City of Vaughan

As more people take part in informal outdoor activities, popular parks, trails, and open court spaces are becoming busier, often at the same times of day. Since the City does not have clear information about when and where demand is highest:  

• Users often make multiple trips to already crowded locations, sometimes without realizing how busy they are.  
• Certain popular parks become overcrowded, while nearby facilities remain underutilized 
• Bike paths, walking routes, and park entrances experience uneven and unpredictable levels of use. 
• The City lacks the data needed to make informed decisions about  active transportation planning, where to invest in infrastructure, and how to design services. 

This situation is similar to how transportation systems operated before real-time traffic and transit information became available, when people and planners had limited visibility into congestion and travel patterns. 

High-use outdoor sports courts (pickleball and tennis) act as major local trip generators for pedestrians, cyclists, micromobility users, and short vehicle trips. These facilities currently operate on a first-come, first-serve basis with no real-time visibility into space availability, demand intensity, dwell time, or queue length. 

Residents often travel to these destinations without knowing whether courts are occupied, resulting in unnecessary trips, localized congestion, informal queuing, and inefficient circulation within park pathways, sidewalks, and adjacent streets. 

 From a mobility systems perspective, there is a significant opportunity for the City to enhance real-time and predictive demand intelligence to better understand how people travel to, wait for, and circulate around high-demand public destinations. 

• Ability to collect real-time demand information and assess the needs for planning purposes
• Ability to provide real-time demand information to users so they can have improved user experience in utilizing these public spaces.
• Reduce unnecessary travel to congested public destinations
• Improve circulation and flow within high-use public spaces
• The ability to redistribute demand to nearby, underutilized facilities
• Test scalable smart-mobility technologies applicable to other public-realm nodes
• Collect data to support future planning, policy, and infrastructure investment

Pilot at select high-demand outdoor court locations that:

• Generate consistent pedestrian and cycling traffic
• Include multiple courts and predictable peak periods
• Are located near sidewalks, trails, or transit-accessible corridors

Examples:

• Carrville Community Centre, located at 65 Thomas Cook Ave.
• LeParc Park, located at 172 Connie Crescent

• Non-intrusive occupancy detection sensors (e.g., motion sensors, computer vision, IoT, edge devices)
• Cloud-based analytics platform
• AI / machine-learning models for occupancy detection, dwell time, and demand forecasting
• Public-facing real-time dashboard or mobile-friendly interface
• Optional user input layer for preferred visit times and destinations

Apply by 11:59pm Wednesday, June 10, 2026.

Sports fields are connected by the City’s transportation network, often reached by sidewalks, trails, bike routes, and local roads. When field conditions change rapidly due to rain or poor drainage, decisions to close may not reflect actual conditions in real time, causing: 

• People may make unnecessary trips to parks or arrive only to find fields closed 

• Nearby fields and facilities may become overused as users redirect their activities 

• City staff may need to travel more frequently to conduct repeat field inspections 

This challenge is similar to how transportation systems operated before real-time traffic, road condition, and transit information was available. The challenge explores whether sensor-based condition monitoring can provide timely informed decision-making, therefore, reduce unnecessary travel, and improve flow to public destinations. 

City sports fields and park-based recreation destinations are significant local trip generators for pedestrians, cyclists, micromobility users, and short vehicle trips. However, decisions to close or reopen sports fields due to wet or unsafe conditions currently rely on manual inspections, which are time-consuming, subjective, and constrained by staff availability and weather timing.

The lack of real-time, objective field-condition data results in: 

• Delayed decision-making in the whether the parks or sports fields should be closed or remained open
• Residents and user groups travelling to fields that are closed or unsafe
• Unnecessary vehicle, walking, and cycling trips to unavailable destinations 
• Localized congestion and circulation challenges around parks and access routes 
• Reduced predictability for residents who walks/ cycle resulting in poor user experiences

• Improve user experience, especially those who are walking and biking, by providing real-time field condition information 
• Reduce unnecessary trips to unavailable or unsafe destinations 
• Improve circulation and access management around high-use parks / sports fields
• Increase consistency, transparency, and defensibility of closure and reopening decisions 
• Reduce staff travel and manual inspection requirements 
• Generate condition and demand data to inform: 
  • Park access design 
  • Field drainage and asset investment decisions 

