•Constr.
•Farming
•Resid.
•Govt.
•Warehs.
•Transp.
•Office
•Industrial
•Service
Stop Location
One of 3,000
TAZs
Stop TOD Choice
1st Stop TOD (24
1-hr periods)
Next Stop TOD
(24 1-hr
periods)
11 stops
Source: Kuppam, A. et al. Development of a Tour-Based Truck Travel Demand Model using Truck GPS Data. Presented at the 2014 TRB 93rd
Annual Meeting. January 2014.
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All Trucks in April 2011
GPS Events = 3,429,603
Truck Tours = 58,637
Trucks = 22,657
One Truck (ID 357042) in April 2011
GPS Events = 719
Truck Tours = 40
Trucks = 1
ATRI GPS Truck ID 3570452
April 2011
ATRI GPS All Truck IDs
April 2011
Source: Kuppam, A. et al. Development of a Tour-Based Truck Travel Demand Model using Truck GPS Data. Presented at the 2014 TRB 93rd
Annual Meeting. January 2014.
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Work plan and
organization of
TAG
Model
Structure and
methods
Data
requirements
and data
sources
Data Collection
– GPS data
Commodity flow
data
acquisition
GPS data
analysis and
processing
Collection and
analysis of
traffic counts
List of main
traffic
generators and
industries
Establishments/
firm synthesis
models
Behavioral
establishment
interaction model/
distribution models
Tour formation
models for different
truck
types/industries
Mode choice models
Multimodal
network and
corresponding
documentation.
Firm Evolution
Model
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Establishment
survey, commercial
vehicles survey
Contractual
work and
administration
Quality control
and Assurance
Employment
and land use
projections
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