Tag: crash data

Chicago Crash Browser is back

May 7, 2022 / / 0 Comments

ChicagoCrashes dot org was, for many years, the only source for people to get information about traffic crashes in Chicago. I started it in 2011.

Chicago Crash Browser v0.2
A screenshot of Chicago Crash Browser v0.2 showing what the website looked like on December 30, 2011.

It was updated annually with data from two years ago, because of how the Illinois Department of Transportation processed the reports from all over the state. I shut it down because it had outdated code, I was maintaining it in my free time, and I didn’t want to update the code or spend all the time every year integrating the new data.

In 2015, the Chicago Police Department started testing an electronic crash reporting system in some districts that meant police officers could write reports and they would immediately show up in a public database (in the city’s data portal). The CPD expanded this to all districts in September 2017. (A big caveat to using the new dataset is that it has citywide data for only four and a half years.)

Since then, whenever someone asked me for crash data (mostly from John to illustrate Streetsblog Chicago articles), I would head to the data portal and grab data from just the block or intersection where someone had recently been injured or killed. I would load the traffic crash data into QGIS and visualize it. I found this also to be painstaking.

Now, with renewed attention on the common and unfixed causes of KSIs (“industry” term for killed or seriously injured) that we’re seeing repeatedly across Chicago – read about the contributing cause of Gerardo Marciales’s death – I decided to relaunch a version of Chicago Crash Browser.

The new version doesn’t have a name, because it’s part of the “Transportation Snapshot” in Chicago Cityscape, the real estate information platform I operate. It’s also behind a paywall, because that’s how Chicago Cityscape is built.

I wanted to make things a lot easier for myself this round and it comes with a lot of benefits:

  • Explore all crash reports in a given area, whether that’s one you draw yourself or predefined in the Cityscape database.
  • Quickly filter by crash type (bicyclist, pedestrian, etc.) and injury severity.
  • Download the data for further analysis.
A screenshot of a map and data table visualizing and describing traffic crash reports in Columbus Park.
What the crash data looks like within Chicago Cityscape.

How to access the Chicago Crash Browser

The crash data requires a Cityscape membership. I created a new tier of membership that cannot be signed up – I must grant it to you. It will give you access only to Transportation Snapshots.

  • Create a free account on Chicago Cityscape. The site uses only social networks for creating accounts.
  • Mention or DM me on Twitter, @stevevance, saying you’d like access to the crash data. Tell me what your email you used to create an account on Chicago Cityscape.
  • I’ll modify your membership to give you access to the “transportation tier” and tell you to sign out and sign back in to activate it.

Once you’re in, this video shows you how to draw a “Personal Place” and explore the traffic crash data there. Text instructions are below.

  1. From the Chicago Cityscape homepage, click on “Maps” in the menu bar and then click “Draw your own map”.
  2. On the “Personal Place” page that appears with a large map, decide which shape you’d like to draw: a circle with a radius that you specify (good for intersections), a square or rectangle (good for street blocks), or an arbitrary polygon (good for winding streets in parks). Click the shape and draw it according to the onscreen instructions. For intersections I recommend making the circle 150 feet for small intersections and 200 feet for long intersections; this is because intersections have an effect on driving beyond the box.
  3. Once you’ve completed drawing the shape, a popup window appears with the button to “view & save this Personal Place”. Click that button and a new browser tab will open with something called a “Place Snapshot”.
  4. In the Place Snapshot enter a name for your Personal Place and click the “Save” button.
  5. Scroll down and, under the “Additional Snapshots” heading, click the link for “Transportation & Jobs Snapshot”; a new browser tab will open.
  6. In Transportation Snapshot, scroll down and look for “Traffic crashes”. You’ve made it to the new Chicago Crash Browser.

Chicago Crash Browser, miraculously, has 2012 bicycle and pedestrian crash data

January 4, 2014 / / 0 Comments

Screenshot shows that you can choose your own search radius. When researching, be sure to copy the permalink so you can revisit your results. 

I’ve upgraded the Chicago Crash Browser, my web application that gives you some basic crash and injury statitics for bicyclist and pedestrian crashes anywhere in Chicago, to include 2012 data. It took the Illinois Department of Transportation eight months to compile the data and it took me four months to finally get around to uploading it into my database. While I spent that time, I made some improvements to the usability of the app and output more information. Since the last major changes I made (back in February 2013) I’ve gained two code contributors (Richard and Robert) making this my first communal project on GitHub.

