ANNUAL REPORT, 2016-17
Eric J. Miller, Ph.D.
James Vaughan, h.BSc.
Monika Nasterska, B.A.Sc., M.Eng.CEM
Brendan Reilly, h.BSc.
Bilal Yusuf, B.Eng, M.Eng.CEM
March, 2017
Annual Report 2016-17
TABLE OF CONTENTS
Page No.
1
1
Table of Contents
List of Tables
1.
INTRODUCTION
2
2.
2016-17 BUDGET & RESOURCES
2
3.
3.1
3.2
3.3
3.4
3.5
3.6
3.7
3.8
3.9
3.10
3.11
3.12
3.13
3.14
3.15
3.16
3.17
3.18
3.19
3.20
2016-17 PROJECTS & ACTIVITIES
Support for Agency Usage of TMG Model Systems & Components
Transit Fare Class Model
HOV Demand Modelling
Commercial Vehicle Generation (Including Special Generators)
Active Transportation
PORPOS Modelling
Updating NCS2011 to NCS2016
Commercial Vehicle Network Upgrades
Future Year Base Network(s)
Multi-Class, Congested Transit Assignment
2016 Base Network
Surface Transit Speed Updating
Volume-Delay Function Calibration; Intersection Delay
Disaggregate Transit Assignment
TMG Toolbox Improvements
XTMF Maintenance
Documentation of TMG Products
Outreach & Training
Committee Meetings
Other Activities: PopSyn3
4
4
5
6
6
7
8
8
8
8
8
10
11
11
11
11
12
12
12
12
13
4.
SUMMARY OF 2016-17 ACCOMPLISHMENTS
13
Appendix I: EMME TOOLBOX CONTENTS
14
LIST OF TABLES
2.1: 2016-17 Expenditures
2.2: 2016-17 Revenues
3.1: 2016-17 Work Plan
4.1: TMG Accomplishments 2016-17
Page No.
2
3
4
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Annual Report 2016-17
1.
INTRODUCTION
This document describes the activities of the Travel Modelling Group (TMG) during its sixth
year of operation, 2016-17 (April 1, 2016 through March 31, 2017).
This past year has been another challenging one for TMG given continuing efforts to assist the
City of Toronto’s operational implementation of GTAModel V4.0 during the first half of the
year,1 and, then having to cope with a complete turn-over in TMG staff change during the second
half of the year. Despite these challenges, however, we managed to achieve many of our
planned deliverables.
Section 2 describes the budget and resources of the TMG during the reporting period. Section 3
then provides an overview of TMG activities with a comparison to the proposed work plan for
the year. Finally, Section 4 summarizes TMG accomplishments in 2016-17.
2.
2016-17 BUDGET & REVENUES
Tables 2 1 and 2 2 provide the 2016-17 TMG expenditures and revenues, respectively. This
budget supported two full-time technical staff persons. The TMG staff for 2016-17 consisted of:
 One full-time network analyst/modeller. Monika Nasterska took over the position on
February 1, 2016 and then resigned on October 28, 2016 to take a position in consulting.
The position was filled again by Bilal Yusuf as of January 2, 2017.
 One full-time software programmer/designer. The long-time incumbent in this position
(James Vaughan) resigned on August 31, 2016 to accept a promotion to Senior Software
Architect within UTTRI. He was replaced by Brendan Reilly effective November 1,
2016.

Table 2.1: 2016-17 Expenditures
TMG Budget
Expenses
Salaries1
Supplies, Misc. Expenses
Emme Licence Maintenance
Contingency
Overhead (@40%)
Total Expenses
2016-17
Amount
2017-18
Amount
2018-19
Amount
$169,446.78
$250.00
$3,000.00
$0.00
$61,714.29
$234,411.06
$169,744.65
$250.00
$3,000.00
$0.00
$65,571.43
$238,566.07
$176,294.43
$250.00
$3,000.00
$0.00
$67,142.86
$246,687.29
1
In addition, we also provided significant assistance to the City of Mississauga in its implementation of GTAModel
V4.0.
