How the City of Toronto Used Shared Streets’ PUDO Data to Examine Curbside Impacts
This is a guest post written by Natalie Chan and Raphael Dumas of the City of Toronto.
The City of Toronto Transportation Services Division’s Big Data Innovation Team worked with the Municipal Licensing & Standards Division (MLS) and the University of Toronto Transportation Research Institute (UTTRI) on a review of the Vehicle-for-Hire by-law, which regulates taxicabs, limousines, and private transportation companies such as Uber and Lyft. The report studied the transportation impacts of Private Transportation Companies (PTC) in the City of Toronto to build a deeper understanding of these new services and to pave the way for future work to keep in front of these rapidly changing trends.
As part of the VFH by-law review, we assessed the curbside impact of PTC activities to answer questions such as:
- Where are the hotspots of activities around curbside regulations?
- What are the policy implications on curbside management?
- What are the localized impacts of pick-up and drop-off activities?
The Data
To facilitate this study, we partnered with SharedStreets and acquired detailed pick-up and drop-off data from Uber and Lyft for a total of nine weeks in 2018. The data was aggregated by hour of day and to a 10m spatial resolution. The SharedStreets platform decoupled trip origins and destinations, and filtered out any areas where only a small number of pick-up or drop-off were made in the requested time-period for any 10m segment of curb to avoid this data being personally identifiable. With this high resolution of PTC activity data, we were able to start to understand how PTCs use the curb and to flag hot spots of potential conflicts with curbside bylaws and regulations.
Curbside regulation in the City of Toronto is passed by City Council and encoded as a text description of the affected location. This data is publicly available as XML on the City’s OpenData Portal and Transportation Services’ staff have been geo-coding these bylaws to the curb space they pertain to.
We used SharedStreets’ Street Referencing System tool to create a shared reference between our bylaw network, bike lane network and the pick-up/drop-off data. The reference tool allowed us to create a link between different GIS datasets and aided us in data aggregation, analysis, and visualization.
What we found
No-Stopping Zones
The introduction of PTCs, a mode of transportation heavily dependent on access to the curbside, raises important questions on the continued effectiveness of the City’s curbside traffic and parking regulations. A detailed look at the pick-up/drop-off data during the morning commute period showed hotspots of activities in no-stopping zones. The largest hotspots are found on Bay St and Adelaide St in the Financial District. Bay Street has a designated “Urban Clearway” with the curb lane dedicated for taxi, transit, and cycling from 7 A.M. to 7 P.M. weekdays and a No Stopping restriction (licensed taxicabs in the City of Toronto are permitted to stop in No Stopping zones).
Many of the streets with the highest stopping activity are on arterials carrying large volumes of vehicular and transit traffic, a large part of the reason why stopping restrictions exist. Bringing these two datasets together can assist us in identifying where these illegal pick-up/drop-off activities occur, thereby informing ongoing work in curbside planning as well as parking enforcement.
Bike Lanes
A safety concern with PTC pick-up and drop-off activity is potential conflicts with cyclists, especially when it occurs near cycling infrastructure. Integrating pick-up and drop-off data with the city’s existing bike lanes shows where these potential conflicts might occur. The largest hotspots are located on Adelaide St in the Financial District as well as busy establishments such as the Chelsea Hotel and the University of Toronto downtown campus. While it is not possible to conclude from the available data whether the pick-up/drop-off occurred within or next to a bike lane, hotspots can highlight areas that poses a high risk of conflict. Continued investigation is needed to inform future design changes of bike lanes as well as upgrades to cycling facilities.
PTC services have been immensely popular with Toronto residents as evidenced by the rapid growth in trips. Pick-up/drop-off data have a huge value and can aid us in uncovering new insights about how these services have an impact on curbside operations in the City of Toronto. This enables future work to allow the City to keep in front of these changing trends and to be able to define policies to support the benefits of PTC services while minimizing adverse impacts to traffic, to the environment and the equity of mobility services.
