The New York Police Department provides data for every motor vehicle collision in NYC since July 2012. Each record includes location coordinates and other metadata, most notably the number of injuries and fatalities, segmented further by motorists, cyclists, and pedestrians.

I wrote some code to process the raw data, and built an interactive heatmap of 1.4 million collisions between July 2012 and January 2019. By default the color intensity represents the number of collisions in each area, but you can customize it to reflect injuries or fatalities.

Click here to view map in full screen or on a mobile device

Turn on javascript (or click through from RSS) to use the interactive map.

Note that the raw data does not identify each collision with pinpoint accuracy, rather collisions are typically rounded to the nearest intersection, which makes some areas look artificially better or worse than they really are. For example, there are a number of collisions at both ends of the Verrazzano Bridge, but apparently none in between. In reality those collisions are likely spread more evenly across the bridge’s span, but the dataset rounds them to either the Brooklyn or Staten Island base.

Dangerous areas

The map shows the areas with the most injuries and fatalities, but I’m hesitant to use the phrase “most dangerous”, as the collisions data does not tell us how many motorists, cyclists, and pedestrians traveled through each area without injury. For example, more pedestrians are injured by motor vehicles in Times Square than in any other area, but Times Square probably has the most total pedestrians, so it’s possible that “pedestrian injuries per mile walked” is higher elsewhere. It might make for interesting further analysis to estimate total vehicle, bicycle, and pedestrian travel in each area, then attempt to calculate the areas with the highest probability of injury or fatality per unit of distance traveled.

Cyclist injuries

Delancey Street on Manhattan’s Lower East Side accounts for the most cyclist injuries of any area. In November 2018, the city installed a new protected bike lane from the Williamsburg Bridge to Chrystie Street, and it will be interesting to see how effective it is in reducing future cyclist injuries. If the L train shutdown—in whatever form it ends up taking—causes more people to bike across the bridge, accidents and injuries might well increase, so as noted above, it will be important to adjust for total usage. The Manhattan base of the Queensboro Bridge also accounts for a significant number of cyclist injuries, and much like at the Williamsburg Bridge, there is an attempt underway to improve cycling conditions.

In Brooklyn, the areas with the most cyclist injuries include Grand Street between Union and Bushwick avenues in Williamsburg, and the section of Tillary Street between Adams and Jay streets downtown. In Queens, stretches of Roosevelt Avenue in Jackson Heights appear particularly dangerous. From Google Maps it appears that none of these three outer borough areas had fully protected bike lanes historically, though at least Grand Street’s bike lane was improved somewhat in the fall of 2018.

Google Street View illustrates some of the challenges cyclists face in these areas, including cars parked in bike lanes:

Tillary & Jay streets, Brooklyn

While I was working on this post, I happened to walk by Tillary & Jay streets one evening with some friends, one of whom captured this video of cyclists contending with a double-decker tour bus:

Video: Edwin Morris

Grand Street & Bushwick Avenue, Brooklyn

Roosevelt Avenue & 94th Street, Queens

I did not do any extensive investigation of the relationship between bike lanes and cyclist injuries, but it would make for interesting further analysis. The Department of Transportation publishes a city bike map along with a shapefile, and provides lists of active and past projects dedicated to bicycle safety, all of which could potentially be used to better understand the relationship between bike lane development and cyclist safety. At a minimum, it’s good to see that some of the areas with the most cyclist injuries have already been targeted for bike lane improvements.

Pedestrian injuries

As mentioned earlier, Times Square accounts for the most pedestrian injuries. Beyond Times Square and the Manhattan central business district more broadly, it looks like there might be a correlation between public transportation stations and pedestrian injuries. Outside of central Manhattan, several of the areas with the most pedestrian injuries are located near subway or rail stations, including:

I’d imagine that areas immediately surrounding subway stops have some of the highest rates of foot traffic, so it could be simply that more pedestrians equals more injuries. Or maybe subway stops tend to be located on busier, wider roads that are more dangerous to cross. It would be interesting to know if there are particular subway stations that have high or low pedestrian collision rates compared to their total usage, and if so, what features might distinguish them from other stations.

Motorist injuries

Motorist injuries are more geographically spread out than cyclist and pedestrian injuries, I would guess due to more vehicle travel at higher speeds in the outer boroughs compared to Manhattan. Highways look to account for many of the areas with the most motorist injuries: in the Bronx, sections of the Cross Bronx Expressway and Bronx River Parkway, along with the Van Wyck Expressway and Belt Parkway in Queens, and the western terminus of the Jackie Robinson Parkway in Brooklyn.

