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