Toronto rolls out congestion 'action plan' with traffic levels now at 75 per cent of pre-pandemic norm
Traffic levels across Toronto are back to 75 per cent of the pre-pandemic normal and Mayor John Tory says that city officials “fully expect” a further increase in gridlock as schools reopen and some workers return to their downtown offices over the coming weeks.
Tory made the comment during a press conference on Tuesday as he discussed a new “action plan” to tackle congestion this fall.
The plan includes nearly a dozen initiatives, including a pause on non-essential utility work during the first two weeks of September and a return to pre-pandemic policies for construction near school zones.
As part of the plan, the city will also reduce the number of rush hour construction exemptions that are issued after previously increasing them in order to take advantage of lower traffic volumes earlier in the pandemic.
“Every very year we do see an increase in traffic in September as people return to school and as people are back from summer vacations and back to work but we know that in the midst of the pandemic this September could bring even more change,” Tory said. “Ahead of the fall, I asked city staff to anticipate this eventual return to work and to school and to traffic of one kind or another, whether on transit or on the streets, and they have put a plan in place to keep people moving as best we can, as traffic volumes continue to rise and people get back to typical life activities.”
Data released by the city on Tuesday showed that traffic volumes plunged by 55 per cent earlier in the pandemic but have risen steadily and are now at about 75 per cent of the pre-pandemic normal.
Pedestrian traffic downtown is also on the rise. At one point, it was at 15 per cent of the pre-pandemic normal but is now at approximately 35 per cent with a further increase expected as more workers head back to the office.
In school zones specifically, traffic volumes are at about 80 per cent of the pre-pandemic level compared to a low of 66 per cent earlier in the pandemic.
The plan released by the city on Tuesday will see the city’s traffic agents returned to downtown congestion hot spots like University Avenue, Bay Street and Front Street after many of them were previously redeployed to areas near construction zones and other pinch points to reflect the changing traffic patterns in the early days of the COVID-19 pandemic.
The city will also be accelerating the installation of more than 900 pieces of technology that will provide its staff with valuable real-time traffic data.
“We hope that more people are going to come back to work downtown, we hope that we are going to be able to have our students stay in school without interruption but as that all happens and we return to something approaching normal we will be able to make the adjustments as needed. Conversely if anything happens that isn’t normal we can make adjustments in that regard as well,” Tory promised on Tuesday. “This is meant to be a very flexible and adaptable plan to take account of the real circumstances that arise, pandemic or otherwise.”
The following are the key components of Toronto’s fall congestion management plan:
- Active monitoring of traffic cameras around the city, especially at congestion hot spots
- Increasing the number of RESCU (Road Emergency Services Communications Unit) Operators monitoring and overriding traffic signals
- Deploying all city traffic agents to the hottest congestion hot spots, including Lake Shore Boulevard and Gardiner access points, University Avenue, Front Street and Bay Street
- Reducing the number of rush hour construction exemptions issued
- Returning to pre-pandemic policies for construction near school zones
- Pausing new non-essential utility cut work during the first two weeks of September.
- Deploying school crossing guards at 765 locations
- Activating ‘Smart Signals’ at 17 intersections to independently adjust to real-time traffic conditions
- Accelerating and completing maintenance and connection of more than 900 pieces of technology that detect vehicles and provide valuable congestion insight