Trends by borough and neighborhood

The city’s Vision Zero plan has the stated goal of eliminating all traffic deaths by the year 2024, and in general, traffic fatalities have been declining since 2012. One piece of confusion: the city recently announced that there were 200 traffic deaths city-wide in 2018, but the NYPD dataset reports 226 deaths in 2018. I’m not sure why those numbers are so different, but either way the trend still points toward decreasing fatalities.

The number of injuries per year has increased, though, and there are individual neighborhoods that have seen improving or worsening trends. To cherry-pick a few examples: Union Square, Chinatown, and East Harlem have seen some of the bigger reductions in injuries since 2012, while University Heights, Mott Haven, and East New York have seen injuries increase.

You can view trends city-wide, by borough, or by neighborhood (map) using the inputs below:

Turn on javascript (or click through from RSS) to select boroughs/neighborhoods.

New York City Bronx Brooklyn Manhattan Queens Staten Island

Select a neighborhood… Allerton/Pelham Gardens Bedford Park Belmont Bronx Park Bronxdale City Island Claremont/Bathgate Co-Op City Country Club Crotona Park Crotona Park East East Concourse/Concourse Village East Tremont Eastchester Fordham South Highbridge Hunts Point Kingsbridge Heights Longwood Melrose South Morrisania/Melrose Mott Haven/Port Morris Mount Hope Norwood Parkchester Pelham Bay Pelham Bay Park Pelham Parkway Rikers Island Riverdale/North Riverdale/Fieldston Schuylerville/Edgewater Park Soundview/Bruckner Soundview/Castle Hill Spuyten Duyvil/Kingsbridge University Heights/Morris Heights Van Cortlandt Park Van Cortlandt Village Van Nest/Morris Park West Concourse West Farms/Bronx River Westchester Village/Unionport Williamsbridge/Olinville Woodlawn/Wakefield

Select a neighborhood… Bath Beach Bay Ridge Bedford Bensonhurst East Bensonhurst West Boerum Hill Borough Park Brighton Beach Brooklyn Heights Brooklyn Navy Yard Brownsville Bushwick North Bushwick South Canarsie Carroll Gardens Clinton Hill Cobble Hill Columbia Street Coney Island Crown Heights North Crown Heights South Cypress Hills Downtown Brooklyn/MetroTech DUMBO/Vinegar Hill Dyker Heights East Flatbush/Farragut East Flatbush/Remsen Village East New York East New York/Pennsylvania Avenue East Williamsburg Erasmus Flatbush/Ditmas Park Flatlands Fort Greene Gowanus Gravesend Green-Wood Cemetery Greenpoint Homecrest Kensington Madison Manhattan Beach Marine Park/Floyd Bennett Field Marine Park/Mill Basin Midwood Ocean Hill Ocean Parkway South Park Slope Prospect Heights Prospect Park Prospect-Lefferts Gardens Red Hook Sheepshead Bay South Williamsburg Starrett City Stuyvesant Heights Sunset Park East Sunset Park West Williamsburg (North Side) Williamsburg (South Side) Windsor Terrace

Select a neighborhood… Alphabet City Battery Park Battery Park City Bloomingdale Central Harlem Central Harlem North Central Park Chinatown Clinton East Clinton West East Chelsea East Harlem North East Harlem South East Village Financial District North Financial District South Flatiron Garment District Gramercy Greenwich Village North Greenwich Village South Hamilton Heights Highbridge Park Hudson Sq Inwood Inwood Hill Park Kips Bay Lenox Hill East Lenox Hill West Lincoln Square East Lincoln Square West Little Italy/NoLiTa Lower East Side Manhattan Valley Manhattanville Marble Hill Meatpacking/West Village West Midtown Center Midtown East Midtown North Midtown South Morningside Heights Murray Hill Penn Station/Madison Sq West Randalls Island Roosevelt Island Seaport SoHo Stuy Town/Peter Cooper Village Sutton Place/Turtle Bay North Times Sq/Theatre District TriBeCa/Civic Center Two Bridges/Seward Park UN/Turtle Bay South Union Sq Upper East Side North Upper East Side South Upper West Side North Upper West Side South Washington Heights North Washington Heights South West Chelsea/Hudson Yards West Village World Trade Center Yorkville East Yorkville West

