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ORGANIZING REGIONAL TRANSPORTATION DATA AND PLANNING: THE MONTREAL EXPERIENCE

ORGANIZING REGIONAL TRANSPORTATION DATA AND PLANNING: THE MONTREAL EXPERIENCE. Toronto, 25 novembre 2010. Daniel Bergeron Director of Urban and Transportation Data. PRESENTATION OUTLINE. AMT AT A GLANCE DATA COLLECTION MODELLING PARTNERSHIP. AMT AT A GLANCE. TORONTO

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ORGANIZING REGIONAL TRANSPORTATION DATA AND PLANNING: THE MONTREAL EXPERIENCE

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  1. ORGANIZING REGIONAL TRANSPORTATION DATA AND PLANNING: THE MONTREAL EXPERIENCE Toronto, 25 novembre 2010 Daniel Bergeron Director of Urban and Transportation Data

  2. PRESENTATION OUTLINE AMT AT A GLANCE DATA COLLECTION MODELLING PARTNERSHIP

  3. AMT AT A GLANCE

  4. TORONTO Population 6,0 M Service Area 8 700 km2 Municipalities 26 Annualridership600 M VANCOUVER Population2,3 M Service Area 1 800 km2 Municipalities21 Annualridership180 M CANADA’S LARGEST REGIONS • MONTRÉAL • Population 3,6 M • Service Area 4 000 km2 • Municipalities 83 • Annualridership470 M • Transit Operators 15

  5. AMT’S MISSION AND MANDATES CREATION Created in 1995 by the Quebec government MISSION INCREASE ridership and public transport services to improve commuting efficiency PLAN, coordinate, integrate and promote public transport services with partners ROLES STRATEGIC PLANNER with an integrated vision of regional mobility PRINCIPAL CONTRACTOR on metropolitan public transport projects OPERATOR of commuter trains, express buses, reserved lanes, metropolitan terminuses and park-and-ride facilities REDISTRIBUTOR of financial assistance to other transport organizations

  6. AMT’S SENIOR EXECUTIVES HUMAN RESSOURCES CORPORATE AFFAIRS PRESIDENT AND CEO INTERNAL AUDITOR FINANCE INNOVATION & PLANNING OPERATIONS COMM. & MARKETING SECURITY & SAFETY ENGINEERING & CONSTRUC. URBAN & TRNSP DATA

  7. URBAN AND TRANSPORTATION DATA DIRECTOR ASSISTANT STRATEGIC DATA MODELLING FARE / FUNDING CHIEF CHIEF CHIEF ANALYST MARKET RESEARCH ANALYST CENSUS & CUSTOMMER DATA SPECIALIST MODELLING SPECIALIST MODELLING AND SMART CARD DATA ANALYST MOBILITY DATA ANALYST MODELLING ANALYST FUNDING FRAMEWORK ANALYST GIS ANALYST SURVEY ANALYST TECHNICIAN TECHNICIAN

  8. DATA COLLECTION MONTREAL’S REGIONAL TRAVEL SURVEY (ENQUÊTE ORIGINE-DESTINATION)

  9. DATA COLLECTION MONTREAL’S REGIONAL TRAVEL SURVEY (ENQUÊTE ORIGINE-DESTINATION) • General idea • The major public institutions are responsible for the travel survey. Therefore, they: • Are accountable for the surveys and their content • Ensure the maintenance of expertise within public institutions... and, more generally, in the Montreal community • The university milieu is strongly implicated in the data collection and treatment; it also act as scientific advisor to the survey technical committee

  10. TRAVEL SURVEY ORGANIZATIONAL STRUCTURE Public body Steering committee AMT, STM, RTL, STL, ACIT, MTQ, MAMR Universityenvironment Secretariat AMT Privatefirm Permanent structure Administration Archives Technicalcommittee AMT, STM, RTL, STL, ACIT, MTQ, MAMR Scientificadvice École Polytechnique de Montréal Analysis Diffusion Advice Support Project manager Call centre Polling firm SampleControl ProductivityControl Survey software Universityresearch group École Polytechnique de Montréal Project Team • QualityControl Analysis and advice Universityresearch group École Polytechnique de Montréal

