Travel Modelling Group - PowerPoint Presentation

1. Travel Modelling GroupTechnical Advisory CommitteeSeptember 11, 20131

2. Today’s AgendaSoftware ImprovementsNew TMG Toolbox ToolsNetwork PackagesNetwork Comparison2001 / 2012 Base Network ProgressMethodologyCoding of Transit-Only LanesPresentation on GTAModel Version 4.0+Design FeaturesRoadmapData Requirements2

3. Software Improvements - ToolsAnalysis:Transit line boarding counts for comparison against TTSZone adjacency matrix construction using zonal geometryNetwork EditingTool for deleting transit stops occurring on highwaysTool for matching network rotationNetwork optimization tool – converts cosmetic nodes to link shape vertices on a subset of links. 3

4. Software Improvements - NWPNetwork Package (NWP) File Format:Compressed packaging of a single scenario (modes, nodes, links, turns, lines, link shapes) for easy sharing.The Input / Ouput folder in the TMG Toolbox has tools for importing/exporting network packages.Compression ratio ~ 90% e.g., a network which is 10MB as batch files will only be 1MB.Also exports / imports extra attributes (Emme 4 only)4

5. Software Improvements – Network ComparisonBased on Network Correspondence File for a primary scenario and a secondary scenarioAll nodes in both scenarios get assigned a twin from the other scenarioAll links in both scenarios get assigned a list of twins from the other scenario to account for link splittingTwinning is based on node proximity, not node or link ID!Currently two tools use the correspondence file:“Flag Twinned Links and Nodes” computes extra attribute indices based on comparison“Copy New Elements” copies untwinned elements from the secondary scenario into the primary scenario5

6. 2011 / 2012 Network Progress Base 2011 Network is complete; still waiting on feedbackGTFS stop locations are being used to update the 2011 base network to a 2012 base network with transit.New links have been identified by GTFS stop locations, and were created in 2012.The 2012 base network will contain a node for every GTFS stop grouping.Transit itineraries will be generated from GTFS data; with some data cleaning.The 2012 base network will support full-day modelling6

7. Base Network Progress – Transit Only LanesCurrent Example: Spadina, St. ClairThe issue: This works well for network representation, but can become an issue when using GTFS stop locations to generate transit schedules.7ccccuuucsslslslsl

8. Transit-Only Lanes: Proposed SolutionFlag links with transit-exclusive ROW with new mode ‘X’ (Emme 4 permits 52 modes, so ‘X’ is a different mode from ‘x’).Manually / programmatically calculate transit vehicle equivalentsA similar procedure can be used to implement transit speed updatingThis frees up the ‘L’ and ‘Q’ modes. For example, ‘L’ could be reserved for standard-gauage LRVs (e.g., Eglinton Crosstown line)8

9. GTAModel V4.0Eric J. Miller, Ph.D.James Vaughan & Peter KucirekTravel Modelling Group, University of TorontoTechnical Advisory Committee PresentationSeptember 11, 2013Toronto,

10. Key FeaturesMicrosimulation24-hour weekday“Continuous” generation of activity/trip start times4 (maybe 5?) time periods for network assignmentsAM PeakMid-dayPM PeakEvening/night (maybe split?)TTS2012 basedActivity/tour-basedSame inputs as a 4-step model:Population & employment by zoneEmme road and transit assignments to generate travel times/costs

11. Microsimulation (1)Zone population is synthesized into individual persons with specific age, employment status, occupation, school status and driver’s license.Persons assigned to households with a given number of cars.Zone employment is synthesized into individual jobs by occupation type.

12. Microsimulation (2)In V4.0, observed TTS distributions will be used for synthesis.Basically what is done in GTAModel 2.0, 2.5, GGH Model.Distributions can be updated on a scenario version.Future versions can implemented more sophisticated synthesis procedures (or, perhaps someday be driven by the demographic component of a land use model).

13. Microsimulation (3)Advantages:Processing a list of persons is faster than processing many large matrices. As soon as one starts to disaggregate trip-makers by occupation, age, etc. list-based calculations are far more efficient.E.g., matrix-based HBW work mode split calculations for approximately 2000 zones, 4 occupation groups, FT/PT workers = 4x106x4x2 = 32x106 nested logit model calculations to model mode choice for approx. 2.5x106 workers!

14. Microsimulation (4)Advantages, cont’d:Eliminates aggregation problems within the mode choice modelProvides detailed distributions of behaviour and impacts by type of trip-maker (any type of aggregation of trips, etc. is possible).Simplifies model calculations.

