Moving Into Practice by JD Hunt, University of Calgary PROCESSUS Second International Colloquium Toronto ON, Canada June 2005.

Slides:



Advertisements
Similar presentations
ATHENS UNIVERSITY OF ECONOMICS AND BUSINESS TRANSPORTATION SYSTEMS AND LOGISTICS LABORATORY (TRANSLOG) © Prof. K. Zografos STEPs STEPs Scenarios for the.
Advertisements

Use GIS-T to Synchronize Land and Infrastructure Development Principle Investigator: Yingling Fan Humphrey Institute of Public Affairs Co-Investigator:
Oregon Freight Plan July 28, Linking Freight Improvements to Economic Growth Travel Time Freight Transportation Improvements Productivity Competitiveness.
OVERVIEW OF CMAPS ADVANCED TRAVEL MODEL CADRE Kermit Wies, Deputy Executive Director for Research and Analysis AMPO Modeling Group, November 2010.
Investigating Land Use Regulation and Transportation Policy with the San Diego PECAS Model Dimantha I De SilvaHBA Specto Incorporated Daniel Flyte San.
GIS and Transportation Planning
Economic Development Benefit/Cost Transit Slides.
GIS at PSRC GIS data collection & travel demand modeling ESRM 250 February 4, 2010.
Utilizing Connected Travel Demand and Land Use Models in the Sacramento Region Gordon R. Garry Sacramento Area Council of Governments April 30, 2010.
Freight Transportation in the Upper Midwest Transportation Border Working Group Calgary, Alberta Mr. Travis Gordon Midwest Regional University Transportation.
French cities’ urban freight surveys 1 st Scientific and Technical Workshop Bologna 05/11/2013 Presented by: Adrien Beziat, PhD, Paris, France.
The SoCoMMS Model Paul Read Dan Jones. The Presentation Outline of the Study The Modelling Framework Accessibility Model.
1 JD Hunt JE Abraham JAS Khan University of Calgary Workshop of the Land Use Transport (LUT) Modelling Group London, UK 2 July 2005 Calgary Testbed for.
SCAG Region Heavy Duty Truck Model Southern California Region Heavy Duty Truck Model.
Applying the SWIM2 Integrated Model For Freight Planning in Oregon Prepared for the 13 th TRB Transportation Planning Applications Conference May 9, 2011.
MAG New Generation Freight Model SHRP2 C20 IAP Project Vladimir Livshits, Ph.D AMPO Annual Conference, Atlanta, GA October 23, 2014 Freight Session.
Freight transport modelling - an approach to understand demand and use of transport energy Annecy, May 26th, 2008 Ole Kveiborg and Jean-Louis Routhier.
Transportation Planning Section, Transportation Development Division Oregon Transportation Plan 2005 Modeling Alternative Policy Choices Becky Knudson,
Logistics and Regions. Trends The regions are becoming integrated in large-scale network economies (new markets conditions, reliance on global supply.
Transportation Planning Analysis UnitPNREC 2006 Transportation Modeling in Oregon: Overview of ODOT Statewide Integrated Model Pacific Northwest Regional.
Advanced Modeling System for Forecasting Regional Development, Travel Behavior, and the Spatial Pattern of Emissions Brian J. Morton Elizabeth Shay Eun.
Lec 15 LU, Part 1: Basics and simple LU models (ch6.1 & 2 (A), ch (C1) Get a general idea of urban planning theories (from rading p (A)
Estimating Congestion Costs Using a Transportation Demand Model of Edmonton, Canada C.R. Blaschuk Institute for Advanced Policy Research University of.
Transportation Development Division Oregon Integrated Land Use and Transportation Models Part 1: Statewide Model Part 2: MetroScope Part 3: Land Use Scenario.
SEMCOG Modeling Peer Exchange Panel Report. Overall Outline Topic Definition Planning Objective Problem Statement Basic Solution Advanced Solution Resources.
11 San Diego Work Related Travel Survey Brian Lane, SANDAG Kevin Stefan, HBA Specto ABJ40 Travel Survey Methods Committee January 16, 2013.
Humber Bridge Review Results from the HUMBER ESTUARY TRANSPORT MODEL.
Microsimulation of Intra-Urban Commercial Vehicle and Person Movements 11th National Transportation Planning Applications Conference Session 11: May 8,
Program Update Baltimore MPO November 25, Internal Draft AGENDA  Program Overview  Alternatives Development  Stakeholder and Public Outreach.
2010 Travel Behavior Inventory Mn/DOT TDMCC- Jonathan Ehrlich October 14, 2010.
Traffic Assignment Convergence and its Effects on Selecting Network Improvements By Chris Blaschuk, City of Calgary and JD Hunt, University of Calgary.
Overview of Project Main objective of study is to assess the impact of delay at border crossings and resulting changes in user benefits and broad macroeconomic.
ODOT Freight Modeling Presented to the Ohio Conference on Freight Toledo, OH September 18, 2007 By Gregory Giaimo, PE Ohio Department of Transportation.
