1. Travel Modelling Group Technical Advisory Committee
September 11, 2013

2. Today’s Agenda Software Improvements 2001 / 2012 Base Network Progress
New TMG Toolbox Tools
Network Packages
Network Comparison
2001 / 2012 Base Network Progress
Methodology
Coding of Transit-Only Lanes
Presentation on GTAModel Version 4.0+
Design Features
Roadmap
Data Requirements

3. Software Improvements - Tools
Analysis:
Transit line boarding counts for comparison against TTS
Zone adjacency matrix construction using zonal geometry
Network Editing
Tool for deleting transit stops occurring on highways
Tool for matching network rotation
Network optimization tool – converts cosmetic nodes to link shape vertices on a subset of links.

4. Software Improvements - NWP
Network 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)

5. Software Improvements – Network Comparison
Based on Network Correspondence File for a primary scenario and a secondary scenario
All nodes in both scenarios get assigned a twin from the other scenario
All links in both scenarios get assigned a list of twins from the other scenario to account for link splitting
Twinning 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 scenario

6. 2011 / 2012 Network Progress
Base 2011 Network is complete; still waiting on feedback
GTFS stop locations are being used to update the 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 modelling

7. Base Network Progress – Transit Only Lanes
Current Example: Spadina, St. Clair The issue: This works well for network representation, but can become an issue when using GTFS stop locations to generate transit schedules. c u cs sl

8. Transit-Only Lanes: Proposed Solution
Flag 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 equivalents
A similar procedure can be used to implement transit speed updating
This frees up the ‘L’ and ‘Q’ modes. For example, ‘L’ could be reserved for standard-gauage LRVs (e.g., Eglinton Crosstown line)

9. GTAModel V4.0 Eric J. Miller, Ph.D. James Vaughan & Peter Kucirek
Travel Modelling Group, University of Toronto
Technical Advisory Committee Presentation
September 11, 2013
Toronto,

10. Key Features Microsimulation 24-hour weekday TTS2012 based
“Continuous” generation of activity/trip start times
4 (maybe 5?) time periods for network assignments
AM Peak
Mid-day
PM Peak
Evening/night (maybe split?)
TTS2012 based
Activity/tour-based
Same inputs as a 4-step model:
Population & employment by zone
Emme 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 model
Provides 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 Modelling GTHA needs 24-hour modelling capability
PM peak is now the dominant peak
Energy/emissions calculations require 24-hour analysis
Economic evaluation really requires 24-hour analysis
Off-peak transit markets need to be analyzed.

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

17. Activity/Tour-Based Model
It 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: Advantages Advantages 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: Features
Agent-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 Structure
World
Households
Episode
Distributions
Spatial
Representation
Persons
Person
Projects
Project
Agenda
Individual
Activity
Episodes
Schedule
Household
Joint Activity
Zones
Distance
Matrix
Travel Time
Matrices
Travel
Individual &
Persons exist within households. This allows TASHA to deal explicitly with:
Vehicle allocation
Ridesharing
Joint activities/trips
Serve-dependent activities/trips

21. Project Types
Person-Level
Projects
Work
School
Shopping
Other
Project
Project
Project
Project
Household-Level
Projects
Joint Shopping
Joint Other
Serve Dependent
Project
Project
Project
The 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 Scheduling
Project 1
episode 1.1
episode 1.2 ….
Project 2
episode 2.1
episode 2.2 ….
Project N
episode N.1
episode N.2 ….
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. …
Day 1
Day 2
Day 3
Day 4
Day 5
Day 6
Day 7

23. Joint Activities Person 1 Person 2 Joint Shopping Activity:
Duration: 2 hrs
Location: The Mall
Search for feasible
joint time slot
Day n
Day n …. …. …. ….

24. Serve Dependents Child’s Schedule Adult 1 Schedule Adult 2 Schedule
At-Home
At-Home
Take child to/from daycare
Daycare
Work
At-Home
At-Home
Shopping
At-Home

25. Vehicle Allocation within TASHA
TASHA 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 TASHA
Within-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. = “Gap” in Project Agenda
TASHA 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.
Activity Episode Frequency, Start Time and Duration Generation
(a) Draw activity
frequency from
marginal PDF
(b) Draw activity start
time from feasible
region in joint PDF
(c) Draw activity
Duration from
feasible region in
joint PDF
Joint
PDF
Joint
PDF
Activity
Frequency
Start
Time
PDF
Start
Time
Duration
Activity
Frequency
Feasible
Start Times
Feasible
Durations
Scheduling Activity Episodes into a Daily Schedule
Work Project
Work
School Project
Other Project
Other
Shopping Project
Shop 1
Shop 2 : :
Person
Schedule
At-home
At – Home
Work
Shop 1
Other
Other
At-home
Shop 2
At-home
= “Gap” in Project Agenda
= Activity Episode
= Travel Episode