  11. Adaptedfrom Dr Robert Chapleau École Polytechnique de Montréal MONTREAL’S REGIONAL TRAVEL SURVEY

  12. From Dr Catherine Morency École Polytechnique de Montréal TOTALLY DISSAGGREGATED DATA Population density Aggregated data thru zonal system Population density TotallyDisaggregated data

  13. From Dr Catherine Morency École Polytechnique de Montréal CONCEPTUAL DATA AND APPLICATION FRAMEWORK

  14. Observedurbanmobility Shopping Leisure Work Other Study Travel Survey Census Transportation models Households Persons Progression of Activityrythms TRIPS Household and Person Attributes Automobiles Population « day » POPULATION «  night » Residential location patterns Activity location patterns Consumption of transportation resources … Land Use models TRANSPORTATION NETWORK Network coverage Home Place of Activity Activity links Dynamics of residential construction Location of activities TERRITORY Urban and Transportation Network Database

  15. MODELLING

  16. MODELLING • General idea, especially for transit modelling • Coherence of data, instruments and methodsused for data collection, service planning, projectevaluation, management and financing of public services and equipment • Autonomy of major public institutions • Coherence of methods and tools • Increasing collaboration and sharing of data and expertise • Significantuniversity support in terms of tools, methods, training and scientificadvice.

  17. MODELLING DESCRIPTIVE MODELLING MODELLING PROSPECTIVE MODELLING CHALLENGE AND CONTEXT DATA COLLECTION DETAILED INFORMATIONAL INVENTORY

  18. MANAGEMENT OF PUBLIC SERVICES AND EQUIPMENT Fare revenue sharing Billing of costs/deficits Measure of redistributive effects UNDERLYING EVALUATION Measure of network usage by Descriptive survey of trip characteristics Validation of declared information Evaluation of network usage PROJECT/POLICY EVALUATION Service planning New infrastructure / service Subway extension / New commuter rail line / BRT line Policies (Fare, Parking, Congestion pricing,...) UNDERLYING EVALUATION Measure of impacts of a project/policy on Multimodal travel demand Network usage Derived indicators (GHG emissions, ...) CHALLENGE AND CONTEXT DESCRIPTIVE MODELLING Enrichment of collected data Route choice/ Travel time and distance / Network load PROSPECTIVE MODELLING Instrumentation of an interactive process Performance evaluation and assessment of solutions

  19. Population Census Mobility Travel survey Clientele On-board survey Ridership Neworks Sales Networks PT / Roads Geography Geomatics Forecasting Demand Evaluation Itineraries Evaluation Mode choice Simulation Itineraries Time Distance Trips Loads Networks DESCRIPTIVE MODELLING PROSPECTIVE MODELLING GENERAL APPROACH DETAILED INFORMATIONAL INVENTORY Route Characteristics Choice of Mode/route Calibration Planning of projects for the development of the passenger transport system Management and finance of shared services and infrastructure

  20. TYPICAL MODELLING PROCESS From Agence métropolitaine de transport DETAILED INFORMATIONAL INVENTORY MODELLING • Travel surveys • household • on-board • ticket buyers Travel demand Observed/ Projected • Transit simulation • Individualitineraries • Trip time/distance • Network flows • Indicators • Networks • Link flow • Trips • mode • routes (itineraries) • time / distance • Society • costs by individual/household • Environment • Emissions • Economy • Transport costs / benefits • Reference population • - demography • PT users • ticket sales Demographic projections • Mode transfer/choice • Transit • Bimodal • Auto Transit networks • Transport supply • Public transit Urbangeomatics • Territory • Borders • Barriers • Intermodal links • Road simulation • Travel time (impedance) • Volume Transport supply - Roads

  21. Adaptedfrom Ministère des transports du Québec TYPICAL MODELLING PROCESS Demand scenario Census (StatsCan) Transit counts Demographic projections Planning scenarios Results Transit simulation Trip seeding Economic projections Travel Demand Trip forecasting Mode transfer model Regional travel surveys Network effects Supply scenario Emissions and consumption Transit Network Road simulation Coded transit network Transit projects Cost/benefit analysis Intermodal facilities Traffic microsimulation Road Network Coded road network Road Project Traffic counts http://www.mtq.gouv.qc.ca/portal/page/portal/ministere/ministere/recherche_innovation/modelisation_systemes_transport/modele_transport_urbain_personnes