Using the Oregon Statewide Integrated Model for the Oregon Freight Plan Analysis Prepared for the TRB SHRP2 Symposium: Innovation in Freight Demand Modeling.
11. 2 Public Transportation’s Role in a Greenhouse Gas Reduction Strategy Kevin Desmond King County Metro Transit Division Seattle, WA On behalf of the.
Transportation leadership you can trust. presented to presented by Cambridge Systematics, Inc. TRB Applications Conference – Freight Committee May 7, 2013.
Florida Multimodal Statewide Freight Model
Jamie Bridges Charles Baber John Abraham Abdel-Rahman Muhsen Dimantha De Silva Sudipta Sarkar Baltimore Metropolitan Council HBA Specto Incorporated.
April 2010 Scott Smith Volpe Center / RITA / U.S. DOT Transportation Border Working Group Meeting Boston, MA An Integrated Regional Planning / Microsimulation.
Presentation to the Sustainable Prosperity Conference
Characteristics of Weekend Travel in the City of Calgary: Towards a Model of Weekend Travel Demand JD Hunt, University of Calgary DM Atkins, City of Calgary.
1 Activity Based Models Review Thomas Rossi Krishnan Viswanathan Cambridge Systematics Inc. Model Task Force Data Committee October 17, 2008.
September, 2012An Activity Based Model for a Regional City1.
Finance: The Critical Link The Transportation – Land Use – Environment Connection Brian D. Taylor October 2003 Institute of Transportation Studies.
OREGON ECONOMIC & BRIDGE OPTIONS STUDY The problem is not just the bridges, or the freight system, It is about Oregon’s economy and quality of life. FHWA.
Connectivity & Mobility
Jennifer Murray Traffic Forecasting Section Chief, WisDOT Metropolitan Planning Organization Quarterly Meeting July 28 th, 2015.
Transportation leadership you can trust. presented to FHWA “Talking Freight” Seminar Series presented by Lance Neumann Cambridge Systematics, Inc. August.
MARYLAND FREIGHT SUMMIT Freight in the Mid-Atlantic Region Jeffrey F. Paniati Associate Administrator for Operations Federal Highway Administration September.
Improving the Models, SACOG Perspectives Sustainable Communities Implementation Challenges and Opportunities UC Davis Policy Forum Gordon Garry March 5,
Calgary: Taking Modeling in a Different Direction 21 st International Emme Users’ Conference 2007 October
Cal y Mayor y Asociados, S.C. Atizapan – El Rosario Light Rail Transit Demand Study October th International EMME/2 UGM.
What are Intelligent Transportation Systems? Intelligent Transportation Systems (ITS) are existing and new technologies, including information processing,
Integrated Travel Demand Model Challenges and Successes Tim Padgett, P.E., Kimley-Horn Scott Thomson, P.E., KYTC Saleem Salameh, Ph.D., P.E., KYOVA IPC.
Tri-level freight modeling: A simulation of trucks going near and far Rolf Moeckel Parsons Brinckerhoff Sabya Mishra University of Maryland TRB Planning.
Calgary Commercial Movement Model Kevin Stefan, City of Calgary J.D. Hunt, University of Calgary Prepared for the 17th International EMME/2 Conference.
Dialog for Gateway Futures : A Progress Report Dr. Brian Deal University of Illinois.
1 TRANSPORTATION ENERGY USE DIVISION Welcome to US & Canada Transportation Border Working Group Meeting 14 April 2010 Boston, MA.
Presented to Model Task Force Model Advancement Committee presented by Thomas Rossi Krishnan Viswanathan Cambridge Systematics Inc. Date November 24, 2008.
Application of an Activity-based Model for a Toll Road Study in Chicago Matt Stratton Parsons Brinckerhoff May 19, 2015.
OREGON MODELING IMPROVEMENT PROGRAM An Analysis Toolbox for Decision-Makers: A Focus on Freight and the Economy May 2004.
Directionality Influences in Spatial Processes by JD Hunt, University of Calgary M Thériault, Université Laval P Villeneuve, Université Laval PROCESSUS.
Estimation of a Weekend Location Choice Model for Calgary KJ Stefan, City of Calgary JDP McMillan, City of Calgary CR Blaschuk, City of Calgary JD Hunt,
Relationship between Land Use and Transportation by Rae J. Furlonge.
The problem isn’t just the bridges, or the freight system, it’s about Oregon’s economy and quality of life. Oregon Modeling Steering Committee OREGON DEPARTMENT.
Simulating Cities: An Overview of the ILUTE Approach
Transportation Planning Analysis Unit, Transportation Development Division TRB Innovations in Travel Modeling Conference The Path to a Staged Implementation.
Waikato Regional Transportation Model A Strategic Tool for Land Use and Transport Investigations SPN Meeting, November 2015.
Chelan County Transportation Element Update
Oregon Statewide Integrated Model
Presentation transcript:

Moving Into Practice by JD Hunt, University of Calgary PROCESSUS Second International Colloquium Toronto ON, Canada June 2005

Overview Introduction Topic: Taking PROCESSUS results into practice Motivations Examples Commercial Movement Micro-simulation Stop Duration Modelling Growing Tours and Hybrid Tours PECAS Theoretical Structure Conclusions

Introduction How PROCESSUS work has moved into practice (PRACTUS?) Holy Grail: Theoretical advances that Have practical implications Make things easier Increase fidelity and accuracy

Introduction Practical interaction important Have potential impacts Directed to specific problems Scheduling discipline Funding and data collection Engineering is Applied Science

Introduction Practical interaction important - essential Have potential impacts Directed to specific problems Scheduling discipline Funding and data collection Engineering is Applied Science

Examples Commercial Movement Micro-simulation Calgary, Ohio, Los Angeles Stop Duration Modelling Calgary, Edmonton Growing Tours and Hybrid Tours Calgary, Edmonton PECAS Theoretical Structure Integrated and Connected Spatial Economics Behavioural Space Development Oregon, Sacramento, Edmonton, Baltimore, Alberta, Ohio

Examples Commercial Movement Micro-simulation Calgary, Ohio, Los Angeles Stop Duration Modelling Calgary, Edmonton Growing Tours and Hybrid Tours Calgary, Edmonton PECAS Theoretical Structure Integrated and Connected Spatial Economics Behavioural Space Development Oregon, Sacramento, Edmonton, Baltimore, Alberta, Ohio

Commercial Vehicle Movements Vehicles operated for commercial purposes As opposed to household, personal movements Includes ‘non-commercial’ non-household purposes (government, not-for-profit) Comprise 10-15% of total urban traffic

Some Examples Commercial Hauling freight for a company Service workers visiting clients Sales meetings Mail Delivering parcels Personal Travel to work Travel to school Shopping Leisure trips Social visits