I know that it’s been used as part of research in the 46th Ward participatory budgeting process for 2013, and by residents in the 26th Ward to show Alderman Maldonado the problem intersections in the Humboldt Park area. Transitized recently included pedestrian crash stats obtained from the Crash Browser in a blog post about pedestrianizing Michigan Avenue in Streeterville.

The first change I made was adding another zoom level, number 19, so you can get closer to the data. I made some changes to count how many people were injured and total them. You can now choose your search distance in multiples of 50 feet between 50 and 200, inclusive. As is typical, I get sidetracked when I notice errors on the map. Thankfully I just fire up JOSM and correct them so the next person that looks at the map sees the correction. Future changes I want to make include upgrading to the latest jQuery, LeafletJS, and Leaflet plugins. I’d also like to migrate to Bootstrap to improve styling and add responsive design so it works better on small screens.

Sign up for the newsletter where I’ll send a couple emails each year describing new changes (I’ve so far only published one newsletter).

Why do speeding crashes in Chicago lead to worse injuries?

November 21, 2013 / / 6 Comments

Don’t git behind me. Photo by Richard Masoner. 

A discussion about Chicagoans’ proclivity for tailgating (on a post about speed cameras) prompted me to look at the prevalence of this in causing crashes. I looked at the three-year period of 2010-2012 first, mainly so the numbers wouldn’t be so large, and left this information in a comment. But considering the prerequisites* for a crash to be reported in this dataset, and my desire to compare two multi-year periods, I switched my analysis to the single four-year period 2009-2012.

2009-2012

Total crashes: 318,193. Total fatalities: 554 people.

Tailgating crashes

62,080 crashes, 19.53% of all crash types

Tailgating crashes, injuries breakdown:

  • Killed: .0012 (this represents the number of deaths per crash). 75 people died in these crashes, representing 13.54% of all deaths.
  • Incapacitating injuries: 8.53% (the average distribution of people’s injuries in all tailgating crashes)
  • Non-Incapacitating: 46.32%
  • Possible injury: 45.15%

The share of all crash types that are tailgating has increased steadily from 18.11% in 2009 to 20.79% in 2012.

Speeding crashes

10,339 crashes, 3.24% of all crash types

Speeding injuries:

  • Killed: .0118 (this represents the number of deaths per crash). 122 people died in these crashes, representing 22.02% of all deaths.
  • Incapacitating injuries: 15.55% (the average distribution of people’s injuries in all speeding crashes)
  • Non-Incapacitating: 51.95%
  • Possible injury: 32.50%

The share of all crash types that are tailgating has decreased slightly from 3.72% in 2009 to 3.02% in 2012. While speeding leads to fewer crashes, it leads to a greater incidence of death and serious injury. The probability of a speeding crash leading to at least one death seems to stay steady through the period while the probability of seeing a person with an incapacitating injury versus a different kind of injury varies more, but not so much in a range that overlaps the rates for tailgating crashes.

A future comparison at injuries should look at the top crash causes for death and serious injury.

N/A and Unable to determine crashes

237,729 crashes, 74.71% of all crash types

N/A and unable to determine injuries:

  • Killed: .0013 (this represents the number of deaths per crash). 305 people died in these crashes, representing 55.05% of all deaths.
  • Incapacitating injuries: 9.38% (the average distribution of people’s injuries in all N/A crashes)
  • Non-Incapacitating: 48.26%
  • Possible injury: 42.35%

Notes

Updated December 4, 2013

I updated the wording on how to interpret these numbers. For example, previously for “killed” there was a percentage saying this number represented the amount of crashes that had at least one death. This wasn’t accurate: the same number represents a rate of deaths per crash of that type. Injury percentages represent the distribution of injury types experienced by all the people injured in crashes of that type.

Reliability

Analyzing crash causes is not very reliable as 45.60% of the reported crashes in 2012 had “N/A” or “unable to determine” listed as the primary cause! The third and fourth most frequently ascribed causes were the two tailgating codes (described below). There are some crashes that had the one of these two causes in the secondary cause field but I haven’t calculated that.

Cause code descriptions

Each crash has two cause codes. For tailgating crashes I searched for reports where “failing to reduce speed to avoid crash” or “following too closely” in either the primary or secondary cause field (it’s possible that a report had both of these causes ascribed). For speeding crashes I searched for “speed excessive for conditions” or “exceeding speed limit” in either the primary or secondary cause fields.

Prerequisites

This data excludes crashes where there was no injury or no property damage greater than $500 (2005 to 2008) and $1,500 (2009 to 2012). You cannot compare the two datasets when you want to see a share of all crashes because the number of “all crashes” will be underreported in the second dataset.