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Annual Report 2016-17
Table 2.2: 2016-17 Revenues
Revenues
2016-17
Member Contributions
Metrolinx
MTO
City of Toronto
City of Hamilton
Region of Durham
Region of Halton
Region of Peel
Region of York
City of Mississauga
Amount
$60,000.00
$30,000.00
$30,000.00
$18,000.00
$18,000.00
$18,000.00
$18,000.00
$18,000.00
$6,000.00
City of Brampton2
Total Member Contributions
Carry-Forward from Previous Year
Additional Revenue (UofT Subsidy)
$0.00
$216,000.00
$40,000.00
$0.00
Total Revenues4
$256,000.00
Avg. Increment relative to 2014-15 base
Avg. Increment relative to previous year
Total Revenues-Total Expenses
Contributions-Actual Expenses
-5.0%
9.9%
$21,588.94
-$18,411.06
Notes:
1. Salaries and benfits for TMG + summer research students. 2 students in 2016-17; 1 student in 2017-18 & 2018-19.
TMG staff salary increases based on an assumed increase of 4% per annum.
2. The City of Brampton seems to have dropped out of TMG. I have been unable to get them to respond
to any correspondance for about 2 years now.
3. 2015-16 contributions were reduced relative to 2014-15 due to "buy-out" of staff time for the
SmartTrack Ridership Study.
4. "Total Revenues" include carry-forward from the previous year.
University of Toronto In-Kind Contributions
Principal Investigator Time
$45,000.00
Co-Investigator Time
$29,000.00
Office Space & telephones
$6,194.26
Total
$80,194.26
This excludes many other in-kind contributions by UofT to TMG that are very difficult to quantify. These include:
Data Management Group support of TMG
Internet access
University of Toronto library access
Administrative support
TMG computers & software
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Annual Report 2016-17
3.
2016-17 PROJECTS & ACTIVITIES
Table 3 1 presents that 2016-17 work plan as approved by the TMG Steering Committee. As
indicated in this figure, the work plan tasks divided into 19 primary tasks. TMG activities in
each of these areas are discussed in the following sub-sections.
Table 3.1: 2016-17 Work Plan
TMG 2016-17 Work Plan
No. TASK
1 Support for agency usage of TMG model systems & components
2 Transit fare class model
3 HOV demand modelling
4 Commercial vehicle generation (including special generators)
5 Active transportation mode choice
6 PORPOS modelling
7 Updating NCS2011 to NCS2016 (includes traffic zone guidance)
8 Commercial vehicle network upgrades
9 Future Year Base Network(s)
10 Multi-class, congested transit assignment
11 2016 base network
12 Surface transit speed updating
13 Volume-delay function calibration; intersection delay
14 Disaggregate transit assignment
15 TMG Toolbox Improvements
16 XTMF Maintenance
17 Documentation of TMG products
18 Outreach & Training (3 workshops)
19 Meetings: TMGSC (2) & TMGTAC (6)
MONTH
Apr
May
1
1
3
3
1
1
June
1
3
July
1
3
1
1
Aug
1
3
1
2
2
3
3
SC
1
Oct
1
Nov
1
Dec
1
Jan
1
Feb
1
Mar
1
3
3
3
3
3
3
1
1
1
1
1
1
2
3
2
3
2
3
TAC
TAC
W3
SC
1
3
1
TAC
Sep
1
3
W1
TAC
1
1
1
3
3
2
2
1
1
1
1
2
2
2
2
2
2
SC
W3
TAC
1
W2
TAC
Staff Average Weekly Time Allocation (Days)
1. Numbes in cells indicate estimates of the approximate average number of days per week spent on the task in the given month.
2. TMG Toolbox improvements, XTMF maintenance and documentation are all on-going activities.
3. One-half to one day per week per staff person is expected to be allocated to documentation of the work on an on-going basis.
Primarily Software Developer task
Primarily Network Modeller task
n Light, on-going effort
n = approximate, average number of days per week for this task
n Heavy, focussed effort
Includes allocation of time for documentation, meetings, etc.
Suggested Workshops (includes consultants as well as TMG members)
W1 June: NCS2016
W2 September: V4.0 modelling
W3 November: Multi-class, congested transit assignment
W4 March: Surface transit speed updating
3.1
Support for Agency Usage of TMG Model Systems & Components
TMG staff provided on-going support to both the City of Toronto and the City of Mississauga in
their usage of GTAModel V4.0. The City of Toronto support took a considerable amount of
staff time through June 2016 as UTTRI’s SmartTrack Ridership project with the City was
wrapping up.
