Monthly Traffic Safety Analysis

9,931 CRASHES IN
CHICAGO, IL
SEPTEMBER 2018

All metrics benchmarked againstSeptember 2017

In September 2018, Chicago experienced 9,931 total crashes, an increase of 9.9% compared to the 9,038 crashes reported in September 2017. Despite the rise in total incidents, total fatalities decreased by 30.8%, from 13 in the prior year to 9 in the current period. Total injuries saw a modest increase of 3.3%, rising from 1,897 to 1,959.

9,931

9.9%was 9,038

Total Crash Events

9

-30.8%was 13

Persons Killed

1,959

3.3%was 1,897

Persons Injured

2,669

15.1%was 2,319

Hit-and-Run Crashes

Note: "Persons Killed" (9) 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. 17 crashes with unreported severity are not shown in the severity breakdown.

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-09-01 to 2018-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Chicago are on an upward trend, with total crashes increasing by 9.9% year-over-year, from 9,038 to 9,931. Concurrently, total injuries also increased by 3.3%, from 1,897 to 1,959. However, a positive trend was observed in fatalities, which decreased by 30.8%, from 13 to 9.

2,669

Hit-and-Run Crashes — September 2018

15.1% vs prior (2,319)

Hit-and-run incidents increased year-over-year, rising from 2,319 crashes in September 2017 to 2,669 crashes in September 2018, an increase of 350 incidents. The hit-and-run rate also saw an upward trend, increasing from 25.7% of total crashes to 26.9%.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 2-50.0%

1

Cyclists Killed

Prior: 0%

7

Motorists Killed

Prior: 11-36.4%

259

Pedestrians Injured

Prior: 2436.6%

176

Cyclists Injured

Prior: 211-16.6%

1,524

Motorists Injured

Prior: 1,4425.7%

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-09-01 to 2018-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Friday in September 2017 (1,670 crashes) to Saturday in September 2018 (1,567 crashes), though both days saw a decrease in their respective peak counts. The peak hour for crashes remained consistently at 4 p.m. in both periods, with crashes at this hour increasing from 711 to 785. Notably, Sunday crashes significantly increased by 384, from 1,011 to 1,395.

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-09-01 to 2018-09-30 · Crash date field aggregated by weekday

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-09-01 to 2018-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The fatal crash rate decreased significantly from 0.13% in September 2017 to 0.07% in September 2018, with the number of fatal crashes dropping from 12 to 7. Serious injury crashes also saw a reduction, decreasing from 220 (2.4% share) to 190 (1.9% share). Conversely, minor injury crashes increased from 755 (8.4% share) to 840 (8.5% share), and no-injury crashes rose from 7,608 (84.2% share) to 8,468 (85.3% share).

Severity is per crash event (most severe injury). 7 fatal crash events resulted in 9 persons killed.

Outcome by Severity (Crash Events)

Fatal7fatal crashes0.1%
-41.7%prior 12
Serious Injury190serious injury crashes1.9%
-13.6%prior 220
Minor Injury840minor injury crashes8.5%
11.3%prior 755
Possible Injury409possible injury crashes4.1%
-5.3%prior 432
No Injury8,468no injury crashes85.3%
11.3%prior 7,608

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-09-01 to 2018-09-30 · KABCO injury classification scale

Severity Distribution

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-09-01 to 2018-09-30 · Most severe injury per crash record

Top Contributing Factors

Failing to Yield Right-of-Way remained the leading contributing factor, increasing from 1,119 crashes in 2017 to 1,227 crashes in 2018, a rise of 108 incidents. Following Too Closely also maintained its second position, with counts increasing from 1,044 to 1,079 crashes, a change of 35 incidents. Improper Overtaking/Passing saw a notable increase of 100 crashes, rising from 396 to 496, which moved it into the third-highest ranking factor, displacing Improper Backing, which decreased by 24 crashes from 443 to 419.

Officer-Reported Primary Contributing Cause

FAILING TO YIELD RIGHT-OF-WAY1,227 (12.4%)9.7%prior 1,119
FOLLOWING TOO CLOSELY1,079 (10.9%)3.4%prior 1,044
IMPROPER OVERTAKING/PASSING496 (5%)25.3%prior 396
IMPROPER LANE USAGE433 (4.4%)12.2%prior 386
IMPROPER BACKING419 (4.2%)-5.4%prior 443
FAILING TO REDUCE SPEED TO AVOID CRASH383 (3.9%)6.1%prior 361
IMPROPER TURNING/NO SIGNAL367 (3.7%)18.4%prior 310
DRIVING SKILLS/KNOWLEDGE/EXPERIENCE338 (3.4%)3.7%prior 326
DISREGARDING TRAFFIC SIGNALS192 (1.9%)31.5%prior 146
OPERATING VEHICLE IN ERRATIC, RECKLESS, CARELESS, NEGLIGENT OR AGGRESSIVE MANNER146 (1.5%)24.8%prior 117

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-09-01 to 2018-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A significant shift was observed in adverse weather conditions, with crashes occurring in rain increasing from 241 in 2017 to 853 in 2018, and cloudy/overcast conditions rising from 112 to 308. Correspondingly, crashes on wet road surfaces dramatically increased from 330 to 1,100 year-over-year. Crashes during daylight hours also increased, from 6,366 to 6,963.

