ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHICAGO, IL · JANUARY 2018
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/january-2018-report
Monthly Traffic Safety Analysis
9,532 CRASHES IN
CHICAGO, IL
JANUARY 2018
In January 2018, Chicago experienced a substantial increase in traffic incidents compared to January 2017. Total crashes rose from 4,363 to 9,532, marking a 118.5% increase. The most notable year-over-year shift was in total injuries, which surged by 453.0% from 321 to 1,775.
9,532
▲ 118.5%was 4,363
Total Crash Events
11
▲ 266.7%was 3
Persons Killed
1,775
▲ 453.0%was 321
Persons Injured
2,404
▲ 99.5%was 1,205
Hit-and-Run Crashes
Note: "Persons Killed" (11) counts individual fatalities across all crash events. "Fatal" in the severity table below (9) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 18 crashes with unreported severity are not shown in the severity breakdown.
Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for January 2018 indicates a significant upward trend in traffic incidents compared to the prior year. Total crashes increased by 118.5%, rising from 4,363 to 9,532. Fatalities saw a 266.7% increase, climbing from 3 to 11, while total injuries escalated by 453.0% from 321 to 1,775.
2,404
Hit-and-Run Crashes — January 2018
▲ 99.5% vs prior (1,205)
Hit-and-run crashes increased in count from 1,205 in January 2017 to 2,404 in January 2018, representing a 99.5% increase. Despite this rise in raw numbers, the hit-and-run rate relative to total crashes decreased from 27.6% to 25.2% year-over-year.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
10
Motorists Killed
0
Other Killed
304
Pedestrians Injured
34
Cyclists Injured
1,435
Motorists Injured
2
Other Injured
Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Tuesday in both periods, with 722 crashes in January 2017 and 1,659 crashes in January 2018. However, the peak crash hour shifted from 5 PM (366 crashes) in January 2017 to 8 AM (729 crashes) in January 2018, indicating a change in the busiest time of day for incidents.
Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-01-31 · Crash date field aggregated by weekday
Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate increased slightly from 0.07% in January 2017 to 0.09% in January 2018. The proportion of serious injury crashes (code 'A') rose from 0.6% to 1.7% of all crashes, while minor injury crashes (code 'B') increased from 2.6% to 7.5%. Conversely, crashes with no reported injuries (code 'O') decreased in proportion from 94.1% to 85.8%.
Severity is per crash event (most severe injury). 9 fatal crash events resulted in 11 persons killed.
Outcome by Severity (Crash Events)
Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-01-31 · KABCO injury classification scale
Severity Distribution
Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-01-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors saw significant increases in count year-over-year, and their rankings shifted. "Failing to Yield Right-of-Way" crashes increased from 411 to 1,160, a 182.2% change in count, becoming the most frequent factor. "Following Too Closely" crashes also rose from 550 to 1,056, representing a 92.0% change in count, and moved to the second position.
Officer-Reported Primary Contributing Cause
Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'CLEAR' weather conditions increased from 3,120 to 7,057, though their share of total crashes slightly increased from 71.5% to 74.0%. Crashes during 'SNOW' conditions saw a substantial increase from 94 to 964 incidents. On road surfaces, 'DRY' conditions accounted for 5,594 crashes, up from 2,888, while 'SNOW OR SLUSH' conditions saw crashes rise from 66 to 994.
Weather
Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-01-31 · Weather condition at time of crash
Lighting
Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-01-31 · Lighting condition field
Road Surface
Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-01-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 8,686 to 19,341 year-over-year. The '26-34' age group remained the largest demographic involved in crashes, increasing from 1,420 persons to 3,451 persons. Among vehicle makes, Toyota Motor Company, Ltd. surpassed Chevrolet to become the top make involved in crashes, with 2,209 incidents compared to Chevrolet's 2,163.
Top Vehicle Makes (19,341 vehicles)
Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-01-31 · Vehicle unit records
5,833 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 (20,908 persons with recorded sex)
Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph speed zones increased from 3,317 to 7,074 incidents, marking a 113.3% increase in count, with fatal crashes in this zone rising from 2 to 4. Crashes in 35 mph speed zones also saw a significant rise from 219 to 621, with fatal crashes increasing from 1 to 3. The data indicates a general increase in crashes across various speed zones.
Fatal crashes by zone: 20 mph: 1 of 355 (0.282%) · 30 mph: 4 of 7,074 (0.057%) · 35 mph: 3 of 621 (0.483%) · 40 mph: 1 of 108 (0.926%)
Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-01-31 · 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: 2018-01-01 through 2018-01-31
- Report generated: June 1, 2026
Data Coverage
- Reporting period: 2018-01-01 through 2018-01-31 (31 days)
- Geographic scope: Chicago, IL
- Total crash records analyzed: 9,532
- Total persons involved: 21,174
- Total vehicles involved: 19,341
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/january-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Chicago Traffic Crashes · Socrata
Period: 2018-01-01 – 2018-01-31
Generated: June 1, 2026 · All rights reserved