How the rankings are built

Sources

• Traffic counts — City of Toronto, Traffic Volumes – Multimodal Intersection Turning Movement Counts, "most recent summary" table: one row per intersection with the latest count's totals by mode and approach. Refreshed daily by the City; this build uses counts through Aug 26, 2026.
• Serious-injury collisions — City of Toronto, Motor Vehicle Collisions involving Killed or Seriously Injured Persons, sourced from Toronto Police Service. One row per involved person since 2006; this build uses records through Aug 29, 2026.
• Red-light cameras — City of Toronto, Red Light Cameras. 301 locations.
• All collisions — Toronto Police Service, Traffic Collisions Open Data: every collision reported to police since 2014 — property damage only, fail-to-remain, injury and fatal — one row per event with its location and who was involved. 825,265 events in this build, 556,188 within 65 m of a counted intersection.

Two ways to count collisions

The most collisions rankings use the police dataset — the big number, dominated by property-damage collisions, which tracks volume closely. The most dangerous rankings use the City's KSI dataset — only collisions in which someone was killed or seriously injured, a far smaller number that says more about consequence than frequency. Every intersection page shows both, and neither is a statement about fault.

Names

The City names each node by every road that meets there ("Spadina Ave / Bloor St W / Spadina Rd"). Pages use the spoken two-street form — "Bloor & Spadina" — chosen by rule: ramps, trails and river names are dropped, a road that continues under a different name is counted once, east/west or north/south halves are merged, the more prominent street (the one appearing at more intersections citywide) goes first, and a short list of well-known pairs overrides that order ("Jane & Finch", "King & Spadina"). The formal name and the City's node name appear under every heading.

What an intersection is

An intersection is a node in the City's centreline network. Its name is the City's own (e.g. "Kennedy Rd / Lawrence Ave E"), shown here with an ampersand. An intersection gets a page when it has a traffic count dated Jan 1, 2015 or later, or at least one KSI collision matched to it. 5,825 of 6,112 counted intersections qualify in this build.

Matching collisions to intersections

Each collision record carries coordinates. KSI person-level rows are first combined into one collision per collision ID; police records are deduplicated by event ID. A collision is attributed to the nearest intersection node within 65 metres — roughly the width of a six-lane arterial crossing — whether the police coded it as intersection-related or mid-block; beyond 65 m it is attributed to no intersection. In this build 5,211 of 7,598 KSI collisions matched an intersection.

A collision counts as fatal if any involved person's record is classed Fatal; as involving a pedestrian / cyclist / motorcyclist if the City flags that road user in the collision; and as in darkness if the light condition is recorded as dark (with or without street lighting).

Windows and comparability

• Collision rankings use the last ten complete years, 2016–2025. Records can take a year or more to be finalized, so the current year is never ranked. All-time counts since 2006 appear on each page for context.
• Busiest rankings use 14-hour counts only. Before September 2023 the City counted for 8 non-continuous hours; since then, 14 continuous hours. The two are not comparable, so older counts are shown on intersection pages but not ranked. Each figure is one day's count, not an annual average.
• Highway ramps and collector-lane nodes (names containing "Hwy", "Ramp", "Collector", "Express") are excluded from the busiest rankings because they are not what people mean by a busy intersection.
• Exposure-adjusted rate (KSI per year per 10,000 daily vehicles) is shown only where an intersection has at least five KSI collisions in the window and a 14-hour count, to avoid ranking on noise.

Red-light cameras

Cameras are joined to intersections by the City's intersection ID, falling back to the nearest node within 40 m. Ontario ended automated speed enforcement on 14 November 2025; speed-camera locations are therefore historical and are not shown as active.

Tickets. The City publishes Red Light Camera Annual Charges as a spreadsheet: one row per camera site, one column per year since 2007. It is joined to the camera list by the City's location code (the spreadsheet numbers sites from 2501, the camera list from 6001 — the same sites, offset by 3,500), with a fallback on the two street names. "Charges" are tickets issued, not convictions. The current year is partial — the file states the cut-off date and the pages repeat it — so rankings use the last complete year. Sites the City has decommissioned stay in the spreadsheet and are listed separately with their totals. In this build 301 of 301 cameras matched a ticket record (0 by street name).