Weather

CLEAR8,402 (87.6%)
-0.3%prior 8,426
RAIN853 (8.9%)
253.9%prior 241
CLOUDY/OVERCAST308 (3.2%)
175.0%prior 112
OTHER16 (0.2%)
60.0%prior 10
SNOW4 (0.0%)
300.0%prior 1
FOG/SMOKE/HAZE3 (0.0%)
-57.1%prior 7
SEVERE CROSS WIND GATE1 (0.0%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-09-01 to 2018-09-30 · Weather condition at time of crash

Lighting

DAYLIGHT6,963 (72.5%)
9.4%prior 6,366
DARKNESS, LIGHTED ROAD1,777 (18.5%)
7.1%prior 1,659
DARKNESS407 (4.2%)
10.6%prior 368
DUSK290 (3.0%)
18.4%prior 245
DAWN168 (1.7%)
18.3%prior 142

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-09-01 to 2018-09-30 · Lighting condition field

Road Surface

DRY8,250 (87.9%)
-0.3%prior 8,271
WET1,100 (11.7%)
233.3%prior 330
OTHER25 (0.3%)
127.3%prior 11
SAND, MUD, DIRT8 (0.1%)
-27.3%prior 11
SNOW OR SLUSH2 (0.0%)
100.0%prior 1
ICE1 (0.0%)
-66.7%prior 3

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-09-01 to 2018-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 18,548 in September 2017 to 20,218 in September 2018. The top three vehicle makes involved in crashes remained consistent, with Chevrolet, Toyota, and Ford holding the top spots, all showing an increase in counts. The age distribution of persons involved in crashes showed increases across all reported age groups, with the 35-44 age group seeing the largest increase of 389 persons, from 2,688 to 3,077.

Top Vehicle Makes (20,218 vehicles)

1
CHEVROLET2,196 (10.9%)
4.2%prior 2,108
2
TOYOTA MOTOR COMPANY, LTD.2,145 (10.6%)
5.5%prior 2,034
3
FORD2,011 (9.9%)
13.8%prior 1,767
4
NISSAN1,626 (8%)
9.3%prior 1,487
5
HONDA1,469 (7.3%)
14.2%prior 1,286
6
DODGE925 (4.6%)
15.3%prior 802
7
JEEP770 (3.8%)
24.4%prior 619
8
HYUNDAI758 (3.7%)
2.8%prior 737
9
KIA MOTORS CORP432 (2.1%)
12.8%prior 383
10
VOLKSWAGEN431 (2.1%)
40.4%prior 307

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-09-01 to 2018-09-30 · Vehicle unit records

6,359 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 (22,040 persons with recorded sex)

Male11,880 (53.9%)
11.7%prior 10,640
Female8,485 (38.5%)
9.6%prior 7,745
Non-Binary1,675 (7.6%)
9.6%prior 1,528

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-09-01 to 2018-09-30 · Person-level records linked to crash events

Speed Limit Zones

The 30 mph speed limit zone continued to account for the highest number of crashes, increasing from 6,666 in 2017 to 7,271 in 2018. Despite this increase in crashes, the fatal crash rate in the 30 mph zone decreased from 0.135% to 0.055%, with fatalities dropping from 9 to 4. The 35 mph zone also saw an increase in crashes, from 642 to 712, while its fatal crash rate slightly decreased from 0.312% to 0.281% with fatalities remaining at 2.

Fatal crashes by zone: 30 mph: 4 of 7,271 (0.055%) · 35 mph: 2 of 712 (0.281%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-09-01 to 2018-09-30 · 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: 2018-09-01 through 2018-09-30
  • Report generated: June 1, 2026

Data Coverage

  • Reporting period: 2018-09-01 through 2018-09-30 (30 days)
  • Geographic scope: Chicago, IL
  • Total crash records analyzed: 9,931
  • Total persons involved: 22,298
  • Total vehicles involved: 20,218

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/september-2018-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 Year-over-Year Crash Report — September 2018 vs September 2017 | ThatCarHitMe.com