ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHICAGO, IL · 2017
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/2017-annual-report
Yearly Traffic Safety Analysis
83,786 CRASHES IN
CHICAGO, IL
2017
In 2017, Chicago recorded 83,786 total traffic crashes, an 89.1% increase from the 44,297 crashes reported in 2016. This period also saw a significant rise in traffic fatalities, which increased from 14 in 2016 to 88 in 2017. The most notable shift was the substantial year-over-year increase across nearly all crash metrics, including injuries and crash severity.
83,786
▲ 89.1%was 44,297
Total Crash Events
88
▲ 528.6%was 14
Persons Killed
13,031
▲ 260.7%was 3,613
Persons Injured
22,160
▲ 92.6%was 11,505
Hit-and-Run Crashes
Note: "Persons Killed" (88) counts individual fatalities across all crash events. "Fatal" in the severity table below (78) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 151 crashes with unreported severity are not shown in the severity breakdown.
Source: Chicago Traffic Crashes · Socrata Open Data · 2017-01-01 to 2017-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety metrics worsened significantly year-over-year, with total crashes rising by 89.1% from 44,297 in 2016 to 83,786 in 2017. Concurrently, the number of people injured increased by 260.7% to 13,031, and the number of fatalities grew from 14 to 88.
22,160
Hit-and-Run Crashes — 2017
▲ 92.6% vs prior (11,505)
The number of hit-and-run crashes increased by 92.6%, rising from 11,505 in 2016 to 22,160 in 2017. The hit-and-run rate, which is the proportion of all crashes that were hit-and-runs, remained relatively stable with a slight upward trend. This rate was 26.0% in 2016 and increased to 26.4% in 2017.
Vulnerable Road User Casualties
16
Pedestrians Killed
4
Cyclists Killed
68
Motorists Killed
0
Other Killed
1,685
Pedestrians Injured
855
Cyclists Injured
10,484
Motorists Injured
7
Other Injured
Source: Chicago Traffic Crashes · Socrata Open Data · 2017-01-01 to 2017-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained broadly consistent, though the volume increased substantially across all times. Friday was the peak day for crashes in both 2016 (7,394 crashes) and 2017 (13,769 crashes). The peak hour for collisions shifted slightly later in the afternoon, moving from the 3 PM hour in 2016 to the 4 PM hour in 2017.
Source: Chicago Traffic Crashes · Socrata Open Data · 2017-01-01 to 2017-12-31 · Crash date field aggregated by weekday
Source: Chicago Traffic Crashes · Socrata Open Data · 2017-01-01 to 2017-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity worsened from 2016 to 2017, with the fatal crash rate tripling from 0.03% to 0.09%. The proportion of crashes resulting in a serious injury also increased, from 0.6% in 2016 to 1.5% in 2017. Correspondingly, the share of crashes with no reported injuries decreased from 93.8% of all incidents in 2016 to 88.3% in 2017.
Severity is per crash event (most severe injury). 78 fatal crash events resulted in 88 persons killed.
Outcome by Severity (Crash Events)
Source: Chicago Traffic Crashes · Socrata Open Data · 2017-01-01 to 2017-12-31 · KABCO injury classification scale
Severity Distribution
Source: Chicago Traffic Crashes · Socrata Open Data · 2017-01-01 to 2017-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent, with 'Following Too Closely' and 'Failing to Yield Right-of-Way' as the top two causes in both years. However, the count of crashes attributed to these factors grew; 'Failing to Yield' incidents increased by 132.6% (from 4,217 to 9,810), and its share of all factors rose from 9.5% to 11.7%. The count of 'Following Too Closely' crashes increased by 74.5% (from 5,705 to 9,955), though its share of total factors decreased slightly.
Officer-Reported Primary Contributing Cause
Source: Chicago Traffic Crashes · Socrata Open Data · 2017-01-01 to 2017-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of environmental conditions during crashes remained largely similar year-over-year, with most incidents in both periods occurring in clear weather on dry roads. In 2017, the proportion of crashes in clear weather was 80.8%, compared to 79.9% in 2016. There was a slight increase in the proportion of crashes occurring on wet roads (from 11.8% to 13.3%) and during darkness on lighted roads (from 17.7% to 21.0%).
Weather
Source: Chicago Traffic Crashes · Socrata Open Data · 2017-01-01 to 2017-12-31 · Weather condition at time of crash
Lighting
Source: Chicago Traffic Crashes · Socrata Open Data · 2017-01-01 to 2017-12-31 · Lighting condition field
Road Surface
Source: Chicago Traffic Crashes · Socrata Open Data · 2017-01-01 to 2017-12-31 · Road surface condition field
Vehicles & Demographics
The profile of vehicles and persons involved in crashes showed little proportional change between the two years. Chevrolet, Toyota, and Ford were the top three vehicle makes involved in collisions in both 2016 and 2017, maintaining their respective ranks. The age distribution of persons involved also remained consistent, with the 26-34 age group representing the largest cohort in both periods (15.4% in 2016 and 15.8% in 2017).
Top Vehicle Makes (170,194 vehicles)
Source: Chicago Traffic Crashes · Socrata Open Data · 2017-01-01 to 2017-12-31 · Vehicle unit records
55,536 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 (183,040 persons with recorded sex)
Source: Chicago Traffic Crashes · Socrata Open Data · 2017-01-01 to 2017-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones was consistent, with the 30 MPH zone accounting for the vast majority of incidents in both 2016 (73.9%) and 2017 (74.1%). However, the fatal crash rate within these zones increased notably. In the 30 MPH zone, the fatal crash rate more than tripled from 0.027% in 2016 to 0.090% in 2017, while the rate in 35 MPH zones nearly doubled from 0.109% to 0.193%.
Fatal crashes by zone: 15 mph: 2 of 2,669 (0.075%) · 25 mph: 6 of 4,891 (0.123%) · 30 mph: 56 of 62,127 (0.09%) · 35 mph: 11 of 5,706 (0.193%) · 40 mph: 2 of 838 (0.239%) · 45 mph: 1 of 519 (0.193%)
Source: Chicago Traffic Crashes · Socrata Open Data · 2017-01-01 to 2017-12-31 · 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: 2017-01-01 through 2017-12-31
- Report generated: June 1, 2026
Data Coverage
- Reporting period: 2017-01-01 through 2017-12-31 (365 days)
- Geographic scope: Chicago, IL
- Total crash records analyzed: 83,786
- Total persons involved: 185,328
- Total vehicles involved: 170,194
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/2017-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: 2017-01-01 – 2017-12-31
Generated: June 1, 2026 · All rights reserved