The City of Mississauga work largely consisted of supporting their consultants in learning
XTMF and in developing Mississauga’s networks (using their custom zone system) within
NCS11 for use within GTAModel V4.0. This resulted in TMG staff revisiting the TMG
automated centroid connector procedures in detail, leading to a number of improvements in these
procedures.
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Annual Report 2016-17
3.2
Transit Fare Class Model
We believe that TMG has made significant progress over the past several years in terms of
developing robust fare-based transit assignment methods. These methods, however, are still
based on the assumption that all transit users pay an “average adult fare” for their trip. This
clearly is not the case and could represent a bias in our current models that is not completely
compensated for by our calibration efforts. Rectifying this problem requires a transit fare class
model that determines the fare that is “actually” paid by each trip-maker, depending on the tripmaker’s age (school-age, senior, etc.) and fare media (transit pass, cash, etc.) choice.
Dealing with age within a mode choice model is, in principle, straightforward in model systems
such as GTAModel V4.0 since each trip-maker’s age is known. Modelling transit pass
ownership2 is, however, a non-trivial task, especially since TTS only provides us with a one-day
snapshot of travel behaviour, whereas the decision to purchase a transit pass is a somewhat
longer-term (e.g., monthly) decision.
Given the use of a fare-based transit assignment model, however, implementation of a transit fare
class choice model is not practical unless a multi-class assignment is implemented, since
different fare class users will face different generalized time-plus-fare “impedances”. Multiclass transit assignment is discussed in Section 3.10, below.
It was not possible to take on this full set of complex modelling issues within the current year.
To begin investigation of these issues, however, Prof. Habib undertook two exploratory
analyses:3,4
1. Statistical analysis of transit usage with and without a transit pass.
2. Discrete choice model of transit pass choice and daily transit trip frequency.
Transit pass ownership would be best modelled as part of the choice of a person’s (household’s)
mobility bundle, where this consists of choice of the number of household vehicles along with
each person’s choice of driver’s licence status and transit pass ownership.5 This mobility bundle
decision would “sit above” the activity/travel scheduling model in the model system hierarchy.
The relationship between mobility bundle choice and work/school location choice is also an
issue that needs further investigation.
Going forward it is recommended that:
1. Once an operational multi-class transit fare assignment procedure is available, all new
mode choice models should, at a minimum, use age-appropriate (student,6 adult, senior)
2
Or, more generally, choice of fare media. In the case of the TTC, for example, in 2011 an adult rider could choose
from among, cash, tokens and Metropass.
3
Nurul Habib, K.M. & S, Hasnine, “An Econometric Investigation of the Influence of Transit Passes on Transit
Users’ Behaviour in Toronto”, presented at the 97th Annual Meeting of the Transportation Research Board,
Washington, D.C, January, 2017.
4
Nurul Habib, K.M., “Role of Transit Pass Ownership in Daily Transit Usage”, presentation to the TMG Technical
Advisory Committee, June 1, 2016.
5
Note that the driver’s licence decision is a longer-term, one-time decision, whereas the transit pass decision can be
made typically on a monthly basis. In a “static, cross-sectional” model system such the GTHA model systems, these
two time frames cannot really be differentiated; hence treating these a combined decision is a practical solution.
6
Post-secondary “U-Pass” fares, where available, need also be included.
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Annual Report 2016-17
fares. These fares should be consistently used in the multi-class transit assignment model
as well.
2. A joint driver’s licence and mobility pass choice model should be investigated that
integrates appropriately with the rest of the model system, notably household car
ownership, and the PORPOW/PORPOS models.
3.3
HOV Demand Modelling
GTAModel V4.0 endogenously models within-household car allocations, ride sharing and “serve
passenger” trip-making. Inter-household carpooling and other non-household-based “auto
passenger” trips (taxis, Uber, etc.) are very simplistically modelled. In particular, the linkage
between these “passenger” trips and the vehicular trips that convey these passengers is not
explicit. This means that a full representation of HOV travel is not possible within the current
model system. While details vary from one model system to another within the region, it is fair
to say that HOV travel demand modelling is still not well developed, especially relative to the
policy importance of the issue.
The main obstacles to developing improved extra-household passenger travel models include: (1)
the large combinatorial problem usually associated with characterizing the “choice sets”
involved (i.e., who might share rides with whom; who has what services available; etc.); and (2)
limited data for model building and testing (although available data are increasingly available).