15. 24-Hour ModellingGTHA needs 24-hour modelling capabilityPM peak is now the dominant peakEnergy/emissions calculations require 24-hour analysisEconomic evaluation really requires 24-hour analysisOff-peak transit markets need to be analyzed.

16. 2012 TTSIt was originally proposed to build a 2006 version of the model and then update it once 2012 TTS data were available.Given the eminent release of the 2012 data we believe it makes sense to go directly to the 2012 model.Also, the Emme 2012 24-hour transit network is closer to readiness than the 2006 24-hour network and is a higher priority for completion for a variety of applications.

17. Activity/Tour-Based ModelIt was originally proposed to build a “simple” tour-based model as a logical extension of current GTAModel and GGH Model practice (which effectively generate simple H-Work-H and H-School-H tours).In attempting to design this model, however, significant complications soon arose wrt modelling shopping and other-purpose trips in a “simplified” way (i.e., it quickly became “not simple”).It also became clear that we already had a solution to this problem in the TASHA model that has been under development and testing at UofT for the past decade.We therefore propose to re-estimate TASHA using 2012 TTS data as the GTAModel 4.0 model system.

18. TASHA: AdvantagesAdvantages of using TASHA include:Fully operational code already exists within XTMF, thereby minimizing the amount of new code that will need to be generated.TASHA deals with all trip purposes in a relatively simple, straightforward way but generates tours of arbitrary complexity in a computationally very efficient manner.Considerable experience with TASHA already exists that can be applied to the new version.We feel strongly that trying to invent a “simple” tour-based model represents an inferior solution and use of resources than a direct implementation of TASHA.

19. TASHA: FeaturesAgent-based microsimulation; models both persons and households.Activity-based – generates 24-hour weekday out-of-home activity patterns.Tour-based: tours are emergent out of the scheduling of out-of-home activities. Mode choice is tour-based. Arbitrarily complex tours can be generated and handled efficiently.Household-based: detailed auto availability & allocation models determine mode choice decisions.Interfaces with both Emme and MATSIM (and, indeed, any network model).Can be used as a replacement for the first 3 stages in a 4-step model (with standard 4-step inputs) or as the travel demand component in an integrated transport-land use model system).Model parameters can all be developed from TTS data (i.e., no special surveys are required).In addition to the Toronto implementation, TASHA has been applied for research purposes in Montreal, London UK and Changzhou China.

20. TASHA Class StructureWorldHouseholdsEpisodeDistributionsSpatialRepresentationPersonsPersonProjectsPersonProjectAgendaIndividualActivityEpisodesPersonScheduleHouseholdProjectAgendaJoint ActivityEpisodesZonesDistanceMatrixTravel TimeMatricesHouseholdProjectsTravelEpisodesIndividual &Joint ActivityEpisodesPersons exist within households. This allows TASHA to deal explicitly with: Vehicle allocation Ridesharing Joint activities/trips Serve-dependent activities/trips

21. Project TypesWorkProjectSchoolProjectShoppingProjectOtherProjectPerson-LevelProjectsJoint ShoppingProjectJoint OtherProjectServe DependentProjectHousehold-LevelProjectsThe current project structure is quite crude: it reflects that available data used to build the model (an ordinary one-day household travel survey).

22. Activity SchedulingProject 1 episode 1.1 episode 1.2 ….Project 2 episode 2.1 episode 2.2 ….Project N episode N.1 episode N.2 ….Day 1Day 2Day 3Day 4Day 5Day 6Day 7…TASHA is an activity scheduling model in which individual activity episodes are generated and then explicitly scheduled. Out-of-home activity patterns and their associated trip-chains (tours) are thus “built from scratch” rather than selected from a pre-specified set of feasible patterns. Thus, travel patterns dynamically adjust to changes in transportation level of service, activity system “supply”, changes in household and personal constraints and needs, etc.

23. Joint Activities….….Day nPerson 1….….Day nPerson 2Joint ShoppingActivity:Duration: 2 hrsLocation: The MallSearch for feasiblejoint time slot

24. Serve DependentsDaycareAt-HomeAt-HomeChild’s ScheduleAt-HomeAt-HomeAdult 1 ScheduleAt-HomeAdult 2 ScheduleWorkShoppingTake child to/from daycare

25. Vehicle Allocation within TASHATASHA assigns household vehicles to drivers based on overall household utility derived from the vehicle usage. Drivers not allocated a car must take their second-best mode of travel.