Queries

These are some of the MySQL queries I used to get the data out of my own crash database (I’m figuring out ways to make it public, using a shared login). “Cause 1 code” indicates the primary cause of the crash according to the police officer’s judgement. “Cause 2 code” indicates the secondary cause of the crash according to the police officer’s judgement.

1. Crash cause reliability: SELECt count(casenumber), sum(`Total killed`), `Cause2`, `Cause 2 code` FROM `CrashExtract_Chicago` WHERE year = 12 GROUP BY `Cause 2 code`  ORDER BY cast(`Cause 2 code` as signed)

2. Speeding crashes: SELECT count(casenumber), sum(`Total killed`), sum(`totalInjuries`), sum(`A injuries`), sum(`B injuries`), sum(`C injuries`) FROM `CrashExtract_Chicago` WHERE (`Cause 1 code` = 1 OR `Cause 1 code` = 27 OR `Cause 2 code` = 1 or `Cause 2 code` = 27) AND year > 8

3. Tailgating crashes: SELECT count(casenumber), sum(`Total killed`), sum(`totalInjuries`), sum(`A injuries`), sum(`B injuries`), sum(`C injuries`) FROM `CrashExtract_Chicago` WHERE (`Cause 1 code` = 3 OR `Cause 1 code` = 28 OR `Cause 2 code` = 3 or `Cause 2 code` = 28) AND year > 8

4. N/A and Unable to determine crashes: SELECT count(casenumber), sum(`Total killed`), sum(`totalInjuries`), sum(`A injuries`), sum(`B injuries`), sum(`C injuries`) FROM `CrashExtract_Chicago` WHERE (`Cause 1 code` = 18 OR `Cause 1 code` = 99) AND year > 8

Links between pedestrian safety and crime

October 25, 2012 / / 4 Comments

Chicago Pedestrian Plan

Safety item 20: Analyze the relationship between pedestrian safety and crime (download the plan)

The 2011 Chicago Pedestrian Crash Analysis identified a strong correlation between community areas with high numbers of pedestrian crashes and community areas with high crime rates. Correlation does not indicate causation and further study is necessary to understand this relationship and the potential broader benefits of pedestrian safety improvements. [From page 62 in the 2012 Chicago Pedestrian Plan.]

ACTIONS

Short Term

  • Identify and obtain funding for this study.
  • Identify a location for safety improvements and obtain data for the “before” conditions.

Mid Term

  • Design and implement pedestrian safety improvements.
  • Develop a pedestrian safety enforcement plan for the area for the duration of the project.
  • Analyze the effects on pedestrian safety and crime.

MILESTONES

  1. Initiate this study by 2013 and complete by 2015.

ADDITIONAL RESOURCES

National Highway Traffic Safety Administration. Data-Driven Approaches to Crime and Traffic Safety (DDACTS). 2011. [I don’t fully see the connection, but this reference was linked to a page on NYC Department of Transportation’s website.]

Pedestrian Crash Analysis

The summary report didn’t contain the word “crime”. The technical report contained 2 mentions, with an additional chart. They are quoted in the ordered list below. Download the summary report.

  1. In an examination of various factors including crime, income, race, language spoken, and Walk Score®, the strongest correlation found was between pedestrian crashes and crime
  2. Finally, crime statistics were compared to pedestrian crashes to determine if a correlation could be identified, using data from the Chicago Police Department (CPD) annual reports for 2005 through 2009. The annual reports include incidences of crime by Chicago Community Area (CCA). The statistics for the years 2005 through 2009 were averaged and compared to the aver- age number of fatal and serious injury pedestrian crashes over the same time period in each CCA. Of these factors, crime was the only variable that correlated to pedestrian crashes. Figure 1 shows the correlation between crime and pedestrian crashes was very high. However, there may be many variables responsible for this correlation.
  3. Figure 1: Crime vs. Fatal and Serious Injury Pedestrian Crashes by Chicago Community Area

Figure 1.

I have a few criticisms of this analysis: it lacks raw data; the data tables included in the technical report are of limited length, listing only the “top” items of any metric; the summary report lists many silly factoids; the maps are low resolution and of a limited scale – their design could be modified to improve their usefulness in communicating the crash frequencies of the marked locations. The analysis is reliable.

The technical report includes the state’s guide on how police officers are trained to fill out a crash report form. It also includes relevant crash reporting laws in Illinois. Download the technical report.

Special post for S.M.