As a first step towards building a longer-term project dealing with these issues, a literature
review of the current state of the art/practice of HOV modelling and evaluation was undertaken
by Prof. Nurul Habib and one of his students (Albert Lo). This literature review will form the
basis for next steps in TMG/UTTRI data collection, analysis and modelling in this area. 7
3.4
Commercial Vehicle Generation (Including Special Generators)
Due to a combination of factors no significant direct progress was made on this task during the
2016-17 work period. These factors include:
 Prof. Roorda (the academic lead on this task) was on sabbatical July 1 – December 31,
2016.
 TMG staff turn-over limited their ability to work on this task.
 This task needed a student as a primary contributor to this work. As things actually
transpired, a suitable student for this task, unfortunately, was never identified.
Prof. Roorda, however, continued to develop his freight / urban goods movement research
program along a number of dimensions outside of the TMG work plan per se. Perhaps most
notably is the recent graduation of Dr. Toka Mostafa, whose Ph.D. dissertation deals with several
elements of a microsimulation model system of “firmographics” – the generation, growth and
decline of firms which underlies both employment projections and urban goods movement
modelling.8
Lo, A. and K.M. Nurul Habib, “HOV Evaluation: A Literature Review”, Toronto: University of Toronto
Transportation Research Institute”, March, 2017.
8
Mostafa, T. A Microsimulation Platform of Firm Evolution Processes, Ph.D. thesis, Toronto: Department of Civil
Engineering, University of Toronto, March, 2017.
7
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Annual Report 2016-17
3.5
Active Transportation
Active transportation demand modelling is an area of considerable graduate-student-based work
within UTTRI. In 2015, the MASc thesis by Yunfei Zhang developed a set of GIS-based land
use measures (e.g., land use mix) and active transportation network measures (sidewalks, bicycle
lanes, etc.) and re-estimated the GTAModel V4.0 mode choice model with these new variables
included in walk and bicycle utility functions. The results obtained were encouraging, although
they did not result in dramatic increases in overall model fit (Zhang, 2015). Further research is
required, building on Zhang’s work before significantly improved models of walk and bicycle
mode choice are likely to able to be included in large regional travel demand models such as
GTAModel. In particular, operational models of bicycle and pedestrian route choice appear to
be required in order to generate improved modal utility function variables.
Given these observations, during the 2016-17 time-period two MASc theses were completed
investigating both bicycle route choice (Kathryn Grond)9 and pedestrian route choice (Greg
Lue).10 Two very important points to note with respect to both of these modelling efforts is that
they both are:
 Based on travel data collected using smartphone apps. Grond used the City of Toronto’s
bicycle app data, while Lue used data collected by UTTRI in a smartphone pilot project
undertaken in November, 2015 that was sponsored by Waterfront Toronto.
 Heavily dependent on high-quality, detailed GIS data concerning roadway network and
neighbourhood urban form / land use data. This point was emphasized in Zhang’s earlier
work. Both of these studies reinforced the importance of such data. While we continue
to improve the quality and depth of our GIS datasets, especially as increasing amounts of
municipal data become generally available though Open Data initiatives, further
improvements are still needed. Also the implications of the need for spatially detailed
data for active transportation modelling for regional travel demand model systems (which
still operationally work at the traffic zone level) are not yet clear, but are expected to be
challenging for incorporating research results into operational practice.
Possible next steps for TMG activities in this area include:
 Investigation of bicycle and pedestrian network modelling options. I.e., modelling active
transportation networks within Emme, or possibly “in parallel” in other (more detailed)
GIS-based network representations.
 Investigation of issues and options for “scaling up” the prototype models developed by
Grond and Lue for regional-scale operational implementation.
 Building on Zhang’s GIS work, update our GIS database of active transportation related
neighbourhood and street attributes to support “skimming” of these attributes along
chosen paths for input into enhanced mode choice models.
 Revisiting Zhang’s mode choice modelling with path-based bicycle and walk mode
attributes.
9
Grong, K. Route Choice Modeling of Cyclists in Toronto, MASc thesis, Toronto: Department of Civil Engineering,
University of Toronto, August, 2016.
10
Lue, G., Estimating a Toronto Pedestrian Route Choice Model Using Smartphone GPS Data: It’s Not the
Destination, but the Journey, that Matters, MASc thesis, Toronto: Department of Civil Engineering, University of
Toronto, March, 2017.
