| City: |
Toronto, Ontario, Canada
|
| Organization: |
- Big Data Innovation Team, Transportation Services,
City of Toronto
- University of Toronto Transportation Research
Institute (UTTRI)
|
| Project Start Date: |
Summer 2018 (project scoping)
|
| Project End Date: |
June 2019 (report released)
|
| Reference: |
City
of Toronto. (2019, June). The Transportation Impacts
of Vehicle-for-Hire in the City of Toronto.
|
| Problem: |
Trips using Private Transportation Companies (PTCs) in
the City of Toronto have grown rapidly since they were first
licensed in 2016. As part of a review of the City's
Vehicle-for-Hire Bylaw, a study was undertaken to answer the
following questions:
- What are the trends and patterns in vehicle-for-hire
travel in the City?
- How has this travel impacted the transportation
network?
- How have travel choices evolved in Toronto?
|
| Technical Solution: |
- Trip routing: The likeliest route for each trip was
modeled using pgRouting, a PostgreSQL implementation of
Dijkstra’s Shortest Path algorithm, and traffic speed
data from HERE
- Routing deadheading: The PTC trip data provided to the
City does not contain explicit driver identifiers, so
algorithms were used to determine how trips might be
linked, in order to estimate the distance driven between
the destination of one trip to the origin of the next
- Estimating travel alternatives to PTC trips: The
duration of the fastest transit alternative to a PTC
trip was estimated using OpenTripPlanner, with GTFS and
OpenStreetMap data
|
| Datasets Used: |
- PTC Trip Records, Uber and Lyft (via Municipal
Licensing & Standards Division), September
2016-September 2018
- Pick-up/Drop-off Activity Data, Uber and Lyft (via
SharedStreets), January-September 2018
- Aggregate Wait Times, Aggregate Proportion of Distance
Travelled by Period and Hourly Number of Active
Vehicles, Uber, March 2017-September 2018
- Transportation Tomorrow Survey, University of Toronto
Data Management Group, 2016
- Resident Survey, University of Toronto Transportation
Research Institute, May 2019
- TTC Subway Delay Data, City of Toronto, n.d.
- Traffic Speed Data, HERE, n.d.
- Bluetooth Traffic Speed Data, City of Toronto, n.d.
- Transitland Feed Registry. Retrieved from https://transit.land/feed-registry/
- OSM Extracts by Interline. Retrieved from: https://www.interline.io/osm/extracts/
|
| Outcome: |
This was the first study of its kind done on PTC trips in
Toronto. The study provided a better understanding of where
and when PTC trips are concentrated, as well as their impact
on congestion and transit trips. This led to an updated
Vehicle-for-Hire Bylaw and an ongoing vehicle-for-hire
monitoring program.
|
| Issues that arose: |
- Taxi brokerages declined participation in the
study, so data on taxi and limousine trips was not
available
- Additional data, such as collision records and
more detailed data from PTCs, would have allowed
for deeper analysis of the impacts of PTC trips on
the transportation network
|
| Status: |
Operational: the study is complete, but there is now
ongoing monitoring of vehicle-for-hire services
|
| Entered by: |
28 September 2019: Jason Farra,
jason.farra@mail.utoronto.ca |