Data 2001 Commercial Movement Study All commercial movements Not just freight Not just trucks 3,100 establishments in Calgary 4,300 establishments in Edmonton 24 hour stop diary Firmographics Employment structure Vehicle fleet

Tour-based Micro-simulation Considers tours rather than individual trips Micro-simulation of each tour

Establishment Client

Establishment Client

Tour-based Micro-simulation Considers tours rather than individual trips Micro-simulation of each tour Uses additional information for decisions Full-tour conditions Location of establishment (tour-base) Work-shift influences Simulates each trip as tour progresses Closer to reality A number of clients scattered throughout city Efficient businesses will service them in tours

Micro-simulation Process Tour Generation Tour Start Vehicle and Tour Purpose Next Stop Purpose Next Stop Location Stop Duration Iterative

Establishment Client Lunch Return to Establishment Other Goods / Service

Stop Duration Private Service - Service - Light

Micro-simulation Process Start Time Next Stop Purpose Return Service Goods Other Tour Generation Vehicle and Tour Next Stop Is At Establishment Location Next Stop Location Stop Duration

Micro-simulation Process Start Time Next Stop Purpose Return Service Goods Other Tour Generation Vehicle and Tour Next Stop Is At Establishment Location Next Stop Location Tour starting in zone 340 (Central Industrial) AM Peak Stop Duration

Micro-simulation Process Start Time Next Stop Purpose Return Service Goods Other Tour Generation Vehicle & Tour Next Stop Is At Establishment Location Next Stop Location Tour starting in zone 340 (Central Industrial) AM Peak Light vehicle; service tour Stop Duration

Micro-simulation Process Start Time Next Stop Purpose Return Service Goods Other Tour Generation Vehicle and Tour Next Stop Is At Establishment Location Next Stop Location Tour starting in zone 340 (Central Industrial) AM Peak Light vehicle; service tour Current time: 7:22 AM Stop Duration

Micro-simulation Process Start Time Next Stop Purpose Return Service Goods Other Tour Generation Vehicle and Tour Next Stop Is At Establishment Location Next Stop Location Tour starting in zone 340 (Central Industrial) AM Peak Light vehicle; service tour Current time: 7:22 AM Service stop Stop Duration

Micro-simulation Process Start Time Next Stop Purpose Return Service Goods Other Tour Generation Vehicle and Tour Next Stop Is At Establishment Location Next Stop Location Tour starting in zone 340 (Central Industrial) AM Peak Light vehicle; service tour Current time: 9:48 AM Service, 211 (Stampede) Stop Duration

Micro-simulation Process Start Time Next Stop Purpose Return Service Goods Other Tour Generation Vehicle and Tour Next Stop Is At Establishment Location Next Stop Location Tour starting in zone 340 (Central Industrial) AM Peak Light vehicle; service tour Current time: 9:48 AM Service, 211 (Stampede) Service stop Stop Duration

Micro-simulation Process Start Time Next Stop Purpose Return Service Goods Other Tour Generation Vehicle and Tour Next Stop Is At Establishment Location Next Stop Location Tour starting in zone 340 (Central Industrial) AM Peak Light vehicle; service tour Current time: 11:21 AM Service, 211 (Stampede) Service, 209 (Apartment) Stop Duration

Micro-simulation Process Start Time Next Stop Purpose Return Service Goods Other Tour Generation Vehicle and Tour Next Stop Is At Establishment Location Next Stop Location Tour starting in zone 340 (Central Industrial) AM Peak Light vehicle; service tour Current time: 11:21 AM Service, 211 (Stampede) Service, 209 (Apartment) Other stop Stop Duration

Micro-simulation Process Start Time Next Stop Purpose Return Service Goods Other Tour Generation Vehicle and Tour Next Stop Is At Establishment Location Next Stop Location Tour starting in zone 340 (Central Industrial) AM Peak Light vehicle; service tour Current time: 12:13 PM Service, 211 (Stampede) Service, 209 (Apartment) Other, 2205 (Marathon rest.) Stop Duration