Collisions recorded after the window closed (from January 2026 to the latest date in each dataset) are never hidden: they appear on the intersection page as a separate "since January" line in the cards, tables and text, and a fatal one is stated in the first paragraph. They are simply not part of the ranking, which needs complete years.

"What's here" layers

Each layer is a straight-line proximity join from the intersection node, computed at build time from a City dataset. Distances are as the crow flies, not walking distance.

• Bikeways — a Cycling Network segment passing within 30 m; the segment's highest-order infrastructure type is shown. "Protected" means a cycle track or multi-use trail.
• Getting here (within 1 km) — every agency's GTFS schedule feed is read at build time: TTC (subway stations with their lines, streetcar and bus routes with the nearest stop for each), GO Transit (rail stations with their lines, GO bus routes), UP Express, VIA Rail, and the regional agencies that cross into Toronto — MiWay, Durham Region Transit, Brampton Transit and York Region Transit — where their feeds are available. A route counts if any of its stops is within 1 km; the distance shown is to that nearest stop. Because the feeds describe the timetable in force on the build date, a temporary diversion or replacement bus appears exactly as the agency schedules it — a streetcar route listed on a street it does not normally use is usually that. The "at the corner" chips still use 100 m for stops and 250 m for a station. GO and UP Express data is provided with permission of Metrolinx.
• Within walking distance (1.5 km) — schools, parks, community centres and arenas, Toronto Public Library branches and the City's Places of Interest and Attractions list, each with straight-line distance; counts are of everything within the radius, the nearest few are named. The "near schools" rankings keep the stricter 250 m rule.
• Bike Share — stations within 150 m for the chip, and the nearest dock plus the count within 1 km, from the live GBFS station list.
• Parking (within 2 km) — three sources. Every lot: the City's topographic mapping of parking-lot footprints (about 19,000 polygons drawn from aerial photography — surface lots of any ownership, public or private, but not underground or structured garages unless their footprint is visible); each lot's area is measured and spaces are estimated at one per 30 m², the usual planning rule of thumb, so treat those figures as approximate. Lots within 45 m of a Green P car park are flagged Green P; the rest are private, commercial or institutional. Green P: the Toronto Parking Authority's car-park list (a 2019 snapshot — the City retired the feed) with spaces and average daily peak occupancy from the quarterly Parking Occupancy dataset where the car-park number matches. EV charging: City-operated stations with Level 2 and fast-charge port counts; private networks are not included. Bike parking: post-and-rings within 300 m, racks and corrals with capacity within 600 m, indoor bike stations within 2 km. On-street car parking is not included anywhere.
• Signal features — from Traffic Signals Tabular, joined by node ID then signal number: accessible (audible) pedestrian signal, leading pedestrian interval by direction, transit priority, bicycle signal, activation year.
• Pedestrian crossover — a PXO within 30 m.
• Live traffic camera — the City's RESCU camera list (336 cameras, with a still image the City refreshes every few minutes) joined to the nearest node within 110 m. The page shows the City's 320 × 240 image directly, never enlarged beyond twice its size; a small server function reads the City's Last-Modified header so the card can show how old the frame is and whether a reload brought a new one. The four fixed-direction reference stills (199 × 112) are shown at their own size.
• Measured speeds — the City's midblock speed, volume and classification counts (automatic tube counters laid across a road for one to seven days, recording every vehicle). For each intersection the most recent count on each of its own streets within 400 m is chosen — matched by street name, preferring counts that recorded speed — and shown with its date, daily volume, average, 85th- and 95th-percentile speeds. A midblock reading describes the block, not the movement through the intersection, and the City counts on request rather than on a schedule, so some readings are years old.
• School-zone speed sign — the nearest permanent Watch Your Speed radar sign within 400 m that has a monthly summary in the last 18 months. The City publishes vehicle counts in 5 km/h bins, so "over the limit" sums the bins above the posted limit and "10 km/h or more over" the bins from limit + 10 upward; the bin containing the limit itself is counted as at the limit. Months with fewer than 300 vehicles are ignored.
• Traffic calming — the Vision Zero unit's Traffic Calming Database, keyed by the same intersection IDs the centreline uses; a street segment is shown when either of its end intersections is this one. Planned installations are labelled as such.
• Ward and BIA — point-in-polygon against the 25 ward boundaries (with the sitting councillor from the same City file) and the Business Improvement Area boundaries.
