ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHICAGO, IL · 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/2019-annual-report
Yearly Traffic Safety Analysis
117,764 CRASHES IN
CHICAGO, IL
2019
In 2019, Chicago recorded 117,764 total traffic crashes, a 1.0% decrease from the 118,952 crashes recorded in 2018. While total crashes and fatalities declined, the most notable year-over-year shift was a 29% increase in pedestrian fatalities, which rose from 31 in 2018 to 40 in 2019.
117,764
▼ -1.0%was 118,952
Total Crash Events
115
▼ -11.5%was 130
Persons Killed
22,581
▲ 0.6%was 22,442
Persons Injured
31,955
▲ 1.2%was 31,590
Hit-and-Run Crashes
Note: "Persons Killed" (115) counts individual fatalities across all crash events. "Fatal" in the severity table below (102) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 265 crashes with unreported severity are not shown in the severity breakdown.
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-01-01 to 2019-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends in Chicago showed a slight improvement from 2018 to 2019. The total number of crashes decreased by 1.0% (from 118,952 to 117,764), and total fatalities fell by 11.5% (from 130 to 115). However, the total number of injuries saw a marginal increase of 0.6%, rising from 22,442 to 22,581.
31,955
Hit-and-Run Crashes — 2019
▲ 1.2% vs prior (31,590)
Hit-and-run crashes trended upward from 2018 to 2019. The total number of hit-and-run incidents increased from 31,590 to 31,955. Consequently, the hit-and-run rate as a percentage of all crashes also rose, from 26.6% in 2018 to 27.1% in 2019.
Vulnerable Road User Casualties
40
Pedestrians Killed
4
Cyclists Killed
71
Motorists Killed
0
Other Killed
3,023
Pedestrians Injured
1,349
Cyclists Injured
18,198
Motorists Injured
11
Other Injured
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-01-01 to 2019-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes in Chicago remained highly consistent between 2018 and 2019. Friday was the day with the most crashes in both years, with 19,031 incidents in 2018 and 18,698 in 2019. Similarly, the 4 PM hour was the peak time for crashes in both periods, recording 8,933 crashes in 2018 and 8,956 in 2019, indicating no significant shift in daily or weekly crash rhythms.
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-01-01 to 2019-12-31 · Crash date field aggregated by weekday
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-01-01 to 2019-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes showed a slight decrease from 2018 to 2019. The rate of fatal crashes declined from 0.10 per 100 crashes in 2018 to 0.09 in 2019, with the absolute count of fatal crashes falling from 114 to 102. The proportion of crashes resulting in serious injury also decreased slightly from 1.8% to 1.7% of all crashes, while the share of no-injury crashes remained stable at 85.9% for both years.
Severity is per crash event (most severe injury). 102 fatal crash events resulted in 115 persons killed.
Outcome by Severity (Crash Events)
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-01-01 to 2019-12-31 · KABCO injury classification scale
Severity Distribution
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-01-01 to 2019-12-31 · Most severe injury per crash record
Top Contributing Factors
The primary contributing factors for crashes were consistent year-over-year, with 'Failing to Yield Right-of-Way' and 'Following Too Closely' as the top two causes in both 2018 and 2019. The count of crashes attributed to 'Failing to Yield Right-of-Way' decreased by 8.1% from 14,089 to 12,951. In contrast, crashes due to 'Failing to Reduce Speed to Avoid Crash' saw a 9.7% increase in count, rising from 5,075 incidents in 2018 to 5,566 in 2019.
Officer-Reported Primary Contributing Cause
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-01-01 to 2019-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The environmental conditions under which crashes occurred were similar in 2019 compared to 2018. In both years, the majority of incidents happened in daylight (65.6% in 2019 vs. 65.7% in 2018) and on dry road surfaces (73.1% in 2019 vs. 74.5% in 2018). There was a minor increase in the proportion of crashes on roads with snow or slush, which accounted for 3.6% of crashes in 2018 and 4.2% in 2019.
Weather
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-01-01 to 2019-12-31 · Weather condition at time of crash
Lighting
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-01-01 to 2019-12-31 · Lighting condition field
Road Surface
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-01-01 to 2019-12-31 · Road surface condition field
Vehicles & Demographics
Vehicle and person demographics involved in crashes showed little change between 2018 and 2019. The top three vehicle makes involved in collisions were identical in both years: Chevrolet, Toyota, and Ford. The age distribution of persons involved also remained stable, with the 26-34 age group constituting the largest segment in both periods, accounting for 22.6% of involved persons in 2018 and 22.9% in 2019.
Top Vehicle Makes (240,197 vehicles)
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-01-01 to 2019-12-31 · Vehicle unit records
73,829 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 (259,615 persons with recorded sex)
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-01-01 to 2019-12-31 · Person-level records linked to crash events
Speed Limit Zones
The 30 mph speed zone continued to be the location for the vast majority of crashes, accounting for 86,593 crashes in 2019, down from 88,081 in 2018. Notably, the number of fatal crashes in this zone decreased from 87 to 68. While overall crash counts in lower speed zones fell, there were slight increases in both total and fatal crashes in higher speed zones, such as the 45 mph zone, which saw fatal crashes increase from 0 in 2018 to 4 in 2019.
Fatal crashes by zone: 5 mph: 2 of 750 (0.267%) · 10 mph: 1 of 2,718 (0.037%) · 15 mph: 6 of 4,406 (0.136%) · 20 mph: 3 of 4,813 (0.062%) · 25 mph: 5 of 7,257 (0.069%) · 30 mph: 68 of 86,593 (0.079%) · 35 mph: 9 of 8,227 (0.109%) · 40 mph: 4 of 1,131 (0.354%) · 45 mph: 4 of 738 (0.542%)
Source: Chicago Traffic Crashes · Socrata Open Data · 2019-01-01 to 2019-12-31 · 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: 2019-01-01 through 2019-12-31
- Report generated: June 1, 2026
Data Coverage
- Reporting period: 2019-01-01 through 2019-12-31 (365 days)
- Geographic scope: Chicago, IL
- Total crash records analyzed: 117,764
- Total persons involved: 264,003
- Total vehicles involved: 240,197
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/2019-annual-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: 2019-01-01 – 2019-12-31
Generated: June 1, 2026 · All rights reserved