Locations of car, bicycle, and pedestrian crashes in Chicago from 2009-2013
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Chicago Crash Browser

Demo the Chicago Crash Browser - will load the intersection of 18th Street and Blue Island Avenue.

The Chicago Crash Browser is an interface for the automobile crash data from the Illinois Department of Transportation (IDOT). Crash data for Chicago in 2005-2013 where a bicyclist or pedestrian was the first point of impact by a driver's automobile, as collected by responding law enforcement and maintained by IDOT.

2014 crash data was obtained December 24, 2015. Use of crash data must now be accompanied by this disclaimer:

The Division of Traffic Safety requires the following statement be placed on any work product that incorporates or references our data. DISCLAIMER: The motor vehicle crash data referenced herein was provided by the Illinois Department of Transportation. The author is responsible for any data analyses and conclusions drawn.

##Purpose The purpose of the Crash Browser is two fold:

  1. Give planners, politicians, and policy makers the tools and information they need to make good decisions and prioritization about where to make investments about transportation safety.

  2. Give activists and advocates the information they need to demand change in the transportation system in the most effective way.

##Data The Chicago Crash Browser uses only one of the three tables the state provides, called "CrashExtract". It's called this because the crash data is an extract from the entire database, extracted by year and city. Whenever the whole state was provided, all cities except Chicago ("City Code" != 1051) were stripped and uploaded to a PostgreSQL PostGIS-enabled database.

Get the data

All of the data links are in the Data page.



Since this is an open source project, you can clone/fork it and build or adapt your own version, for Chicago or anywhere else. After you clone it to your computer, run these commands in the Terminal:

npm install && bower install && gulp replaceProd

Then point your web browser to the /dist folder.

##API The API returns JSON and has the following GET parameters:

  • distance (in feet). This is capped at 1,000 feet.
  • north, south, east, west (to create a bounding box inserted as a WHERE statement to reduce the dataset search time)
  • lat (latitude)
  • lng (longitude)

Example call


In the webpage, the bounds are obtained via Leaflet.

The records' WGS84 (EPSG:4326) coordinates are converted to EPSG:3436 (Illinois StatePlane West feet) to be able to search distance in feet (this may not be the best method). This is the data's original projection although the records' WGS84 coordinates (provided by the data author) are the actual fields used.


  • First Chicago bike crash map created in February 2011
  • Derek Eder created an enhanced version a bit later
  • Lots of press for the Chicago bike crash map in 2011
  • Attempted to create a public browser later in 2011, to get more details about the crashes, especially after I obtained additional years of data
  • IDOT asks me to remove the links to the data dumps in March 2015. I did. I put the links back up in March 2016 because IDOT changed their boneheaded policy on who can have access to this vital public health and safety data.

Stay updated


  • Michael Carney and Sebastian Lew (who got me interested in automobile crash data in the first place after they asked if I had it)
  • Richard Lee who made the first social edits via GitHub
  • Robert Guico who installed Bower (for dependencies) and cleaned up a lot of the JavaScript
  • Lori and Charles at IDOT (for providing the data)
  • Jerad Weiner
  • Amanda Woodall at Active Transportation Alliance (for helping me understand the data)
  • Derek Eder and Nick Rougeux
  • Cory Mollett (for PostgreSQL and Amazon Web Services help)
  • Ryan Lakes
  • Nabil Nazha
  • Bill Vassilakis
  • Trina Chiasson
  • Smart Chicago Collaborative for hosting the site
  • Everyone who appreciates this work.

##Cities outside Chicago## I have no plans to include cities outside Chicago because of the amount of work it takes cleaning up the state's data.