Monthly Traffic Safety Analysis

2,765 CRASHES IN
CHICAGO, IL
JANUARY 2016

In January 2016, Chicago experienced a total of 2765 traffic crashes, resulting in 1 fatality and 202 injuries. A notable finding is that 94.1% of these crashes were classified as having no injury. This data provides a snapshot of crash characteristics during this period.

2,765

Total Crash Events

1

Persons Killed

202

Persons Injured

25.8%

Hit-and-Run Rate

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 3 crashes with unreported severity are not shown in the severity breakdown.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Aggregate counts from crash, person, and vehicle records

714

Hit-and-Run Crashes — January 2016

Of the total crashes, 714 were identified as hit-and-run incidents, accounting for 25.8% of all crashes. It is important to note that hit-and-run status is based on the responding officer's initial determination at the scene.

Vulnerable Road User Casualties

During January 2016, there was 1 motorist killed and 179 motorists injured. Additionally, 22 pedestrians were injured, and 1 cyclist sustained injuries. No pedestrians or cyclists were killed in crashes during this period.

0

Pedestrians Killed

0

Cyclists Killed

1

Motorists Killed

22

Pedestrians Injured

1

Cyclists Injured

179

Motorists Injured

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crashes in January 2016 peaked on Fridays, with 491 incidents recorded, and the most frequent hour for crashes was 5 PM, with 243 incidents. The majority of crashes occurred during daylight hours, with 1508 incidents, compared to 159 in complete darkness and 768 in darkness with lighted roads.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Crash date field aggregated by weekday

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Out of 2765 crashes, 1 was fatal, while 158 crashes resulted in injuries (9 serious, 52 minor, and 97 possible injuries). The vast majority, 2603 crashes, or 94.1%, were reported with no injuries. The single fatal crash aligns with the 1 total fatality reported for the month.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0%
Serious Injury9serious injury crashes0.3%
Minor Injury52minor injury crashes1.9%
Possible Injury97possible injury crashes3.5%
No Injury2,603no injury crashes94.1%

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · KABCO injury classification scale

Severity Distribution

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors to crashes were 'FOLLOWING TOO CLOSELY' with 374 incidents (13.5%), followed by 'FAILING TO YIELD RIGHT-OF-WAY' at 242 incidents (8.8%). 'IMPROPER OVERTAKING/PASSING' was the third most common factor, contributing to 132 crashes (4.8%). It is common in crash reporting for some factors to be undetermined, though specific 'Unknown' values are not dominant here.

Officer-Reported Primary Contributing Cause

FOLLOWING TOO CLOSELY374 (13.5%)
FAILING TO YIELD RIGHT-OF-WAY242 (8.8%)
IMPROPER OVERTAKING/PASSING132 (4.8%)
IMPROPER BACKING120 (4.3%)
IMPROPER LANE USAGE106 (3.8%)
DRIVING SKILLS/KNOWLEDGE/EXPERIENCE99 (3.6%)
IMPROPER TURNING/NO SIGNAL91 (3.3%)
FAILING TO REDUCE SPEED TO AVOID CRASH79 (2.9%)
WEATHER64 (2.3%)
DISREGARDING STOP SIGN31 (1.1%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Most crashes occurred under clear weather conditions (2001 crashes, 72.4%) and on dry road surfaces (1661 crashes, 60.1%). Daylight was the predominant lighting condition, accounting for 1508 crashes (54.5%). However, adverse conditions also played a role, with 205 crashes occurring in snow and 170 in rain, and 423 crashes on wet roads.

Weather

CLEAR2,001 (80.8%)
SNOW205 (8.3%)
RAIN170 (6.9%)
CLOUDY/OVERCAST81 (3.3%)
OTHER13 (0.5%)
FOG/SMOKE/HAZE4 (0.2%)
SLEET/HAIL4 (0.2%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Weather condition at time of crash

Lighting

DAYLIGHT1,508 (59.2%)
DARKNESS, LIGHTED ROAD768 (30.2%)
DARKNESS159 (6.2%)
DUSK73 (2.9%)
DAWN38 (1.5%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Lighting condition field

Road Surface

DRY1,661 (70.0%)
WET423 (17.8%)
SNOW OR SLUSH214 (9.0%)
ICE66 (2.8%)
OTHER10 (0.4%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Road surface condition field

Vehicles & Demographics

The age groups most frequently involved in crashes were 26-34 (966 persons), 35-44 (782 persons), and 45-54 (697 persons). Among vehicle makes, Toyota vehicles were most frequently involved with 661 instances, closely followed by Chevrolet with 648 instances, and Ford with 533 instances.

Top Vehicle Makes (5,559 vehicles)

1
TOYOTA MOTOR COMPANY, LTD.661 (11.9%)
2
CHEVROLET648 (11.7%)
3
FORD533 (9.6%)
4
NISSAN426 (7.7%)
5
HONDA378 (6.8%)
6
DODGE277 (5%)
7
HYUNDAI202 (3.6%)
8
JEEP166 (3%)
9
CHRYSLER136 (2.4%)
10
BUICK118 (2.1%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Vehicle unit records

1,977 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 (5,921 persons with recorded sex)

Male3,126 (52.8%)
Female2,264 (38.2%)
Non-Binary531 (9.0%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Person-level records linked to crash events

Speed Limit Zones

The 30 mph speed limit zone recorded the highest number of crashes, with 2011 incidents. In this zone, 0.05% of crashes were fatal. No fatalities were recorded in any other speed limit zones during this period.

