ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHICAGO, IL · APRIL 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/april-2019-report
Monthly Traffic Safety Analysis
9,446 CRASHES IN
CHICAGO, IL
APRIL 2019
In April 2019, Chicago recorded 9,446 total crashes, a decrease from the 9,648 crashes reported in April 2018, representing a 2.09% reduction. The most significant year-over-year change was a 45.45% decrease in total fatalities, falling from 11 in April 2018 to 6 in April 2019.
9,446
▼ -2.1%was 9,648
Total Crash Events
6
▼ -45.5%was 11
Persons Killed
1,752
▼ -1.8%was 1,784
Persons Injured
2,610
▲ 2.0%was 2,559
Hit-and-Run Crashes
Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 19 crashes with unreported severity are not shown in the severity breakdown.
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-04-01 to 2019-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Chicago for April 2019 show a slight decrease compared to April 2018, with total crashes falling by 2.09% from 9,648 to 9,446. This period also saw a notable reduction in total fatalities, which decreased by 45.45% from 11 to 6. Total injuries also declined, dropping by 1.79% from 1,784 to 1,752.
2,610
Hit-and-Run Crashes — April 2019
▲ 2.0% vs prior (2,559)
Hit-and-run incidents increased in April 2019 compared to the previous year. The number of hit-and-run crashes rose by 51, from 2,559 in April 2018 to 2,610 in April 2019. Concurrently, the hit-and-run rate, as a percentage of total crashes, increased from 26.5% to 27.6%, indicating an upward trend in these types of incidents.
Vulnerable Road User Casualties
2
Pedestrians Killed
0
Cyclists Killed
4
Motorists Killed
0
Other Killed
223
Pedestrians Injured
80
Cyclists Injured
1,448
Motorists Injured
1
Other Injured
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-04-01 to 2019-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained largely consistent year-over-year, with Monday continuing to be the peak day for crashes in both April 2018 (1,696 crashes) and April 2019 (1,629 crashes). The peak hour for crashes also remained at 4 PM, although the number of crashes at this hour increased from 715 in April 2018 to 782 in April 2019.
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-04-01 to 2019-04-30 · Crash date field aggregated by weekday
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-04-01 to 2019-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The overall severity of crashes showed a decrease in April 2019 compared to the prior year. The fatal crash rate, calculated as fatal crashes per total crashes, decreased from 0.11% in April 2018 to 0.06% in April 2019. The proportion of serious injury crashes also saw a reduction, dropping from 1.8% to 1.5%, while the proportion of minor injury and possible injury crashes remained stable at 7.4% and 4.2% respectively.
Outcome by Severity (Crash Events)
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-04-01 to 2019-04-30 · KABCO injury classification scale
Severity Distribution
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-04-01 to 2019-04-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors to crashes remained consistent year-over-year, with 'Failing to Yield Right-of-Way' and 'Following Too Closely' being the top two in both periods. 'Failing to Yield Right-of-Way' decreased by 47 crashes, from 1,127 in April 2018 to 1,080 in April 2019, while 'Following Too Closely' decreased by 62 crashes, from 1,022 to 960. Notably, crashes attributed to 'Weather' decreased significantly by 85 incidents, from 232 to 147, whereas 'Improper Turning/No Signal' increased by 43 crashes, from 334 to 377.
Officer-Reported Primary Contributing Cause
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-04-01 to 2019-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
There were shifts in crash conditions year-over-year, with crashes occurring in 'Clear' weather decreasing by 297, from 7,349 in April 2018 to 7,052 in April 2019. Conversely, crashes during 'Rain' increased by 91 incidents, from 1,167 to 1,258. Regarding road surface conditions, crashes on 'Dry' roads decreased by 219, while those on 'Snow or Slush' roads increased by 115, from 207 to 322, and crashes on 'Ice' decreased significantly by 170, from 199 to 29.
Weather
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-04-01 to 2019-04-30 · Weather condition at time of crash
Lighting
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-04-01 to 2019-04-30 · Lighting condition field
Road Surface
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-04-01 to 2019-04-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased by 487, from 19,692 in April 2018 to 19,205 in April 2019. While the top five vehicle makes involved in crashes remained consistent, Nissan saw an increase of 58 vehicles involved, from 1,560 to 1,618, contrasting with decreases for Chevrolet (-84), Toyota (-100), Ford (-8), and Honda (-33). In terms of person demographics, all age groups from 0-54 years showed a decrease in involvement, while the 55-64 age group increased by 54 persons and the 65+ age group increased by 79 persons.
Top Vehicle Makes (19,205 vehicles)
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-04-01 to 2019-04-30 · Vehicle unit records
5,977 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 (20,862 persons with recorded sex)
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-04-01 to 2019-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone, which accounts for the majority of incidents, decreased by 246 crashes, from 7,138 in April 2018 to 6,892 in April 2019, and saw a significant reduction in its fatal crash rate from 0.126% to 0.029%. Conversely, crashes in the 15 mph zone increased by 38 incidents, from 306 to 344. The 45 mph speed zone experienced an increase of 22 crashes, from 47 to 69, and recorded 1 fatal crash in April 2019, compared to none in April 2018.
Fatal crashes by zone: 15 mph: 1 of 344 (0.291%) · 25 mph: 1 of 600 (0.167%) · 30 mph: 2 of 6,892 (0.029%) · 40 mph: 1 of 68 (1.471%) · 45 mph: 1 of 69 (1.449%)
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-04-01 to 2019-04-30 · 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: 2019-04-01 through 2019-04-30
- Report generated: June 1, 2026
Data Coverage
- Reporting period: 2019-04-01 through 2019-04-30 (30 days)
- Geographic scope: Chicago, IL
- Total crash records analyzed: 9,446
- Total persons involved: 21,169
- Total vehicles involved: 19,205
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/april-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: 2019-04-01 – 2019-04-30
Generated: June 1, 2026 · All rights reserved