• Restaurants and food — Toronto Public Health's DineSafe file lists every inspection of every food premises with the establishment's coordinates. One point per establishment is kept, with its latest inspection date, result (pass, conditional pass, closed) and the number of infractions noted on that visit. The current file carries no establishment-type column, so kitchens inside schools, child care centres, care homes, places of worship, offices, caterers and the like are screened out by name, and grocery, convenience, pharmacy, liquor, bakery and butcher shops are split from "eating places" the same way — a rule that will misfile the odd premises. Counts are within 300 m and 1 km; the nearest eight are named.
• Public washrooms and drinking water — three City lists merged: park washrooms (with the seasonal open/closed status and reason the City publishes), washrooms in City-operated buildings (civic centres, community centres, libraries where listed, with hours and an accessibility flag) and the automated street toilets. The nearest three within 1 km are shown, one per building. Drinking fountains and bottle fillers come from the parks water-sources list, within 600 m. Washrooms in malls, shops, restaurants and TTC stations are not in any of these lists.
• Child care — the City's licensed child care centres, within 1 km: licensed spaces by age group, whether the centre has a fee-subsidy contract with the City and whether it is enrolled in the Canada-Wide Early Learning and Child Care ($10-a-day) program. Spaces are licensed capacity, not vacancies; home child care is not included.
• Emergency services — the nearest fire hall, police division (division buildings only, not headquarters or units) and ambulance station within 5 km, straight-line. Response is dispatched by availability, not proximity, so the nearest station is not necessarily the one that would answer a call.
• Thefts at the corner — Toronto Police's Theft From Motor Vehicle and Bicycle Thefts files carry a location for every occurrence, but the police first move each one to the nearest intersection to protect victims' privacy. Because that is exactly our node set, an occurrence is joined to the node within 65 m of its published point — a match on the police's own key rather than a spatial guess. Counts use the same 2016–2025 window as collisions, with the most recent three years and the current year shown separately, and the two most common premises types. Other offences (auto theft, break and enter, robbery, assault) are published by neighbourhood only.
• Apartment buildings — the City's RentSafeTO register (rental buildings of three or more storeys and ten or more units), within 1 km. The roll is imported from LandlordReport, a sister site that keeps one page per registered building, so each building here links to the same page there and carries the counts it computes: the latest City evaluation score out of 100, final Landlord and Tenant Board orders naming the address in the latest half-year of Ontario's order catalogue, and open fire-code violations from Toronto Fire Services' inspection data. If that import is absent the build falls back to the City's registration and evaluation files directly (score and coordinates only). Buildings without coordinates in either file are left out; condominiums and houses are not registered and are not counted.
• Neighbourhood crime rates — Toronto Police's Neighbourhood Crime Rates: yearly counts and rates per 100,000 residents for nine categories by neighbourhood, using the City's population estimates. The site shows the latest complete year, the citywide rate for the same year (all neighbourhoods' counts over all neighbourhoods' population), the ratio between the two, and the change in the neighbourhood's own rate over five years. The "major crimes" figure sums the five Major Crime Indicators the police use — assault, auto theft, break and enter, robbery and theft over $5,000 — and the ranking is by that combined rate. Rates are per resident, which flatters residential neighbourhoods and penalises places with big daytime populations.
• Census profile — the City's Neighbourhood Profiles for the 2021 Census, 158-neighbourhood model: population, median age, median household income (2020), owner and renter households, dwelling types (apartments of five or more storeys, single-detached houses) and main mode of commuting. Density divides the census population by the area of the neighbourhood boundary polygon.
• Neighbourhood — point-in-polygon against the City's 158 neighbourhood boundaries; Neighbourhood Improvement Areas flagged from the City's classification. Neighbourhood KSI totals count every collision the City assigns to the neighbourhood, including those not matched to a counted intersection.

Layers are best-effort: if a source is unavailable when the site is rebuilt, that layer is left blank rather than stale.

What this site does not claim

• "Most dangerous" means most recorded serious-injury collisions. It is not a statement about cause, fault, road design or the behaviour of anyone involved.
• Counts reflect the day they were taken. Volume changes with construction, season and the count's own timing.
• No personal information is published. Person-level collision records are aggregated to counts; nothing on this site identifies an individual.

Licences

Contains information licensed under the Open Government Licence – Toronto. Collision data originates with Toronto Police Service and is published by the City under the same licence. Corrections and questions: see the data page.