Monthly Traffic Safety Analysis

2,539 CRASHES IN
CHICAGO, IL
FEBRUARY 2016

During February 2016, Chicago experienced a total of 2,539 traffic crashes. Notably, there were no fatalities reported during this period, and 166 individuals sustained injuries. The most significant finding is that 94.9% of all crashes resulted in no reported injuries.

2,539

Total Crash Events

0

Persons Killed

166

Persons Injured

26.0%

Hit-and-Run Rate

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 5 crashes with unreported severity are not shown in the severity breakdown.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Aggregate counts from crash, person, and vehicle records

659

Hit-and-Run Crashes — February 2016

In February 2016, 659 crashes were identified as hit-and-run incidents, accounting for 26% of all reported crashes. It is important to note that hit-and-run status is based on the initial determination made by the responding officer at the scene.

Vulnerable Road User Casualties

During February 2016, there were no fatalities reported for pedestrians, cyclists, or motorists. However, 146 motorists sustained injuries, making them the most impacted group. Additionally, 16 pedestrians and 4 cyclists were injured in crashes.

0

Pedestrians Killed

0

Cyclists Killed

0

Motorists Killed

16

Pedestrians Injured

4

Cyclists Injured

146

Motorists Injured

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crashes in February 2016 most frequently occurred on Fridays, with 443 incidents reported. The peak hour for crashes was 3 PM, recording 216 incidents. The majority of crashes, 1,571, took place during daylight hours, compared to 564 in darkness on lighted roads and 120 in complete darkness.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Crash date field aggregated by weekday

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

A significant 94.9% of the 2,539 crashes in February 2016 resulted in no injuries, totaling 2,409 incidents. Injury crashes accounted for 5.1% of the total, comprising 14 serious injuries (0.6%), 43 minor injuries (1.7%), and 68 possible injuries (2.7%). No fatal crashes were reported during this period.

Outcome by Severity (Crash Events)

Serious Injury14serious injury crashes0.6%
Minor Injury43minor injury crashes1.7%
Possible Injury68possible injury crashes2.7%
No Injury2,409no injury crashes94.9%

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · KABCO injury classification scale

Severity Distribution

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor to crashes was 'FOLLOWING TOO CLOSELY', accounting for 322 incidents or 12.7% of the total. This was followed by 'FAILING TO YIELD RIGHT-OF-WAY' with 239 incidents (9.4%) and 'DRIVING SKILLS/KNOWLEDGE/EXPERIENCE' with 169 incidents (6.7%). These three factors collectively represent a substantial portion of identified contributing circumstances.

Officer-Reported Primary Contributing Cause

FOLLOWING TOO CLOSELY322 (12.7%)
FAILING TO YIELD RIGHT-OF-WAY239 (9.4%)
DRIVING SKILLS/KNOWLEDGE/EXPERIENCE169 (6.7%)
IMPROPER OVERTAKING/PASSING134 (5.3%)
IMPROPER BACKING123 (4.8%)
IMPROPER LANE USAGE121 (4.8%)
IMPROPER TURNING/NO SIGNAL102 (4%)
FAILING TO REDUCE SPEED TO AVOID CRASH71 (2.8%)
WEATHER55 (2.2%)
DISREGARDING STOP SIGN25 (1%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes occurred under clear weather conditions (1,939 incidents, 76.4%) and on dry road surfaces (1,835 incidents, 72.3%). Additionally, 1,571 crashes (61.9%) happened during daylight hours. Adverse conditions included 231 crashes in snow and 82 in rain, with 227 incidents on snow or slush-covered roads and 190 on wet surfaces.

Weather

CLEAR1,939 (83.2%)
SNOW231 (9.9%)
RAIN82 (3.5%)
CLOUDY/OVERCAST47 (2.0%)
OTHER13 (0.6%)
SEVERE CROSS WIND GATE13 (0.6%)
SLEET/HAIL3 (0.1%)
FOG/SMOKE/HAZE2 (0.1%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Weather condition at time of crash

Lighting

DAYLIGHT1,571 (66.5%)
DARKNESS, LIGHTED ROAD564 (23.9%)
DARKNESS120 (5.1%)
DUSK71 (3.0%)
DAWN35 (1.5%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Lighting condition field

Road Surface

DRY1,835 (80.6%)
SNOW OR SLUSH227 (10.0%)
WET190 (8.3%)
ICE19 (0.8%)
OTHER6 (0.3%)
SAND, MUD, DIRT1 (0.0%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Road surface condition field

Vehicles & Demographics

Among the persons involved in crashes, the 26-34 age group was most represented with 827 individuals, followed by the 35-44 age group with 689 individuals. The most frequently involved vehicle makes were Toyota (607 vehicles), Chevrolet (604 vehicles), and Ford (473 vehicles).

Top Vehicle Makes (5,078 vehicles)

1
TOYOTA MOTOR COMPANY, LTD.607 (12%)
2
CHEVROLET604 (11.9%)
3
FORD473 (9.3%)
4
NISSAN399 (7.9%)
5
HONDA340 (6.7%)
6
DODGE252 (5%)
7
JEEP178 (3.5%)
8
HYUNDAI156 (3.1%)
9
KIA MOTORS CORP111 (2.2%)
10
CHRYSLER111 (2.2%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Vehicle unit records

1,832 persons with unknown or unrecorded age excluded from age chart. Age=0 in Chicago records is a sentinel for unknown/unrecorded age (not infants) and is grouped with nulls.