26. Household Ridesharing Options in TASHAWithin-household ridesharing is explicitly handled within TASHA. Drivers will “offer” rides to household members if a net gain in household utility is obtained and feasibility criteria are met.

27. PDFActivityFrequencyActivityFrequencyJointPDFStartTimeFeasibleStart TimesStartTimeJointPDFDurationFeasibleDurations(a) Draw activityfrequency frommarginal PDF(b) Draw activity starttime from feasibleregion in joint PDF(c) Draw activityDuration fromfeasible region injoint PDFActivity Episode Frequency, Start Time and Duration Generation At – HomeWorkWorkShop 1Shop 2OtherOtherWork ProjectSchool ProjectOther ProjectShopping ProjectShop 1At-homeOtherShop 2Person Schedule= “Gap” in Project Agenda= Activity Episode= Travel EpisodeAt-homeAt-home::Scheduling Activity Episodes into a Daily ScheduleTASHA generates the number of activity episodes from a set of “projects” that a person (or household) might engage in during a typical weekday. It also generates the desired start time and duration of each episode.It then builds each person’s daily schedule, adjusting start times and durations to ensure feasibility.Travel episodes are inserted as part of the scheduling process.

28. Tour-Based Mode ChoiceChain c:1. Home-Work2. Work-Lunch3. Lunch-Meeting4. Meeting-Work5. Work-Homem1m2m3m4m5Non-drive option for Chain cm1 = driveSub-Chain s:2. Work-Lunch3. Lunch-Meeting4. Meeting-Workm2m3m4Non-drive for Sub-chain sm2 = drivem3 = drivem4 = driveDrive forSub-chain sm5 = driveDrive Option for Chain cmN = mode chosen for trip NTASHA’s tour-based mode choice model: Handles arbitrarily complex tours and sub-tours. without needing to pre-specify the tours Dynamically determine feasible combinations of modes available to use on tours. Modes can be added without changing the model structure. Cars automatically are used on all trips of a drive tour.

29. Treatment of TimeModels all out-of-home activities and trips for a 24-hour typical weekday5 minute time increments are used for start times and durations/travel timesProvides great temporal detail but is computationally very efficient (integer storage & calculations)Trips can be aggregated to whatever level of temporal detail/categorization is required by the network assignment modelDeals naturally with “peak-spreading”, etc.Provides excellent detail for environmental impact analysis

30. FlexibilityTASHA has been designed to be very flexible in terms of its development and its application.It has been developed using ordinary trip-based survey data for the GTA (but it could also exploit activity-based survey data).It can be used as a direct replacement for the first 3 stages in a 4-step system, or integrated within a full microsimulation model system.The data requirements for model development are no greater than other current models, including conventional trip-based models.Usable in a variety of contexts, and facilitates the evolution of the model system over time from aggregate to microsimulation.

31. Application in a conventional settingPop & Empby zoneSynthesize persons, hhlds& work/school locationsTASHAStandard zone-based, staticroad & transit assignmentStandard 4-step zone-based inputsStandard network assignment package (EMME, Vissum, etc.)TASHA contains its own synthesis procedures to convert aggregate, zone-based inputs into disaggregated persons, etc. required for microsimulation

32. Base Year Census Data,Other Aggregate DataSynthesize Base Year Population,Employment, Dwellings, etc.ILUTE Evolutionary EngineFor T = T0+1,T0+NT do: Demographic Update Building Stock Update Residential Housing Commercial Floorspace Firm/Job Location Update Household Composition Update Work/school Participation & Location Update Residential Location Update Auto Ownership UpdateExogenous Inputs, Time T In-migration Policy changes …Dynamic Network Assignment Model(meso- or micro-scopic)T0 = Base time pointT = Current time point being simulatedNT= Number of simulation time steps Travel Models Commercial Vehicle Movement Update Activity/Travel Update (TASHA)Application in a full microsimulation setting

33. Current StatusTASHA was developed using 1996 travel survey data for the GTHA.The activity scheduler has been validated against 2001 survey data.Interfaces with both EMME and MATSIM.TASHA has been used for several environmentally related studies in the GTHA.Has been applied in Montreal, London, Changzhou.

