ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHICAGO, IL · SEPTEMBER 2019
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/illinois/chicago/september-2019-report
Monthly Traffic Safety Analysis
9,815 CRASHES IN
CHICAGO, IL
SEPTEMBER 2019
In September 2019, Chicago experienced 9,815 traffic crashes, a slight decrease of 1.17% compared to the 9,931 crashes recorded in September 2018. Despite the overall reduction in crashes, total fatalities saw a substantial increase, rising from 9 in September 2018 to 12 in September 2019, marking a 33.33% increase. Total injuries also increased slightly by 1.43%, from 1,959 to 1,987.
9,815
▼ -1.2%was 9,931
Total Crash Events
12
▲ 33.3%was 9
Persons Killed
1,987
▲ 1.4%was 1,959
Persons Injured
2,686
▲ 0.6%was 2,669
Hit-and-Run Crashes
Note: "Persons Killed" (12) counts individual fatalities across all crash events. "Fatal" in the severity table below (12) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 16 crashes with unreported severity are not shown in the severity breakdown.
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-09-01 to 2019-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash volume in Chicago showed a minor decline year-over-year, with total crashes decreasing by 116 incidents, or 1.17%, from 9,931 in September 2018 to 9,815 in September 2019. This indicates a relatively stable but slightly decreasing trend in the total number of traffic incidents.
2,686
Hit-and-Run Crashes — September 2019
▲ 0.6% vs prior (2,669)
The number of hit-and-run crashes increased slightly from 2,669 in September 2018 to 2,686 in September 2019, an increase of 17 incidents. The hit-and-run rate also saw a marginal increase, rising from 26.9% of total crashes in September 2018 to 27.4% in September 2019, indicating a slight upward trend.
Vulnerable Road User Casualties
5
Pedestrians Killed
1
Cyclists Killed
6
Motorists Killed
0
Other Killed
242
Pedestrians Injured
190
Cyclists Injured
1,552
Motorists Injured
3
Other Injured
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-09-01 to 2019-09-30 · 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 Saturday in September 2018 to Monday in September 2019. In September 2018, Saturday recorded the highest crash count at 1,567, while in September 2019, Monday had the most crashes with 1,550. The peak crash hour remained 4 p.m. in both periods, although the count decreased from 785 in September 2018 to 723 in September 2019.
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-09-01 to 2019-09-30 · Crash date field aggregated by weekday
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-09-01 to 2019-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of fatal crashes increased from 7 in September 2018 to 12 in September 2019, raising the fatal crash rate from 0.07% to 0.12%. While serious injury crashes decreased from 190 to 182, minor injury crashes rose from 840 to 868, and possible injury crashes increased from 409 to 438. The proportion of crashes resulting in no injury slightly decreased from 85.3% to 84.6%.
Outcome by Severity (Crash Events)
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-09-01 to 2019-09-30 · KABCO injury classification scale
Severity Distribution
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-09-01 to 2019-09-30 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors saw shifts in both counts and rankings. 'Failing to Yield Right-of-Way' decreased by 152 incidents (12.39%), from 1,227 in September 2018 to 1,075 in September 2019, while 'Following Too Closely' decreased by 78 incidents (7.23%), from 1,079 to 1,001. Conversely, 'Failing to Reduce Speed to Avoid Crash' increased significantly by 109 incidents (28.46%), rising from 383 to 492, moving from the sixth to the third most frequent factor. 'Improper Overtaking/Passing' decreased by 48 incidents, from 496 to 448, shifting its rank from third to fourth.
Officer-Reported Primary Contributing Cause
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-09-01 to 2019-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions decreased from 8,402 in September 2018 to 7,709 in September 2019, while crashes during rain increased from 853 to 1,304. Correspondingly, crashes on dry road surfaces decreased from 8,250 to 7,546, and crashes on wet surfaces increased from 1,100 to 1,613. Crashes in daylight decreased from 6,963 to 6,673, whereas crashes in darkness on lighted roads increased from 1,777 to 1,969.
Weather
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-09-01 to 2019-09-30 · Weather condition at time of crash
Lighting
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-09-01 to 2019-09-30 · Lighting condition field
Road Surface
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-09-01 to 2019-09-30 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes remained consistent, with Chevrolet, Toyota, and Ford retaining the top three positions in both periods. Chevrolet saw an increase from 2,196 to 2,329 vehicles, while Ford decreased from 2,011 to 1,909. Regarding age distribution, crashes involving persons aged 26-34 increased from 3,493 to 3,645, whereas those involving persons aged 35-44 decreased from 3,077 to 2,929.
Top Vehicle Makes (20,130 vehicles)
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-09-01 to 2019-09-30 · Vehicle unit records
6,186 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 (21,870 persons with recorded sex)
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-09-01 to 2019-09-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 15 mph speed limit zone increased from 324 to 418, and fatalities in this zone rose from 0 to 2. Similarly, the 20 mph zone saw an increase in crashes from 357 to 403, with fatalities rising from 0 to 1. The 30 mph zone, which accounts for the majority of crashes, experienced a slight decrease from 7,271 to 7,167 crashes, but fatal crashes within this zone increased from 4 to 6.
Fatal crashes by zone: 15 mph: 2 of 418 (0.478%) · 20 mph: 1 of 403 (0.248%) · 25 mph: 1 of 609 (0.164%) · 30 mph: 6 of 7,167 (0.084%) · 35 mph: 1 of 740 (0.135%) · 45 mph: 1 of 55 (1.818%)
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-09-01 to 2019-09-30 · 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: 2019-09-01 through 2019-09-30
- Report generated: June 1, 2026
Data Coverage
- Reporting period: 2019-09-01 through 2019-09-30 (30 days)
- Geographic scope: Chicago, IL
- Total crash records analyzed: 9,815
- Total persons involved: 22,233
- Total vehicles involved: 20,130
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-2019-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Chicago Traffic Crashes · Socrata
Period: 2019-09-01 – 2019-09-30
Generated: June 1, 2026 · All rights reserved