Select a neighborhood… Astoria Astoria Park Auburndale Baisley Park Bay Terrace/Fort Totten Bayside Bellerose Breezy Point/Fort Tilden/Riis Beach Briarwood/Jamaica Hills Broad Channel Cambria Heights College Point Corona Douglaston East Elmhurst East Flushing Elmhurst Elmhurst/Maspeth Far Rockaway Flushing Flushing Meadows-Corona Park Forest Hills Forest Park/Highland Park Fresh Meadows Glen Oaks Glendale Hammels/Arverne Hillcrest/Pomonok Hollis Howard Beach Jackson Heights Jamaica Jamaica Bay Jamaica Estates JFK Airport Kew Gardens Kew Gardens Hills LaGuardia Airport Laurelton Long Island City/Hunters Point Long Island City/Queens Plaza Maspeth Middle Village Murray Hill-Queens North Corona Oakland Gardens Old Astoria Ozone Park Queens Village Queensboro Hill Queensbridge/Ravenswood Rego Park Richmond Hill Ridgewood Rockaway Park Rosedale Saint Albans Saint Michaels Cemetery/Woodside South Jamaica South Ozone Park Springfield Gardens North Springfield Gardens South Steinway Sunnyside Whitestone Willets Point Woodhaven Woodside

Select a neighborhood… Arden Heights Arrochar/Fort Wadsworth Bloomfield/Emerson Hill Charleston/Tottenville Eltingville/Annadale/Prince’s Bay Freshkills Park Great Kills Great Kills Park Grymes Hill/Clifton Heartland Village/Todt Hill Mariners Harbor New Dorp/Midland Beach Oakwood Port Richmond Rossville/Woodrow Saint George/New Brighton South Beach/Dongan Hills Stapleton West Brighton Westerleigh

Note that the borough totals won’t necessarily add up to the city-wide total because about 5% of collisions are missing location data. The earlier data is more likely to be missing location data, which means that the graphs by borough are probably slightly pessimistic, and in reality the earlier years have a few more collisions and injuries relative to the recent years than otherwise stated. See this spreadsheet for a table of counts by borough and year, including collisions with unknown geography.

Contributing factors, vehicle types, and further work

I’ve already noted a few potential topics for future work: population-adjusted collision rates and the impact of bike lanes/subway stations, but the dataset could be useful for many other analyses. Especially in the context of my previous post about taxi and Citi Bike travel times, I wonder about the relationship between increasing road congestion, slower average vehicle speeds, and fewer traffic-related fatalities.

Collisions are most common during daytime hours, when congestion is at its worst, but the likelihood of a collision resulting in an injury or fatality is highest during the late night/early morning hours. The dataset does not include detailed information about speed at the time of collision, but it seems likely that vehicles would be traveling faster at off-peak hours when there is less traffic. Darkness could also be an important factor, with differing effects on each of motorists, cyclists, and pedestrians.

The fatality rate is highest at 4 AM, which is last call for alcohol at NYC bars. The dataset includes contributing factors for each collision—albeit in a somewhat messy format—and sure enough the percentage of collisions involving alcohol also spikes at 4 AM:

Among collisions where alcohol is cited as a contributing factor, 30% result in an injury and 0.4% result in a fatality, compared to 19% and 0.1%, respectively, for collisions where alcohol is not cited. Many “correlation does not imply causation” caveats apply, including that alcohol involvement might be correlated with other factors that impact likelihood of injury, or there could be a bias in reporting alcohol as a factor given that the collision resulted in an injury or fatality.

I experimented a bit with regularized logistic regressions to model probability of injury and fatality as a function of several variables, including time of day, street type (avenue, street, highway, etc.), contributing factors, vehicle types, and more. The models consistently report a positive association between alcohol involvement and likelihood of injury and fatality, though in both cases the effect is not as strong as other factors like “unsafe speed” and “traffic control disregarded”. The model reports that collisions involving bicycles are the most likely to result in injuries, while collisions involving motorcycles are the most likely to result in fatalities. It will be interesting to see what happens if new vehicle types like electric scooters gain more widespread adoption.

Again the regression model cannot prove causation, but it’s still interesting to see which factors are most associated with injuries. The relevant code is available here on GitHub if you want to poke around more.

Population growth, gentrification, Citi Bike’s expansion, and various other traffic control mechanisms (speed limits, crosswalks, traffic lights, etc.) all come to mind as possible areas for further study, and kudos to the City of New York for making so much of the data publicly available.

Technical notes, code on GitHub

The code used to collect and process the collisions data is available here on GitHub.

The interactive map is built with deck.gl and Mapbox.

The map embedded and linked in this post uses pre-aggregated data, which helps performance, but limits the number of filters available. If you want to go a bit deeper, there is a similar version of the map available here that aggregates on the fly, and therefore allows a few extra filters: time of day, number of vehicles involved, and injury status. Note though that this “on the fly” version is much slower to load, and likely will not work on mobile devices.