Micro-simulation Process Start Time Next Stop Purpose Return Service Goods Other Tour Generation Vehicle and Tour Next Stop Is At Establishment Location Next Stop Location Tour starting in zone 340 (Central Industrial) AM Peak Light vehicle; service tour Current time: 12:13 PM Service, 211 (Stampede) Service, 209 (Apartment) Other, 2205 (Marathon rest.) Service stop Stop Duration

Micro-simulation Process Start Time Next Stop Purpose Return Service Goods Other Tour Generation Vehicle and Tour Next Stop Is At Establishment Location Next Stop Location Tour starting in zone 340 (Central Industrial) AM Peak Light vehicle; service tour Current time: 4:20 PM Service, 211 (Stampede) Service, 209 (Apartment) Other, 2205 (Marathon rest.) Service, 2312 (North Hill Mall) Stop Duration

Micro-simulation Process Start Time Next Stop Purpose Return Service Goods Other Tour Generation Vehicle and Tour Next Stop Is At Establishment Location Next Stop Location Tour starting in zone 340 (Central Industrial) AM Peak Light vehicle; service tour Current time: 4:20 PM Service, 211 (Stampede) Service, 209 (Apartment) Other, 2205 (Marathon rest.) Service, 2312 (North Hill Mall) Return to establishment Stop Duration

Micro-simulation Process Start Time Next Stop Purpose Return Service Goods Other Tour Generation Vehicle and Tour Next Stop Is At Establishment Location Next Stop Location Tour starting in zone 340 (Central Industrial) AM Peak Light vehicle; service tour Current time: Service, 211 (Stampede) Service, 209 (Apartment) Other, 2205 (Marathon rest.) Service, 2312 (North Hill Mall) Return to establishment, 340 Stop Duration

Micro-simulation Process Start Time Next Stop Purpose Return Service Goods Other Tour Generation Vehicle and Tour Next Stop Is At Establishment Location Next Stop Location Tour starting in zone 340 (Central Industrial) AM Peak Light vehicle; service tour Current time: Service, 211 (Stampede) Service, 209 (Apartment) Other, 2205 (Marathon rest.) Service, 2312 (North Hill Mall) Return to establishment, 340 Tour starting in zone 2604 (NW residential) Stop Duration

Operation PTM (EMME/2) Commercial Movements Model (micro-simulation) Updated travel times Run of modelRun of process Updated commercial vehicle trip tables Updated personal trip tables Base Information Re-assignment of trip tables

Model network loading of light vehicle flows

Model network loading of heavy vehicle flows less in CBD; more in industrial areas little on non- truck routes

Results Being used for practical policy analysis A number of demonstration policy tests considered here Five scenarios: Base case Increased cost of travel (per km) Increased travel time Removed truck route restrictions Instituted large toll for stops in CBD

Overall proportion of base

VKT proportion of base

Truck Routes Removed Scenario vs. Base Case

Calgary Conclusions Tour-based micro-simulation approach used here Successful Provides direct representation of trip-chaining impacts Includes service delivery Well beyond ‘freight only’ and ‘large heavy vehicle’ limitations Useful planning tool for Including commercial movements and their impacts on system Assessing impacts of transportation policy and infrastructure development on commercial sectors

Calgary Acknowledgements Funding City of Calgary City of Edmonton Province of Alberta SSHRC - MCRI Participation Kevin Stefan, Karen Tsang Ali Farhan, Dianne Atkins, Paul McMillan Alan Brownlee, Bob Ishani, Ian Bakker, John Abraham

Examples Commercial Movement Micro-simulation Calgary, Ohio, Los Angeles Stop Duration Modelling Calgary, Edmonton Growing Tours and Hybrid Tours Calgary, Edmonton PECAS Theoretical Structure Integrated and Connected Spatial Economics Behavioural Space Development Oregon, Sacramento, Edmonton, Baltimore, Alberta, Ohio