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Annual Report 2016-17
3.6
PORPOS Modelling
Place-of-Residence-Place-of-School (PoRPoS) are used in both GTAModel and GGHM to link
the residential locations of students to the students’ school locations. These models are quite
simple in formulation and could certainly be improved. The availability of the recently
available, large-sample (>15K) StudentMoveTO survey of post-secondary student travel within
the City of Toronto provides an exciting new opportunity to explore post-secondary PoRPoS
distributions in a manner never before available. It is also possible to link TTS data with
elementary and secondary school board enrollment data to perhaps improve our models for these
classes of students as well.
3.7
Updating NCS2011 to NCS2016
In consultation with member agencies, a draft EMME Network Coding Standard (NCS16) has
been developed that will shortly be approved by TMGTAC.
3.8
Commercial Vehicle Network Upgrades
Truck route restrictions were researched for the Regional Municipalities of the GTA. Data on
these restrictions was gathered from the City of Toronto, Durham Region, Peel Region, Halton
Region, Burlington, Milton, and Hamilton. This data showed that route restrictions not only vary
by time of day but by season as well. Some of these restrictions have been coded into the
network already by utilizing different modes for different truck vehicle types. Further work,
however, was put on hold due to staff changes and Prof. Roorda’s sabbatical.
Next steps include the treatment of restrictions that do not correspond neatly into a network time
period as specified in the model. There also needs to be adjustments made to the Full Network
Set Generator Tool that allows these changes to be incorporated automatically for use in the
GTA Model. Finally, with the restrictions in place, some zones are completely cut off, and there
needs to be a way to ensure that all zones can have access to each other in order to ensure a
viable model.
3.9
Future Year Base Network(s)
The 2016-17 work plan included the assembly of a 2031 “base” Emme road and transit network
for the GTHA which would include “committed” road and transit improvements relative to the
2016 base case. This task was not completed due to several factors:
 The 2016 base network has not yet been assembled.
 TGMG staff turnovers restricted our ability to address this task.
 Obtaining consensus agreement among the TMG partner agencies concerning what
projects should be included in this future base network (and what their attributes should
be) is a non-trivial task, which we simply lacked resources to undertake over the past
year.
3.10 Multi-Class, Congested Transit Assignment
Considerable experience was gained over the past two years during the GTAModel V4.0
calibration and validation process with respect to congested transit assignment modelling. It is
very clear that transit route choice is sensitive to onboard congestion effects, and careful
calibration of the congested transit assignment model was required to get optimal model results.
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Annual Report 2016-17
Implementation of a multi-class assignment procedure is also clearly important, particularly in a
fare-based transit assignment procedure such as has been implemented in GTAModel V4.0.
That is, different classes of transit users (worker by occupation type, students, etc.) can be
expected to have different values of time and, hence, evaluate the fares paid on different transit
routes/services differently. Emme now supports multi-class congested transit assignment
(MCCTA). In this year’s work we have begun the process of testing this procedure for possible
use within the GTHA. The work undertaken to date has involved:
 Accumulating the data required to test multi-class transit assignment from the 2011 TTS
database.
 Construction of a MCCTA module within the TMG Emme Toolbox and XTMF.
 Preliminary multi-class assignments using current GTAModel V4.0 mode choice model
values of time to both test the assignment module and to get a preliminary sense of the
performance of the multi-class assignment procedure.
 Full-scale parameter estimation runs of the MCCTA model.
Various runs were done trying to estimate the class perceptions and parameters for use in a multi
class transit assignment. The results are given below
Fare Perception
35
30
25
20
15
10
5
0
Estimated against total boardings
Different walk perceptions
connector vs road perception
one walk perception
fare only
Current
Wait Perception
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
Estimated against total boardings
Different walk perceptions
connector vs road perception
one walk perception
Current
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Annual Report 2016-17
Boarding Penalty Perception
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
Estimated against total boardings
Different walk perceptions
connector vs road perception
one walk perception
Current
General
Manufacturing Non-Worker
Non-Student
Sales
Student
The blue line in the graphs above represents the value of the parameter in the current
GTAModel. The following is a description of the various runs:
 In the first run, the parameters were estimated against total boardings per line, which led
to results that did not correspond to reality. Further runs were then estimated against
boardings per line per class in order to keep class distinctions intact.
