Chicago, IL Crash Intelligence Report — February 2026 | ThatCarHitMe.com

Monthly Traffic Safety Analysis

7,808
CRASHES IN
FEBRUARY 2026

In February 2026, Chicago recorded 7,808 crashes, resulting in 8 fatalities and 1,599 injuries. A notable finding is that nearly 30% of all reported crashes involved a hit-and-run incident. This monthly report provides an overview of crash characteristics and contributing factors within the city.

7,808

Total Crash Events

Persons Killed

1,599

Persons Injured

29.8%

Hit-and-Run Rate

  Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (7) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 8 crashes with unreported severity are not shown in the severity breakdown.

Source: Chicago Traffic Crashes · Socrata Open Data · 2026-02-01 to 2026-02-28 · Aggregate counts from crash, person, and vehicle records

2,324

Hit-and-Run Crashes This Period

During February 2026, Chicago experienced 2,324 hit-and-run crashes, representing 29.8% of all reported incidents. It is important to note that hit-and-run status is based on the initial determination by the responding officer. This high rate indicates a significant challenge in identifying all parties involved in crash events.

When Crashes Happen

Crash incidents in February 2026 peaked on Wednesdays, with 1,277 crashes, and the busiest hour for crashes was 3 PM, recording 635 incidents. The majority of crashes, 4,546, occurred during daylight hours, while 2,406 crashes took place in darkness (lighted or unlighted conditions). This suggests a higher frequency of crashes during weekday afternoons and standard commuting times.

Crashes by Day of Week

Crashes by Day of Week
Day	Crashes
Sun	1,027
Mon	1,009
Tue	1,078
Wed	1,277
Thu	1,074
Fri	1,234
Sat	1,109

Source: Chicago Traffic Crashes · Socrata Open Data · 2026-02-01 to 2026-02-28 · Crash date field aggregated by weekday

Crashes by Hour of Day

Crashes by Hour of Day
Hour	Crashes
12a	166
1a	117
2a	109
3a	90
4a	79
5a	157
6a	197
7a	413
8a	522
9a	386
10a	348
11a	378
12p	436
1p	455
2p	517
3p	635
4p	540
5p	482
6p	476
7p	344
8p	287
9p	256
10p	235
11p	183

Source: Chicago Traffic Crashes · Socrata Open Data · 2026-02-01 to 2026-02-28 · Crash time field aggregated by hour (0–23)

Crash Severity Breakdown

A significant 85% of crashes in February 2026 resulted in no reported injuries, indicating property damage only. Injury-involved crashes (serious, minor, or possible) accounted for 14.7% of all incidents. There were 7 fatal crash events recorded, leading to a total of 8 fatalities, highlighting that a single crash can unfortunately result in multiple deaths.

Severity is per crash event (most severe injury). 7 fatal crash events resulted in 8 persons killed. 8 crashes with unreported severity not shown.

Outcome by Severity (Crash Events)

Fatal7fatal crashes0.1%

Serious Injury66serious injury crashes0.8%

Minor Injury581minor injury crashes7.4%

Possible Injury507possible injury crashes6.5%

No Injury6,639no injury crashes85%

Source: Chicago Traffic Crashes · Socrata Open Data · 2026-02-01 to 2026-02-28 · KABCO injury classification scale

Severity Distribution

Crash Severity Distribution
Severity	Count	Percent
Fatal	7	0.1%
Serious Injury	66	0.8%
Minor Injury	581	7.4%
Possible Injury	507	6.5%
No Injury	6,639	85%

Source: Chicago Traffic Crashes · Socrata Open Data · 2026-02-01 to 2026-02-28 · Most severe injury per crash record

Top Contributing Factors

The most frequently cited contributing factor in February 2026 crashes was 'UNABLE TO DETERMINE,' accounting for 42.5% of incidents, a common finding in crash reporting. Other significant factors included 'FAILING TO YIELD RIGHT-OF-WAY' at 12.1% and 'FOLLOWING TOO CLOSELY' at 8.5%. These statistics highlight recurring behavioral patterns contributing to crashes.

Officer-Reported Primary Contributing Cause

UNABLE TO DETERMINE

42.5%

FAILING TO YIELD RIGHT-OF-WAY

12.1%

FOLLOWING TOO CLOSELY

8.5%

IMPROPER OVERTAKING/PASSING

5.6%

NOT APPLICABLE

4.6%

FAILING TO REDUCE SPEED TO AVOID CRASH

4.3%

DRIVING SKILLS/KNOWLEDGE/EXPERIENCE

4.2%

IMPROPER LANE USAGE

3.4%

IMPROPER TURNING/NO SIGNAL

3.3%

IMPROPER BACKING

2.8%

Source: Chicago Traffic Crashes · Socrata Open Data · 2026-02-01 to 2026-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in February 2026 occurred under favorable conditions, with 79.9% happening in clear weather, 71.3% on dry roads, and 58.2% during daylight. However, adverse conditions also contributed, with 368 crashes in snow and 555 on wet road surfaces. These figures indicate that while clear conditions are prevalent, environmental factors still play a role.