Fatal crashes by zone: 30 mph: 1 of 2,011 (0.05%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Posted speed limit at crash location

Crashes by District

The highest concentration of crashes was observed in District 01, which accounted for 272 crashes, representing 9.8% of the total. District 18 followed closely with 269 crashes, and District 08 recorded 253 crashes. These districts show significant crash activity within the city.

Crashes by District

"Other" combines 15 smaller categories (1,251 records): District 16 (123), District 11 (111), District 14 (107), District 15 (97), District 25 (92), District 09 (88), District 04 (87), District 06 (80), District 19 (80), District 02 (78), District 20 (76), District 22 (74), District 17 (70), District 05 (54), District 07 (34).

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Person-level records

First Crash Type

The most common first crash type was 'REAR END' collisions, accounting for 863 crashes or 31.2% of the total. Crashes involving a 'PARKED MOTOR VEHICLE' were the second most frequent, with 587 incidents (21.2%). 'SIDESWIPE SAME DIRECTION' crashes followed with 488 incidents (17.6%).

First Crash Type

1
REAR END863 (31.2%)
2
PARKED MOTOR VEHICLE587 (21.2%)
3
SIDESWIPE SAME DIRECTION488 (17.6%)
4
TURNING333 (12%)
5
ANGLE284 (10.3%)
6
FIXED OBJECT74 (2.7%)
7
SIDESWIPE OPPOSITE DIRECTION52 (1.9%)
8
HEAD ON26 (0.9%)
9
PEDESTRIAN21 (0.8%)

Showing top 9 of 13 reported. 4 additional (37 total) not shown: OTHER OBJECT, PEDALCYCLIST, OTHER NONCOLLISION, ANIMAL.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Person-level records

Point of Impact

Among all recorded vehicle impact points, the 'FRONT' of vehicles was the most common area struck, representing 25.0% of impacts. The 'REAR' was the second most frequent impact area, accounting for 20.3% of impacts. This indicates a prevalence of frontal and rear-end impacts in reported incidents.

Point of Impact

"Other" combines 5 smaller categories (363 records): REAR-RIGHT (301), OTHER (31), UNDER CARRIAGE (16), TOTAL (ALL AREAS) (10), ROOF (5).

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Person-level records

Pre-Crash Driver Action

Prior to crashes, the most frequent action reported for vehicles was 'STRAIGHT AHEAD', accounting for 43.2% of actions. 'PARKED' vehicles were involved in 10.9% of incidents, while 'SLOW/STOP IN TRAFFIC' was reported for 10.5% of vehicles. These top three actions indicate common scenarios leading to crashes.

Pre-Crash Driver Action

1
STRAIGHT AHEAD2,404 (43.6%)
2
PARKED604 (11%)
3
SLOW/STOP IN TRAFFIC583 (10.6%)
4
UNKNOWN/NA522 (9.5%)
5
TURNING LEFT255 (4.6%)
6
BACKING254 (4.6%)
7
PASSING/OVERTAKING148 (2.7%)
8
TURNING RIGHT146 (2.6%)
9
CHANGING LANES110 (2%)

Showing top 9 of 27 reported. 18 additional (484 total) not shown: OTHER, ENTERING TRAFFIC LANE FROM PARKING, STARTING IN TRAFFIC, SLOW/STOP - LEFT TURN, U-TURN, LEAVING TRAFFIC LANE TO PARK, MERGING, SLOW/STOP - RIGHT TURN, SKIDDING/CONTROL LOSS, SLOW/STOP - LOAD/UNLOAD, ENTER FROM DRIVE/ALLEY, PARKED IN TRAFFIC LANE, AVOIDING VEHICLES/OBJECTS, NEGOTIATING A CURVE, DRIVING WRONG WAY, TURNING ON RED, DRIVERLESS, DIVERGING.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · Person-level records

Pedestrian/Cyclist Action

For pedestrians involved in crashes, 'CROSSING - WITH SIGNAL' was the most frequent action, accounting for 11 incidents or 31.4% of recorded pedestrian actions. 'OTHER ACTION' was reported in 9 instances (25.7%), and 'WITH TRAFFIC' in 6 instances (17.1%).

Pedestrian/Cyclist Action

1
CROSSING - WITH SIGNAL11 (28.2%)
2
OTHER ACTION9 (23.1%)
3
WITH TRAFFIC6 (15.4%)
4
AGAINST TRAFFIC5 (12.8%)
5
UNKNOWN/NA4 (10.3%)
6
CROSSING - AGAINST SIGNAL3 (7.7%)
7
PARKED VEHICLE1 (2.6%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-01-01 to 2016-01-31 · 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: 2016-01-01 through 2016-01-31
  • Report generated: June 1, 2026

Data Coverage

  • Reporting period: 2016-01-01 through 2016-01-31 (31 days)
  • Geographic scope: Chicago, IL
  • Total crash records analyzed: 2,765
  • Total persons involved: 6,025
  • Total vehicles involved: 5,559

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/january-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 — January 2016 | ThatCarHitMe.com