Sex Distribution (5,328 persons with recorded sex)

Male2,798 (52.5%)
Female2,039 (38.3%)
Non-Binary491 (9.2%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Person-level records linked to crash events

Speed Limit Zones

The 30 mph speed limit zone accounted for the highest number of crashes, with 1,825 incidents, representing 71.9% of all crashes. No fatalities were reported in crashes occurring within the 30 mph speed limit zone. All other speed limit zones also reported zero fatal crashes for this period.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Posted speed limit at crash location

Crashes by District

District 08 recorded the highest number of crashes, with 291 incidents, which constitutes 11.5% of the total crashes. District 01 followed with 224 crashes, and District 03 with 219 crashes, indicating concentrations of incidents in these areas.

Crashes by District

"Other" combines 15 smaller categories (1,169 records): District 15 (113), District 06 (109), District 24 (104), District 17 (92), District 16 (85), District 09 (83), District 14 (83), District 22 (79), District 02 (78), District 25 (77), District 04 (68), District 19 (67), District 05 (52), District 20 (51), District 07 (28).

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Person-level records

First Crash Type

The most common first crash type was 'REAR END', accounting for 720 incidents or 28.4% of all crashes. 'PARKED MOTOR VEHICLE' was the second most frequent type with 565 incidents (22.2%), followed by 'SIDESWIPE SAME DIRECTION' with 468 incidents (18.4%).

First Crash Type

1
REAR END720 (28.4%)
2
PARKED MOTOR VEHICLE565 (22.3%)
3
SIDESWIPE SAME DIRECTION468 (18.4%)
4
TURNING306 (12.1%)
5
ANGLE297 (11.7%)
6
FIXED OBJECT71 (2.8%)
7
SIDESWIPE OPPOSITE DIRECTION38 (1.5%)
8
PEDESTRIAN22 (0.9%)
9
OTHER OBJECT21 (0.8%)

Showing top 9 of 13 reported. 4 additional (31 total) not shown: HEAD ON, OTHER NONCOLLISION, PEDALCYCLIST, ANIMAL.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Person-level records

Point of Impact

The 'FRONT' was the most frequent point of impact on vehicles, accounting for 1,033 incidents, or 20.3% of all vehicles involved. The 'REAR' was the second most common impact area with 859 incidents (16.9%), followed by 'FRONT-RIGHT' with 631 incidents (12.4%).

Point of Impact

"Other" combines 5 smaller categories (343 records): REAR-RIGHT (279), TOTAL (ALL AREAS) (31), OTHER (17), ROOF (9), UNDER CARRIAGE (7).

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Person-level records

Pre-Crash Driver Action

The most common pre-crash action by drivers was 'STRAIGHT AHEAD', observed in 2,171 instances, representing 42.7% of all vehicle actions. 'PARKED' vehicles were involved in 578 incidents (11.4%), and 'SLOW/STOP IN TRAFFIC' was reported for 538 vehicles (10.6%).

Pre-Crash Driver Action

1
STRAIGHT AHEAD2,171 (43.1%)
2
PARKED578 (11.5%)
3
SLOW/STOP IN TRAFFIC538 (10.7%)
4
UNKNOWN/NA456 (9.1%)
5
BACKING248 (4.9%)
6
TURNING LEFT232 (4.6%)
7
TURNING RIGHT148 (2.9%)
8
CHANGING LANES137 (2.7%)
9
PASSING/OVERTAKING116 (2.3%)

Showing top 9 of 26 reported. 17 additional (414 total) not shown: OTHER, ENTERING TRAFFIC LANE FROM PARKING, MERGING, STARTING IN TRAFFIC, SLOW/STOP - LEFT TURN, U-TURN, LEAVING TRAFFIC LANE TO PARK, AVOIDING VEHICLES/OBJECTS, ENTER FROM DRIVE/ALLEY, SKIDDING/CONTROL LOSS, SLOW/STOP - RIGHT TURN, NEGOTIATING A CURVE, PARKED IN TRAFFIC LANE, SLOW/STOP - LOAD/UNLOAD, DRIVERLESS, DRIVING WRONG WAY, TURNING ON RED.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Person-level records

Pedestrian/Cyclist Action

Among reported pedestrian actions, 'CROSSING - WITH SIGNAL' was the most frequent, occurring in 11 incidents. 'OTHER ACTION' was noted in 5 incidents, and 'WITH TRAFFIC' in 4 incidents. These actions represent the primary activities of pedestrians involved in crashes.

Pedestrian/Cyclist Action

1
CROSSING - WITH SIGNAL11 (33.3%)
2
OTHER ACTION5 (15.2%)
3
UNKNOWN/NA5 (15.2%)
4
WITH TRAFFIC4 (12.1%)
5
AGAINST TRAFFIC3 (9.1%)
6
CROSSING - AGAINST SIGNAL2 (6.1%)
7
NOT AT INTERSECTION1 (3%)
8
PLAYING IN ROADWAY1 (3%)
9
TURNING LEFT1 (3%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-02-01 to 2016-02-29 · Person-level records

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Chicago Traffic Crashes, accessed programmatically via the Socrata Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: Socrata Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2016-02-01 through 2016-02-29
  • Report generated: June 1, 2026

Data Coverage

  • Reporting period: 2016-02-01 through 2016-02-29 (29 days)
  • Geographic scope: Chicago, IL
  • Total crash records analyzed: 2,539
  • Total persons involved: 5,447
  • Total vehicles involved: 5,078

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "Chicago, IL Crash Intelligence Report." Published June 1, 2026. Data source: Chicago Traffic Crashes, Socrata Open Data. Available at: https://thatcarhitme.com/crash-data/illinois/chicago/february-2016-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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Chicago, IL Crash Report — February 2016 | ThatCarHitMe.com