 Different Walk Perceptions: Estimating using all the various walk perceptions as defined
in the current GTAModel, but this was cut down due to fears about over estimation
 Connector vs. Road Perception: all connectors and all road links have the same walk
perceptions for each class
 One Walk Perception: All classes would have just walk perception parameter. This was
done to simplify the model
 Fare Perception Only: This run only estimated fare perception. This was another attempt
at simplifying the model and only using as many parameters as would be necessary.
However, the runs did not produce the intended results. Therefore, the model system is currently
undergoing further work and revision. The current run time for a single run when running on
two servers is about six days and thus requires significant time resources. Upon completion of
the revised model system, multiclass transit runs will begin again. This task, upon approval by
the TMG TAC, will likely be continued in the operating year 2017-2018.
3.11 2016 Base Network
The 2016 base network has not been completed. Due to TMG staff turn-over, completion of the
new NCS16 network coding standard (which is to be used in constructing the 2016 base
network) was delayed in starting, making it impossible to complete the 2016 base network in the
2016-17 work period.
A major component of developing a base network is assembling all the changes in the road and
transit networks that have occurred since construction of the previous base network (in this case
the 2011 network). Work on this data assembly task has been proceeding apace and TMG is in
good shape to complete the 2016 base network early in the 2017-18 work plan. The objective
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Annual Report 2016-17
has always been to have the 2016 base network operational at the time of the release of the 2016
TTS dataset. This is scheduled to occur mid-2017. TMG is well on-target to meet this deadline.
3.12 Surface Transit Speed Updating
Due to staff turn-over, along with other factors, this task was not started in 2016-17. It will
require a significant commitment to develop a well-tested, robust procedure. It is strongly
recommended that this become a major TMG task in 2017-18, possibly with student assistance to
augment TMG staff resources.
3.13 Volume-Delay Function Calibration; Intersection Delay
Due to staff turn-over, along with other factors, this task was not started in 2016-17.
3.14 Disaggregate Transit Assignment
Metrolinx had requested that an investigation of disaggregate transit assignment within Emme be
included in the work plan. TMGTAC discussed its experience with the Emme procedure and it
was agreed that it is computationally very slow and so not very practical for large-scale
applications. Given this, this issue was not explored further.
There are good arguments while a more disaggregate, less static transit assignment would be
useful to use. In particular, “keeping track of” individual trip-makers as they travel through the
transit network would be very helpful for a variety of reasons. The major challenges in adopting
such an approach include:
 The need to use a software package other than Emne, such as, perhaps, MATSim.
 The predictive accuracy of such packages is not well established.
 Such procedures tend to be computationally expensive.
Nevertheless, it would be useful for TMG in the future to investigate such options (particularly
MATSim, which is increasingly being used worldwide) so as to be able to better assess their
strengths, weaknesses and practicality.
3.15 TMG Toolbox Improvements
A primary rationale for the TMG is to develop standard tools, procedures and templates for
general use by member agencies. These tools are primarily of two types: XTMF-based modules
and Emme/4 Modeller procedures. Tool development occurs in two primary ways. First, TMG
staff constantly refine/extend existing tools and develop new tools through the course of their ongoing model system development, network coding and testing and other work tasks. Second,
recommendations for tool development are regularly generated by the TMGTAC on an on-going
basis.
The toolbox is open source software and is available to anyone through github. Some
documentation for the tools is available on the TMG website. Further documentation of the
various tools should be a task for operating year 2017-2018.
The total list of tools along with their status is documented in Appendix I.
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Annual Report 2016-17
3.16 XTMF Maintenance
A push was made to prepare XTMF for version 1.3. A full analysis of the code base was made
and updated to conform to the new coding standards. New features in version 1.3 are:
 Copy model systems between projects.
 Disable modules for run.
 User experience overhaul.
 Theming support.
 Support for instance-specific configurations of XTMF that allows for multiple (local)
versions to be used without conflict.
 Importing / Exporting Model systems from project from/to file.
In addition to updates to XTMF, there have been improvements to the TMG modules for XTMF.
In particular the data processing framework now allows for arbitrary expression execution for
Matrices, Vectors, or Scalar values. An additional module has been added to support when in
conjunction to the above the running of 2D gravity models. These tools will allow for the rapid
development of many modelling scenarios without the need for explicit programming.
