California Statewide Freight Forecast Model Development

Transcription

1 California Statewide Freight Forecast Model Development Kickoff Meeting January 4, 2012 Institute of Transportation Studies University of California, Irvine

2 Project Team from UC Irvine Principal Investigator: Professor Stephen Ritchie Faculty: Professor Michael McNally Postdoc: Dr. Joseph Chow Postdoc: Dr. Andre Tok Graduate Students Miyuan Zhao Iris You Fatemeh Ranaiefar Pedro Camargo Daniel Rodriguez-Roman Vanessa Luong Kyungsoo Jeong Paulos Lakew Kate Hyun Neda Masoud 2

3 Source: Inventory of US GHG Emissions and Sink , EPA, 2013 Motivation (1) Freight transportation CO 2 emissions accounted for 6.1% of total US emissions in Industry 20% Agriculture 8% Electric Power Industry 33% USDOT: by 2035, total US freight tonnage will reach nearly double the 2002 levels Commercial 6% Residential 5% U.S. Terriories 1% Transportation 27% Passenger Transportation 16% Trucking 6%

4 Motivation (2) Existing tools California Statewide Travel Demand Model (CSTDM) MPO Freight Models (e.g. SCAG Heavy Duty Truck Model) Need for a statewide, commodity-based, policy-sensitive and freight infrastructurebased model 4

5 Purpose of the Model Policy-sensitive model to forecast commodity flows and commercial vehicle flows within California addressing: Socioeconomic conditions Land use policies related to freight Environmental policies Multimodal infrastructure investments 5

6 Example Scenario: Panama Canal What happens to average daily GHG emissions on I- 5 corridor in Fresno when Panama Canal is widened in 2014? Doug MacIvor, Caltrans From Dr. Asaf Ashar of National Ports and Waterways Initiative, University of New Orleans, 6

7 Example Scenario: Infrastructure Investment What happens if a rail terminal s capacity increased by 10%? Rail Terminal A Truck flows Rail flows Rail Terminal B Truck flows Truck flows Zone B Rail Terminal A Rail flows Rail Terminal B Truck flows Zone B Zone A Truck flows Truck flows Zone A 7

8 Example Scenario: Carbon Pricing How would truck/rail mode share change if a carbon tax of $20/ton was levied on transportation fuels? 8

9 Project Scope $1.4M Budget 2 Year Timeline: Complete by June 2013 Compatibility with California Statewide Travel Demand Model (CSTDM) SB 391 Section 65071: update the California Transportation Plan by December 31, 2015 Section : shall consider all subject areas for movement of people and freight 9

10 Users of the Model California Department of Transportation Division of Transportation System Information Division of Transportation Planning Division of Rail Districts 1 12 California Air Resources Board Metropolitan Planning Organizations Port and Freight Facilities California Energy Commission Others 10

11 Project Timeline 11

12 MODEL DETAILS 12

13 Proposed FAZ Scheme Total zones in CA: 96 Neighboring states: 7 zones Other states: 46 zones International: 8 zones Total zone centroids: 157 Transshipment Nodes: 51 Total OD Nodes: 208 FAZs in CA

14 Commodity Flows Cereal Grain Waste/Scrap 2-Digit SCTG Commodity Groups 14 Aggregate Groupings Considered 14

15 Changes to CSTDM Network NODES: - Add Transshipment Nodes - Add New Network Gateways - Add New Zone Centroids CSTDM Network LINKS: - Update Truck Tolls - Add Truck Routes - Add Truck Restrictions - Add WIM Locations - Add Freight Rail Lines - Add Hazardous Material Routes - Explode Transshipment Nodes to Links - Add New Connectors 15

16 Transshipment Logistic Nodes Air: BTS T-100 Water: Waterborne Commerce Data Rail: STB Waybill ORNL 1998: 163 Intermodal Facilities (Water/Rail Terminals) Select a list based on tonnage for each point and the scattering locations of facilities BTS-NTAD 2003: 212 Intermodal Facilities (Warehousing/Distribution Centers) ORNL 2000: 825 Rail Facilities Satellite Map 16 Major Air TLNs 11 Major Water TLNs 24 Major Rail TLNs 51 Transshipment Facilities 16