P roduction E xchange C onsumption A llocation S ystem

year tyear t+1 region-wide economic activity interactions commercial movements household travel transport networks transport times and costs space development space prices activity locations and interactions trip patterns activity quantities activity benefits transport policy economic trends economic policy land use policy space changes region-wide economic activity interactions commercial movements household travel transport networks activity locations and interactions trip patterns activity quantities Economic Model PECAS Travel Model transport impacts land consumption activity benefits

$ $$ $ $ $ $ $$ $ $ $ $ $ $$ $ $ $ Producing Sectors Goods, Services, Labour and Space Consuming Sectors $ $ $$ $ $ $ $ $ $ $ $ $ $ $ $ Economic Flows

total consumption total production total production total production buying allocation process commodity flows exchange zone exchange zone exchange zone selling allocation process Economic Interactions: Production - Exchange - Consumption

total consumption total production total production total production buying allocation process commodity flows exchange zone exchange zone exchange zone selling allocation process Economic Interactions: Production - Exchange - Consumption ‘Integrated’ and ‘Connected’

composite utility of technology for activity a at an activity location zone z: Location Specific Utility of Technology CUTech a,z = ( 1/ p,a ) · ln (  p  P exp ( p,a · UTech a,z,p ) ) with: UTech a,z,p =  prod,a · UProd a,p,z +  cons,a · UCons c,p,z + UTechRef a,p UCons a,p,z =  c  C R a,c,p ·  r,a,c,p · CUBuy c,a,z UProd a,p,z =  c  C M a,c,p ·  m,a,c,p · CUSell c,a,z -combines vector of accessibilities into single – SINGLE – ‘composite utility of technology’ value, - each accessibility in vector associated with a given commodity produced or consumed, combination consistent with technology

composite utility of technology for activity a at an activity location zone z: Location Specific Utility of Technology CUTech a,z = ( 1/ p,a ) · ln (  p  P exp ( p,a · UTech a,z,p ) ) with: UTech a,z,p =  prod,a · UProd a,p,z +  cons,a · UCons c,p,z + UTechRef a,p UCons a,p,z =  c  C R a,c,p ·  r,a,c,p · CUBuy c,a,z UProd a,p,z =  c  C M a,c,p ·  m,a,c,p · CUSell c,a,z -combines vector of accessibilities into single – SINGLE – ‘composite utility of technology’ value, - each accessibility in vector associated with a given commodity produced or consumed, combination consistent with technology

Examples in Oregon Initial Model Application

US 97 US 385 New Eastern Oregon Freeway Land use growth/shift resulting from new freeway

US 97 US 385 New Eastern Oregon Freeway Land use growth/shift resulting from new freeway

US 97 US 385 New Eastern Oregon Freeway Land use growth/shift resulting from new freeway

* Medium and high crack density Local Bridges State Bridges Ford’s Bridge Cole’s Bridge Sauvie Island Bridge McKenzie/Willamette River Bridges Weight Limited Bridge Cracked Bridge Oregon Bridge Options Study Economic Equity Impacts Broadened Policy Discussion

Oregon Bridge Options Study

Regional Production Relative to Current Mobility Option

Oregon Bridge Options Study Resulting Staged Approach

Willamette Valley Forum (Oregon) Highway Expansion High Speed Transit VMT TaxLess Land Supply HH Growth Compared to Reference Case Many Less Than RC Same as RC Many More Than RC Compared land use forecasts under various policies Collaborative visioning

Oregon Acknowledgements Funding State of Oregon United States Federal Highway Administration Participation John Abraham Rick Donnelly, Tara Weidner, Christi Willisden, Jim Hicks, Carl Batten, Pat Costinett, Susan Hendricks, Bill Davidson, Tim Heier, Joel Freedman, Larry Conrad, Tracey Lauritsen, Paul Waddell Bill Upton, Brian Gregor

Conclusions PROCESSUS is contributing to PRACTICE Some theoretical advances with large practical implications Large infrastructure investments Some Holy Grails Investment that pays off in future Still too much reliance on choice models More simple rule-based systems Faster computations Emergent behaviour Role for PROCESSUS