  22. INSTITUTIONAL COLLABORATION Steering committee AMT, STM, RTL, STL, ACIT, MTQ, MAMR Secretariat AMT Technicalcommittee AMT, STM, RTL, STL, ACIT, MTQ, MAMR TRAVEL SURVEY DATA Administration Archives Advice Support Scientificadvice École Polytechnique de Montréal Analysis Diffusion AMT MODELLING COMMITTEE (TRANSIT) AMT, STM, RTL, STL, ACIT, MTQ, VdM MTQ STM RTL STL ACIT VdM Committee Chair MODELLING Integration Documentation Scientificadvice École Polytechnique de Montréal

  23. RELATIONSHIPS BETWEEN MODELLING ORGANIZATIONS Academia Diffusion of OD survey data Travel survey Secretariat Public institutions Private firms Modelling committee AMT CIT STM VdM STL RTL MTQ Transit Transit Transit Transit Transit Roads Research and Scientific adv. Methodological support Education and training Analysis tools Commer. suppliers ÉcolePolytechnique de Montréal (MADITUC)

  24. METHODOLOGICAL FRAMEWORK Source: NCHRP 8-43 – Methods for ForecastingStatewide Freight Movements and Related Performance Measures Source: An Introduction to Urban Travel Demand Forecasting A Self Instructional Text U.S. DEPARTMENT OF TRANSPORTATION FEDERAL HIGHWAY ADMINISTRATION URBAN MASS TRANSPORTATION ADMINISTRATION 1977

  25. TRANSPORTATION MODELLING IN GREATER MONTREAL DISAGGREGATE INFORMATION-BASED PARADIGM THE FOUR STAGE TRANSPORTATION PLANNING PARADIGM Zone System Regional travel surveys 1. Trip generation Population X, Y, Size, Autos Origins / destinations Households Land use Age, Sex, License, Status Persons 2. Trip distribution Orig XY, Dest XY, Time, Purpose, Mode, Itinerary Network Trips Trips Travel costs 3. Mode split Territories New attributes TRANSIT Itineraries table Trips by mode ROAD O-D Matrix Network performance 4. Trip Assignment

  26. EXAMPLE OF COLLABORATION IN PUBLIC TRANSPORT MODELLING Representation of travel demand Regional projects Local projects Population forecasts by region Regional Travel survey Specialized surveys On-board surveys Insitut des Statistiques du Québec Population forecasts by small sector - Consideration of development capacity AMT, STM,RTL,STL, CIT, MTQ, MAMROT AMT, STM,RTL,STL,CIT MTQ Adjustments for the horizon year Local demand Trip forecasting - Disaggregate approach: OD factorization MTQ Regional travel demand for the horizon year Particular projects If necessary Commercial and residential development Demand for simulation of the horizon year Adjustment of regional demand Municipalities

  27. DEVELOPMENT AND RESEARCH AT AMT

  28. INVENTORY OF INFORMATION Continuous travel survey New indicators(annual and seasonal variations) Anticipation of major trends(permanent monitoring of important indices) DESCRIPTIVE MODELLING Exploitation of SMART CARD data Study of automobile itineraries Improved understanding of potential transit clientele Improved understanding of bimodal travel (kiss&rideand park&ride) PROSPECTIVE MODELLING Mode choice instead of mode transfer Based on a generalized costs and, potentially, on qualitative variables PERSPECTIVES FOR THE FUTURE DETAILED INFORMATIONAL INVENTORY PROSPECTIVE MODELLING DESCRIPTIVE MODELLING

  29. 1 1 2 2 3 3 4 4 SMART CARD DATA MODELS Boarding trip chains Imputation of the alighting stop 2 3 1 2 Continuous data collection (versus a single averageday) 4 3 1 4 Spatio-temporal distribution of traveldemand Trip itineraries (eg: travel times) Load profiles (eg: pass-km, MLP) Transfers Activity hubs TravelPurpose/Fréquency Temporal variation of traveldemand Traveller behaviour

  30. ANALYSIS OF AUTOMOBILE ITINERARIES Itinerary validation Example Declareditinerary: A-720 et A-20 Validateditinerary: A-720 et A-20 (declarationreproduced) Origine Origin Line 1 Line 2 Line n Destination A-720 A-20 Destination

  31. Thank you!

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