Pilot at select sports fields that: 

• Experience frequent closures due to saturation or drainage issues 
• Are located near trails, sidewalks, or mixed-use park circulation routes 

Options (Location with multiple fields): 

• Concord/ Thornhill Regional Park (Soccer and baseball fields) 
• Maple Community Centre/ District Park 

• IoT soil moisture and ground-condition sensors installed at pilot fields 
• Connectivity infrastructure (cellular / LTE / LoRaWAN as appropriate) 
• Data platform aggregating: 
  • Real-time sensor readings 
  • Historical field condition data 
  • Weather forecasts and rainfall intensity 
• AI / predictive analytics to estimate: 
  • Saturation thresholds 
  • Drying and recovery time 
  • Projected reopening windows 
• Public-facing dashboard displaying: 
  • Traffic-light status (Red / Yellow / Green) 
  • Plain-language explanations 
  • Estimated time-to-availability for trip planning 

Apply by 11:59pm Wednesday, June 24, 2026.

Arterials around the southeast Vaughan are now undergoing major constructions. 

Bathurst Street, south of Steeles Avenue West on the Toronto side, will be undergoing road safety improvements, watermain upgrades and cycle track additions. Bathurst Street, north of Steeles Avenue West on the Vaughan side, will be widening from Highway 7 to Major Mackenzie Drive. On Yonge Street in both Toronto and Vaughan, Yonge Street will see major construction related to the Yonge North Subway Expansion.

While major arterials are typically organized in grids approximately 2km apart, a major east-west arterial is much needed between Steeles Avenue and Highway 7 to alleviate east-west traffic and prevent traffic infiltration onto Vaughan’s local and collector roads as raised by local residents in the area. In addition, while truck restrictions are in place, there are also concerns regarding illegal truck movements and enforcement has been a challenge.

The limited east-west connectivity is causing traffic diversion onto local and collector roads, particularly along Centre Street, raising safety and congestion concerns.

While there are currently ways to track vehicle movements through different smartphone applications, these methods are not accurate in determining the actual number of vehicles on the road and are unable to reliably identify vehicle types (private car/ bus/ truck/ etc.).

The city is a looking for a solution that can:

• Identify both the volume and types of vehicles using local and collector roads in the city’s southeast quadrant, with a specific focus on the Centre Street corridor between Yonge Street and Bathurst Street.
• Overcome current limitations of license plate recognition (LPR) technology, which can track vehicles between two or more entry and exit points to help identify potential traffic infiltration but cannot reliably determine vehicle type without access to government databases.
• Address truck-specific detection challenges, including inconsistent license plate placement, overhanging obstructions, and the presence of multiple plates on trailers, all of which can reduce identification accuracy.
• Ensure reliable vehicle matching over longer travel distances, as entry and exit points may be up to 2km apart. To maintain accuracy and vehicle identifiability under these conditions, supplementary technologies—such as AI-based vehicle recognition or other advanced detection systems—would be required.

(Baseline) Identify current traffic conditions 

• The total regular traffic (auto cars) volume at entry and exit points 
• Total Truck volumes at the entry and exit points 

(Optional) Capture traffic conditions during future construction in Spring/ early summer 2027 for comparison to the baseline traffic conditions 

• The total regular traffic (auto cars) volume at entry and exit points 
• Total Truck volumes at the entry and exit points  
• Net increase in regular and truck traffic at the entry and exit points 
• Identify infiltration traffic and origin/destination pattern based on deviations from the (average) travel time for road segments  

• Centre Street between Bathurst Street and Yonge Street 

• Clark Avenue between Bathurst Street and Yonge Street 

The hardware equipment should be ideally mountable on a utility pole at a height sufficient to mitigate vandalism as well as observe and identify vehicle (type and license plates) over multiple lanes of traffic (up to 4-5 lanes of two-way traffic). 

This unit must be self-powered for at least 24+ hours and be time-programmable to conserve power until the monitoring time periods. 

Apply by 11:59pm Tuesday, June 30, 2026.