ThatCarHitMe.com
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CRASH INTELLIGENCE REPORT · CHICAGO, IL · JULY 2016
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/july-2016-report
Monthly Traffic Safety Analysis
3,316 CRASHES IN
CHICAGO, IL
JULY 2016
In July 2016, Chicago recorded 3,316 traffic crashes, resulting in 2 fatalities and 264 injuries. A notable finding is that 831 crashes, or 25.1% of the total, were classified as hit-and-run incidents.
3,316
Total Crash Events
2
Persons Killed
264
Persons Injured
25.1%
Hit-and-Run Rate
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Aggregate counts from crash, person, and vehicle records
831
Hit-and-Run Crashes — July 2016
During July 2016, 831 crashes were identified as hit-and-run incidents, representing 25.1% of all crashes. This classification is based on the initial determination made by the responding officer at the scene.
Vulnerable Road User Casualties
In July 2016, 1 pedestrian was killed and 22 pedestrians were injured. One motorist was killed and 224 motorists were injured. There were no cyclist fatalities, but 18 cyclists sustained injuries.
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
22
Pedestrians Injured
18
Cyclists Injured
224
Motorists Injured
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Crashes in July 2016 peaked on Fridays, with 644 incidents recorded, and the peak hour for crashes was 4 p.m., with 305 occurrences. The majority of crashes, 2,490, occurred during daylight hours, while 539 occurred in darkness (lighted or unlighted roads).
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Crash date field aggregated by weekday
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Out of 3,316 crashes, 2 were fatal, and 184 crashes involved injuries of varying severity (Serious, Minor, or Possible). The vast majority, 3,125 crashes (94.2%), resulted in no reported injuries. Two persons were killed in these fatal crashes, which aligns with the count of fatal crashes.
Outcome by Severity (Crash Events)
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · KABCO injury classification scale
Severity Distribution
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor in crashes was 'FOLLOWING TOO CLOSELY,' accounting for 420 incidents (12.7%). This was followed by 'FAILING TO YIELD RIGHT-OF-WAY' with 299 incidents (9%) and 'IMPROPER OVERTAKING/PASSING' with 206 incidents (6.2%).
Officer-Reported Primary Contributing Cause
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Most crashes occurred under clear weather (2,868 incidents), on dry road surfaces (2,801 incidents), and during daylight hours (2,490 incidents). Adverse conditions such as rain, snow, or fog contributed to 219 crashes, while wet or snowy road surfaces were present in 257 crashes.
Weather
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Weather condition at time of crash
Lighting
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Lighting condition field
Road Surface
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Road surface condition field
Vehicles & Demographics
The age group most frequently involved in crashes was 26-34 years old, with 1,109 persons. This was followed by the 35-44 age group, with 940 persons. Chevrolet was the most frequently involved vehicle make, appearing in 814 incidents, followed by Toyota Motor Company, Ltd. with 746 incidents.
Top Vehicle Makes (6,691 vehicles)
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Vehicle unit records
2,291 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 (7,092 persons with recorded sex)
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Person-level records linked to crash events
Speed Limit Zones
The 30 mph speed limit zone accounted for the highest number of crashes, with 2,383 incidents, representing 71.8% of all crashes. Within this zone, 0.084% of crashes were fatal. All 2 fatal crashes in July 2016 occurred in areas with a posted speed limit of 30 mph.
Fatal crashes by zone: 30 mph: 2 of 2,383 (0.084%)
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Posted speed limit at crash location
Crashes by District
District 01 recorded the highest number of crashes, with 386 incidents, accounting for 11.64% of the total. District 18 followed with 359 crashes, and District 08 reported 285 crashes.
Crashes by District
"Other" combines 15 smaller categories (1,495 records): District 10 (155), District 11 (124), District 09 (121), District 22 (118), District 15 (103), District 02 (102), District 17 (99), District 20 (98), District 14 (94), District 04 (93), District 19 (90), District 07 (88), District 25 (87), District 05 (73), District 16 (50).
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Person-level records
First Crash Type
The most common first crash type was 'REAR END,' accounting for 959 incidents, or 28.9% of all crashes. 'PARKED MOTOR VEHICLE' was the second most frequent type with 748 incidents, followed by 'SIDESWIPE SAME DIRECTION' with 620 incidents.
First Crash Type
Showing top 9 of 14 reported. 5 additional (69 total) not shown: HEAD ON, OTHER OBJECT, OTHER NONCOLLISION, OVERTURNED, ANIMAL.
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Person-level records
Point of Impact
The 'FRONT' was the most common point of impact on vehicles, accounting for 1,322 instances. This represents 19.8% of the total 6,691 vehicles involved. The 'REAR' was the second most common impact area, with 1,061 instances.
Point of Impact
"Other" combines 5 smaller categories (435 records): REAR-RIGHT (362), TOTAL (ALL AREAS) (38), OTHER (14), ROOF (13), UNDER CARRIAGE (8).
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Person-level records
Pre-Crash Driver Action
The most frequent pre-crash action for persons involved was 'STRAIGHT AHEAD,' with 2,911 instances, representing 40.5% of all persons. 'PARKED' was the second most common action with 773 instances, followed by 'SLOW/STOP IN TRAFFIC' with 563 instances.
Pre-Crash Driver Action
Showing top 9 of 26 reported. 17 additional (560 total) not shown: OTHER, ENTERING TRAFFIC LANE FROM PARKING, MERGING, LEAVING TRAFFIC LANE TO PARK, SLOW/STOP - LEFT TURN, STARTING IN TRAFFIC, U-TURN, ENTER FROM DRIVE/ALLEY, AVOIDING VEHICLES/OBJECTS, SLOW/STOP - RIGHT TURN, PARKED IN TRAFFIC LANE, SLOW/STOP - LOAD/UNLOAD, NEGOTIATING A CURVE, SKIDDING/CONTROL LOSS, DRIVING WRONG WAY, TURNING ON RED, DRIVERLESS.
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Person-level records
Pedestrian/Cyclist Action
Among pedestrians involved in crashes, 'WITH TRAFFIC' was the most reported action, with 17 instances, accounting for 50% of pedestrian actions. 'CROSSING - WITH SIGNAL' was the second most frequent action, with 13 instances.
Pedestrian/Cyclist Action
Showing top 9 of 12 reported. 3 additional (3 total) not shown: WORKING IN ROADWAY, PARKED VEHICLE, PLAYING IN ROADWAY.
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-07-01 to 2016-07-31 · Person-level records
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: 2016-07-01 through 2016-07-31
- Report generated: June 1, 2026
Data Coverage
- Reporting period: 2016-07-01 through 2016-07-31 (31 days)
- Geographic scope: Chicago, IL
- Total crash records analyzed: 3,316
- Total persons involved: 7,194
- Total vehicles involved: 6,691
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/july-2016-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: 2016-07-01 – 2016-07-31
Generated: June 1, 2026 · All rights reserved