3.17 Documentation of TMG Products
Up-to-date documentation of GTAModel V4.0, XTMF and EMME Toolbox modules is
available on the TMG web site. The web site has been completely redesigned and updated.
3.18 Outreach & Training
A critical component of TMG activities in all phases of its work must be training, technology
transfer and outreach. In order to succeed, TMG must be responsive to its collaborating
partners’ needs. It must also get the tools that it is developing into the hands of its partners for
their use. The TMG’s role is intended to be one of tool developer, not to be the user of these
tools on behalf of its partners in operational applications (except perhaps in special cases). 201617 activities in this area included:
 On-going updating and elaboration of the TMG web site.
 Documentation of all procedures, etc. developed by the TMG.
 Six meetings were held with TMGTAC to discuss work in progress, next steps in the
work plan and to disseminate work plan results. In addition to presentations at these
meetings by TMG staff and faculty associates, the September 7, 2016 meeting included
presentations by Peel and York staff on recent model development activities in their
regions.
 One training session/workshop was held for TMG partners on October 26, 2016 dealing
with an introduction to MTO’s recently developed Greater Golden Horseshoe Model
(GGHM) V4.
3.19 Committee Meetings
In addition to the TMGTAC meetings discussed in Section 3.18, two meetings with the TMG
Steering Committee (TMGSC) were held (on May 17/16 and March 22/17) to discuss work plan
progress, budget, overall TMG directions for work and other administrative and supervisory
matters.
12
Annual Report 2016-17
3.20 Other Activities: PopSyn3
An activity undertaken during the past year that was not in the original work plan was the testing
of the PopSyn3 population synthesizer used by MTO in their new GGHM V4 model system.
MTO and WSP (the procedure developers) provided the PopSyn3 software to TMG for testing.
The outputs from PopSyn3 were compared with comparable outputs from the GTAModel V4.0
population synthesizer. It was found that the two procedures generated reasonably similar
results, although some differences exist. “Truth” is difficult to ascertain in this exercise, and so
the main conclusion is that PopSyn3 appears to be doing a “good” job in synthesizing GTHA
disaggregate populations.
This sharing of a GGHM V4 component is very encouraging in terms of promoting common
modelling tools within the region (a primary rationale for TMG’s existence) in general and in
promoting an eventual convergence between GGHM and GTAModel – currently the two
primary, general purpose travel demand model systems for the GTHA. It is TMG’s intention to
implement PopSyn3 as the GTAModel population synthesizer in the next release of the model
system software. It is recommended that other agencies within the region also seriously consider
adopting PopSyn3 as their population synthesis procedure as they move into microsimulationbased modelling.
4.
SUMMARY OF 2016-17 ACCOMPLISHMENTS
Table 4 1 summarizes the key accomplishments by the TMG during 2016-17.
Table 4.1: TMG Accomplishments 2016-17
Task Deliverable
1 Support for agency usage of TMG model systems & components
2 Transit fare card impacts on transit usage & modelling implications studied
3 Literature review of HOV evaluation & modelling state of art/practice
4 Report documenting commercial vehicle generation modelling (including special generators)
5 Prototype bicycle and pedestrian route choice models developed using smartphone app data
6 Report documentation PORPOS modelling R&D work
7 NCS2016 draft final report
8 Draft commercial vehicle network upgrades completed and documented
9 Draft 2031 future year base network completed and documented
10 Multi-class, congested transit assignment developed, tested and documented
11 Draft 2016 base network completed and documented
12 Surface transit speed updating procedure developed, tested and documented
13 Report documenting volume-delay function calibration work
14 Report documenting disaggregate transit assignment work
15 TMG Toolbox Improvements, various products
16 XTMF Maintenance, various products
17 Documentation of TMG products, various products
18 Outreach & Training (1 workshop)
19 Meetings: TMGSC (2) & TMGTAC (6)
13
Date
On-going
Jan. 31, 2016
March 31, 2017
Not completed
August 31, 2016;