Weather

CLEAR6,238

UNKNOWN724

SNOW368

CLOUDY/OVERCAST314

RAIN90

OTHER25

SLEET/HAIL17

FREEZING RAIN/DRIZZLE17

BLOWING SNOW8

FOG/SMOKE/HAZE6

SEVERE CROSS WIND GATE1

Source: Chicago Traffic Crashes · Socrata Open Data · 2026-02-01 to 2026-02-28 · Weather condition at time of crash

Road Surface

DRY5,566

UNKNOWN1,228

WET555

SNOW OR SLUSH389

ICE44

OTHER25

SAND, MUD, DIRT1

Source: Chicago Traffic Crashes · Socrata Open Data · 2026-02-01 to 2026-02-28 · Road surface condition field

Lighting

DAYLIGHT4,546

DARKNESS, LIGHTED ROAD2,034

UNKNOWN540

DARKNESS372

DUSK186

DAWN130

Source: Chicago Traffic Crashes · Socrata Open Data · 2026-02-01 to 2026-02-28 · Lighting condition field

Vehicles & Demographics

The age group 26-34 was most frequently represented in crash data, accounting for 2,831 individuals, followed by those aged 35-44 with 2,363 individuals. Regarding vehicle makes, Toyota was the most common make involved in crashes, with 1,964 instances, closely followed by Ford at 1,595 and Chevrolet at 1,563. These figures reflect the vehicle types and demographics present in crash events.

Top Vehicle Makes in Crashes

TOYOTA

1,964

UNKNOWN

1,689

FORD

1,595

CHEVROLET

1,563

HONDA

1,294

NISSAN

1,160

JEEP

693

HYUNDAI

615

DODGE

501

Source: Chicago Traffic Crashes · Socrata Open Data · Vehicle unit records

Person Age Distribution

Crashes by Person Age Group
Age Group	Persons
0-15	526
16-20	771
21-25	1,480
26-34	2,831
35-44	2,363
45-54	1,768
55-64	1,311
65+	1,055

4,976 persons with unknown or unrecorded age excluded from age chart. Sex distribution below reflects all 17,081 persons.

Sex Distribution (17,081 Persons)

Male8,928

Female6,295

Non-Binary1,544

Unknown314

Source: Chicago Traffic Crashes · Socrata Open Data · 2026-02-01 to 2026-02-28 · Person-level records linked to crash events

Speed Limit Zones

The 30 mph speed limit zone recorded the highest number of crashes in February 2026, with 5,840 incidents, representing 74.8% of all crashes. Within this zone, 0.12% of crashes were fatal. Other significant crash volumes occurred in 25 mph zones (573 crashes) and 35 mph zones (374 crashes), indicating a concentration of incidents on roads with moderate speed limits.

16 crashes with no posted speed limit recorded (0 or unreported) are excluded from this chart.

Crashes by Posted Speed Limit

Fatal crashes by zone: 30 mph: 7 of 5,840 (0.12%)

Crashes by Posted Speed Limit
Speed Limit	Crashes	Fatal	Fatal %
3	4	0	0%
5	25	0	0%
10	203	0	0%
15	288	0	0%
20	337	0	0%
25	573	0	0%
26	1	0	0%
30	5,840	7	0.12%
32	1	0	0%
35	374	0	0%
39	1	0	0%
40	79	0	0%
45	54	0	0%
50	2	0	0%
55	10	0	0%

Source: Chicago Traffic Crashes · Socrata Open Data · 2026-02-01 to 2026-02-28 · Posted speed limit at crash location

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: 2026-02-01 through 2026-02-28
Report generated: March 18, 2026

Data Coverage

Reporting period: 2026-02-01 through 2026-02-28 (28 days)
Geographic scope: Chicago, IL
Total crash records analyzed: 7,808
Total persons involved: 17,081
Total vehicles involved: 15,813

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. 8 crash events had no reported severity classification and are excluded from the severity chart.
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.
Speed zones: Based on the posted speed limit at the crash location as recorded in the crash report.
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 by the City of Chicago under their 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: reports@injuria.ai or visit thatcarhitme.com/report-error. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "Chicago, IL Crash Intelligence Report: February 2026." Published March 18, 2026. Data source: Chicago Traffic Crashes, Socrata Open Data. Available at: thatcarhitme.com

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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