34. Environmental Modeling with TASHATASHA has been connected with:EMME/2 road & transit network assignment model (link speeds & volumes by hour of day) MOBILE6.2C emissions model (link emissions by type by link by time of day)CALMET meteorological modelCALPUFF dispersion model (pollutant concentrations by zone by time of day)Dynamic population exposure to pollution by zone by time of day!!

35. Persons& HouseholdsAuto & TransitTravel Times/CostsTASHA Activity/TravelSchedulerActivityPatterns &Trip ChainsTrips By Mode,Vehicle Type &Time of DayTransportationNetwork ModelVKT by FacilityType, etc.Hot/Cold Soaks,Cold Starts, etc.Emissions ModelMobile SourceEmissionsDispersionModelLocations ofPeople byTime of DayExposure toPollutionHousehold AutoOwnership ModelVehicle AllocationModelLand Use PoliciesVehicle TechnologyTransportation Policies(Road pricing, carbon taxes, transit investment, etc.)EXAMPLE INTERVENTIONS

36. Auto Emissions by location and time of dayLink-based running emissions by time of dayZone-based soak emissions by time of day

37. Dispersion of Emission Concentrations

38. Zone NO2 Exposures

39. TASHA-MATSIMMore recently TASHA has been linked with MATSIM, an agent-based micro/meso-scopic network simulator.MATSIM allows us to keep track of individual agents as they travel through the network so we can accumulate their emissions (and, eventually, their exposure to pollutants).It also provides us with rudimentary vehicle dynamics, allowing a more detailed calculation of vehicle emissions.

40.

41. Implementing TASHA as GTAModel 4.0TASHA assumes:Known work & school locations for all workers & studentsKnown number of cars per householdThese models need to be added to TASHA (but would also have to be created for any V4.0 design)Will use:Doubly-constrained entropy PORPOW model (similar to GTAModel V2.0, V2.5 & GGH Model)Singly-constrained logit PORPOS model (similar to GGH Model)Simple logit household-based car ownership model

42. GTAModel V4.0Pop & Emp by ZoneSynthesize persons, households & jobsHousehold Car OwnershipPORPOWPORPOSTASHA Activity generation Activity scheduling Tour-based model choice Auto allocation RidesharingEmme Road & Transit Assignments by Time PeriodConverged?STOPNoYes

43. GTAModel V4.0Pop & Emp by ZoneSynthesize persons, households & jobsHousehold Car OwnershipPORPOWPORPOSTASHA Activity generation Activity scheduling Tour-based model choice Auto allocation RidesharingEmme Road & Transit Assignments by Time PeriodConverged?STOPNoYesIncludes shopping & other-purpose episode location choices (tour-context sensitive)

44. GTAModel V4.0 TasksModels to estimate:Household auto ownership levelPORPOWPORPOSShopping episode location choiceOther-purpose episode location choiceActivity episode generation ratesTour-based mode choice model (including car allocation & ridesharing models – jointly estimated)

45. Current Status2012 24-hour Emme network will be ready “soon” (end of month?).Other data required being assembled (parking costs, fares, tolls, …).Will be ready to start estimating models as soon as TTS2012 available.Most models can be developed in parallel, expediting development time.3-4 month development time to get the point where the model system can be operationally tested by City of Toronto (and anyone else wishing to do so).

46. Cloud ComputingEarlier this week we successfully connected to the SOSCIP* cloud computing facility.This means that we can use the cloud to estimate the V4.0 models, greatly accelerating model estimation time.This will be particularly helpful for the tour-based mode choice models which are very computationally intensive to estimate.* Southern Ontario Super-Computing Innovation Platform. This is a joint venture of IBM Canada, Province of Ontario, Gov’t of Canada and most southern Ontario universities (led by UofT and Western) to provide the most powerful computing facilities in Canada to Ontario researchers and industry.

47. RisksTTS 2012 availability?Under-reporting of trips, especially in the PM peak.May need to calibrate the activity generation rates to improve fit to screenline counts by time of day.

48. Thank You!48

49. 49

50. GTAModel V4 – Data Requirements2012 zonal parking costs2012 station capacities and costs (already provided by Metrolinx)2012 average adult transit fare for all agencies407ETR 2012 tolls50

51. Other Transit Lane Configurations51ccsslcsxcsxcsxccsslcscscsVdf=60 or @xrow=1 or type=???ccscccccccssssuuuuuuSeaparated ROW ramp to terminalSurface ROW, exclusive lanesSurface ROW, mixed lanesProposed SolutionAlternative 1Alternative 2