March 31, 2107
Not completed
March 31, 2017
Not completed
Task removed
from work plan
On-going
Data assembly
on-going
Not completed
Not completed
Task removed
from work plan
On-going
On-going
On-going
Various dates
Various dates
Annual Report 2016-17
APPENDIX I
EMME TOOLBOX CONTENTS
Traffic Analysis Tools
1. Export Count Station location
2. Export countpost results (updated in 2016-2017)
3. Export screenline results
4. Import cordon counts
Transit Analysis Tools
5. Extract constrained LOS matrices
6. Extract cost matrices
7. Extract feasibility matrix
8. Extract flagged line demand matrix
9. Extract link transfers (updated in 2016-2017)
10. Extract LOS Matrices
11. Extract operator transfer matrix (updated in 2016-2017)
12. Extract rail IVTT matric
13. Extract transit OD vectors (updated in 2016-2017)
14. Revenue calculation
15. Select line analysis
16. Volume per operator (updated in 2016-2017)
17. Create station Access files
18. Export boardings (updated in 2016-2017)
19. Export station boarding alighting
20. Export transit screenline results
General Analysis Tools
21. Create zone adjacency matrix
22. Export partition average matrix (updated in 2016-2017)
23. Link specific volumes
24. Matrix statistics
25. XTMF network calculator
Assignment Tools
26. Assign V4 boarding penalty
27. Calculate 407ETR tolls
28. Check network connectivity
29. Check network integrity
30. Check scenario functions
31. Flag premium buses
32. Import V3 boarding penalty
33. Set walk speed
34. Toll attribute
35. Toll attribute transit background (updated in 2016-2017)
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Annual Report 2016-17
36. Toll based road assignment (updated in 2016-2017)
37. Multiclass congested fare based transit assignment (new in 2016-2017)
38. V2 Line haul
39. V2 transit assignment
40. V3 Fare based transit assignment
41. V3 Line haul
42. V4 Fare based transit assignment (updated in 2016-2017)
Common Tools/Utilities
43. Geometry
44. Network editing
45. Pandas utilities (updated in 2016-2017)
46. Spatial index (updated in 2016-2017)
47. TMG Tool page builder
48. Utilities (updated in 2016-2017)
Input/Output
49. Export binary matrix
50. Export distance matrix
51. Export network package (updated in 2016-2017)
52. Import binary matrix (updated in 2016-2017)
53. Import network package (updated in 2016-2017)
54. Import network update
55. Merge functions
Network Editing Tools
56. Add node weights (new in 2016-2017)
57. CCGEN (updated in 2016-2017)
58. Copy zone system
59. Validate connectors (new in 2016-2017)
60. Clean GTFS
61. Export GTFS stops as shapefiles
62. Generate transit lines from GTFS
63. GTFS to EMME node map (new in 2016-2017)
64. Node Mapping (new in 2016-2017)
65. Shp EMME map (new in 2016-2017)
66. Apply operator Codes
67. Convert VDFs
68. Convert vehicles
69. Geo renumber nodes
70. Modify walk modes
71. Move network
72. Renumber nodes
73. Check connector speeds
74. Check link lanes
75. Check link lengths
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Annual Report 2016-17
76. Check link types
77. Check link VDFs
78. Copy transit lines
79. Create network correspondence file
80. Compute combined headways
81. Create aggregation selection file
82. Create transit time period (updated in 2016-2017)
83. Flag network changes
84. Calculate hypernetwork size
85. Generate hypernetwork from schema (updated in 2016-2017)
86. Hypernetwork volume importer
87. Calculation station frequencies
88. Full network set generator (updated in 2016-2017)
89. Load attribute from polygon
90. Prorate transit speed
91. Remove extra links (updated in 2016-2017)
92. Remove extra nodes (updated in 2016-2017)
93. Reverse transit lines
94. Rotate network
XTMF Internal Tools
95. Apply batch line edits
96. Attach centroids to nodes (new in 2016-2017)
97. Copy scenario (new in 2016-2017)
98. Delete matrix (new in 2016-2017)
99. Delete scenario (new in 2016-2017)
100.
Export matrix batch file
101.
Export network batch file
102.
Export worksheet
103.
Export worksheet table
104.
Import from database
105.
Import matrix batch
106.
Multi class road assignment (updated in 2016-2017)
107.
Return boarding types
108.
Return boardings
109.
Return boardings and WAW
110.
Return boardings multiclass (new in 2016-2017)
111.
Return grouped boardings
112.
Return matrix results
113.
Run macro
114.
Temp attribute manager
115.
XTMF network calculator (updated in 2016-2017)
16