17 Air TLNs (16 Airports) ID NAME ID NAME 1 Sacramento International 9 Santa Barbara Municipal 2 Sacramento Mather 10 John Wayne Airport-Orange County 3 Norman Y. Mineta San Jose International 11 March ARB 4 Metropolitan Oakland International 12 Bob Hope 5 San Francisco International 13 Long Beach Airport 6 Fresno Yosemite International 14 San Diego International 7 Meadows Field 15 Ontario International 8 Imperial County 16 Los Angeles International Data: BTS-T100 17

18 Water TLNs (11 Seaports) ID NAME ID NAME 1 HUMBOLT 7 REDWOOD CITY 2 SAN FRANCISCO 8 HUENEME 3 RICHMOND 9 LONG BEACH 4 SACRAMENTO 10 LOS ANGELES 5 STOCKTON 11 SAN DIEGO 6 OAKLAND Data: Waterborne Commerce Data 18

19 Rail TLNs (24 Rail Terminals) ID NAME ID NAME ID NAME 1 WEST SACRAMENTO 9 SP NEWARK YD 17 Dolores 2 STOCKTON 10 FRESNO 18 LATC 3 LATHROP 11 BARSTOW 19 LA/LONG BEACH 4 MODESTO COLONY 12 SAN BERNARDINO 20 POMONA 5 PITTSBURG 13 CUCAMONGA 21 CITY OF INDUSTRY 6 NORTH BAY 14 KAISER 22 LA MIRADA 7 RICHMOND 15 BAKERSFIELD 23 SAN DIEGO 8 OAKLAND INT GATEWAY 16 LOS ANGELES 24 SAN YSIDRO 19

20 CORE MODEL County Level (58+) + FAF Zones (100+) 100+ Intermodal Facilities in CA 2008 Base Year, 2010 Base Year Update, 2002 Commodity Validation; 2000 Network Validation Transshipment Data Commodity to Vehicle Distribution Time of Day Distribution Socioeconomic Data by Zone Exports/Imports by Zone Modal Network Attributes Annual to Daily Distribution Regression Logit Share Model Mode-Route Choice Peak Vehicle Flow Distribution Commodity Productions & Consumptions by Zone Commodity OD Pairs Annual Commodity Route Flows by Mode

21 Commodity OD Flows (FAF3/CFS) Industry Technical Coefficients (IMPLAN) Socioeconomic Data by Zone Transshipment Data (derived from Rail Waybill) Commodity Seasonality Firm Data (InfoUSA) Aggregate Inventory Data Where intrazonal GPS truck data is available Disaggregated Sub-Zones Modal Network Attributes Commodity to Vehicle Payloads (VIUS) Annual to Daily Distribution Truck GPS Activity Pattern Data by Zone Direct Demand Input Output Model Transshipment Network Model Inventory-Based Firm Microsimulation Truck Tour Disaggregation Time of Day Intrazonal Truck OD Input data for calibration Input data for model Commodity OD Pairs by Mode Annual Vehicle Route Flows by Mode and Vehicle Class Average Daily Inventories by Zone Truck Count Data by Class (WIM) Model function Model output ENHANCED MODEL Annual Transshipments Average Daily Vehicle Flows Stochastic Assignment

22 User Training and Support Workshop User Manual Web-based Educational Module (6 basic courses) Intro to Freight Transportation Impacts on Freight Transportation Data for Freight Transportation Regional/Statewide Freight Planning Local/Urban Freight Planning Freight Operations 22

23 Project Management and Oversight: Redmine Issue Tracker Open source project management Tool Features highlight: Dynamic management of subtasks, issues and assignments Document and file repository Wiki Record of processes and decisions 23

24 Technical Peer Advisory Committee Current Candidates: J. Douglas Hunt Professor, HBA Specto and University of Calgary Anne Goodchild Ram Pendyala Miguel Figliozzi William Rogers Eric Shen Scott Drumm Rolf Schmitt Assistant Professor, University of Washington Professor, Arizona State University Associate Professor, Portland State University Senior Program Officer, Transportation Research Board Director of Transportation Planning, Port of Long Beach Manager, Port of Portland Team Leader, Freight Analysis, Federal Highway Administration 24

25 QUESTIONS OR COMMENTS? 25