28. Tour-Based Mode Choice
Chain c:
1. Home-Work
2. Work-Lunch
3. Lunch-Meeting
4. Meeting-Work
5. Work-Home
Tour-Based Mode Choice
mN = mode chosen for trip N
Drive Option for Chain c
Non-drive option for Chain c
m1 = drive m5 m4 m3
Sub-Chain s:
2. Work-Lunch
3. Lunch-Meeting
4. Meeting-Work m2 m1
TASHA’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.
Drive for
Sub-chain s
Non-drive for
Sub-chain s
m2 = drive
m3 = drive
m4 = drive m4 m3 m2
m5 = drive 28

29. Treatment of Time
Models all out-of-home activities and trips for a 24-hour typical weekday
5 minute time increments are used for start times and durations/travel times
Provides 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 model
Deals naturally with “peak-spreading”, etc.
Provides excellent detail for environmental impact analysis

30. Flexibility
TASHA 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 setting
Pop & Emp
by zone
Standard 4-step zone-based inputs
TASHA contains its own synthesis procedures to convert aggregate, zone-based inputs into disaggregated persons, etc. required for microsimulation
Synthesize persons, hhlds
& work/school locations
TASHA
Standard zone-based, static
road & transit assignment
Standard network assignment package (EMME, Vissum, etc.)

32. Application in a full microsimulation setting
Base Year Census Data,
Other Aggregate Data
Application in a full microsimulation setting
Synthesize Base Year Population,
Employment, Dwellings, etc.
ILUTE Evolutionary Engine
For 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 Update
Exogenous Inputs, Time T
In-migration
Policy changes …
Travel Models
Commercial Vehicle Movement Update
Activity/Travel Update (TASHA)
T0 = Base time point
T = Current time point being simulated
NT= Number of simulation time steps
Dynamic Network Assignment Model
(meso- or micro-scopic)

33. Current Status
TASHA 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 TASHA
TASHA 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 model
CALPUFF dispersion model (pollutant concentrations by zone by time of day)
Dynamic population exposure to pollution by zone by time of day!!

35. EXAMPLE INTERVENTIONS
Transportation Policies
(Road pricing, carbon taxes, transit investment, etc.)
Land Use Policies
Vehicle Technology
Persons
& Households
Auto & Transit
Travel Times/Costs
TASHA Activity/Travel
Scheduler
Household Auto
Ownership Model
Transportation
Network Model
Activity
Patterns &
Trip Chains
Trips By Mode,
Vehicle Type &
Time of Day
VKT by Facility
Type, etc.
Vehicle Allocation
Model
Hot/Cold Soaks,
Cold Starts, etc.
Emissions Model
Locations of
People by
Time of Day
Exposure to
Pollution
Mobile Source
Emissions
Dispersion
Model

36. Auto Emissions by location and time of day
Link-based running emissions by time of day
Zone-based soak emissions by time of day

37. Dispersion of Emission Concentrations

38. Zone NO2 Exposures

39. TASHA-MATSIM
More 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.

41. Implementing TASHA as GTAModel 4.0
TASHA assumes:
Known work & school locations for all workers & students
Known number of cars per household
These 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 V4.0 Pop & Emp by Zone Synthesize persons, households & jobs
Household Car Ownership
PORPOW
PORPOS
TASHA
Activity generation
Activity scheduling
Tour-based model choice
Auto allocation
Ridesharing
Emme Road & Transit Assignments by Time Period No
Converged?
Yes
STOP

43. GTAModel V4.0 Pop & Emp by Zone Synthesize persons, households & jobs
Household Car Ownership
PORPOW
PORPOS
TASHA
Activity generation
Activity scheduling
Tour-based model choice
Auto allocation
Ridesharing
Includes shopping & other-purpose episode location choices (tour-context sensitive)
Emme Road & Transit Assignments by Time Period No
Converged?
Yes
STOP

44. GTAModel V4.0 Tasks Models to estimate: Household auto ownership level
PORPOW
PORPOS
Shopping episode location choice
Other-purpose episode location choice
Activity episode generation rates
Tour-based mode choice model (including car allocation & ridesharing models – jointly estimated)

45. Current Status
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 Computing
Earlier 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. Risks TTS 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!

50. GTAModel V4 – Data Requirements
2012 zonal parking costs
2012 station capacities and costs (already provided by Metrolinx)
2012 average adult transit fare for all agencies
407ETR 2012 tolls

51. Other Transit Lane Configurations
Seaparated ROW ramp to terminal
Surface ROW, exclusive lanes
Surface ROW, mixed lanes c cs sl
csx
Proposed Solution c cs sl
Vdf=60 or type=???
Alternative 1 c cs s u
Alternative 2