ThatCarHitMe.com
An Injuria.ai Company
CRASH INTELLIGENCE REPORT · CHICAGO, IL · AUGUST 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/august-2016-report
Monthly Traffic Safety Analysis
4,461 CRASHES IN
CHICAGO, IL
AUGUST 2016
In August 2016, Chicago experienced a total of 4,461 traffic crashes, resulting in 2 fatalities and 367 injuries. A significant majority of crashes, 93.7%, were classified as 'No Injury' incidents. This period reflects a notable number of crashes with minimal severe outcomes.
4,461
Total Crash Events
2
Persons Killed
367
Persons Injured
26.2%
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 · 2016-08-01 to 2016-08-31 · Aggregate counts from crash, person, and vehicle records
1,170
Hit-and-Run Crashes — August 2016
During August 2016, there were 1,170 reported hit-and-run crashes in Chicago, accounting for 26.2% of all incidents. This classification is based on the initial determination made by the responding officer at the scene of the crash.
Vulnerable Road User Casualties
During this period, 311 motorists were injured, making them the most impacted group by injuries. One cyclist fatality and 26 cyclist injuries were recorded. Additionally, one motorist fatality and 30 pedestrian injuries were reported.
0
Pedestrians Killed
1
Cyclists Killed
1
Motorists Killed
30
Pedestrians Injured
26
Cyclists Injured
311
Motorists Injured
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Crashes in August 2016 peaked on Fridays, with 707 incidents recorded. The busiest hour for crashes was 3 PM, which saw 379 occurrences. Overall, crash frequency was notably higher during daytime and early evening hours, particularly between 7 AM and 8 PM.
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · Crash date field aggregated by weekday
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The majority of crashes in August 2016, 93.7%, resulted in no reported injuries. Injury-involved crashes, encompassing serious, minor, and possible injuries, collectively represented 6.1% of all incidents. A total of 2 fatal crashes occurred, resulting in 2 fatalities, noting that a single crash event can involve multiple fatalities.
Outcome by Severity (Crash Events)
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · KABCO injury classification scale
Severity Distribution
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors to crashes were 'FOLLOWING TOO CLOSELY' (566 crashes, 12.7%) and 'FAILING TO YIELD RIGHT-OF-WAY' (415 crashes, 9.3%). 'IMPROPER BACKING' was also a significant factor, contributing to 280 crashes, or 6.3% of the total. These three factors collectively represent a substantial portion of identified causes.
Officer-Reported Primary Contributing Cause
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Most crashes in August 2016 occurred under optimal conditions, with 84.8% happening in clear weather, 82.0% on dry road surfaces, and 72.7% during daylight hours. Adverse conditions such as rain accounted for 358 crashes, and wet road surfaces were present in 435 incidents. Additionally, 612 crashes occurred in darkness on lighted roads, and 190 in unlit darkness.
Weather
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · Weather condition at time of crash
Lighting
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · Lighting condition field
Road Surface
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · Road surface condition field
Vehicles & Demographics
Among persons involved in crashes, the 26-34 age group was most represented with 1,461 individuals, followed by the 35-44 age group with 1,225. Toyota Motor Company, Ltd. vehicles were involved in the highest number of incidents at 1,100, closely followed by Chevrolet with 1,080. Ford vehicles were involved in 831 incidents.
Top Vehicle Makes (8,964 vehicles)
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · Vehicle unit records
3,098 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 (9,500 persons with recorded sex)
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · Person-level records linked to crash events
Speed Limit Zones
The 30 mph speed limit zone accounted for the highest number of crashes, with 3,328 incidents, representing 74.6% of all crashes. Within this zone, 0.03% of crashes were fatal. The 35 mph zone had 265 crashes, and 0.377% of crashes in this zone were fatal.
Fatal crashes by zone: 30 mph: 1 of 3,328 (0.03%) · 35 mph: 1 of 265 (0.377%)
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · Posted speed limit at crash location
Crashes by District
District 08 recorded the highest number of crashes, with 422 incidents, accounting for 9.46% of all crashes. District 01 and District 18 also showed significant concentrations, with 383 and 351 crashes respectively. These districts represent key areas for crash occurrences.
Crashes by District
"Other" combines 15 smaller categories (2,264 records): District 24 (195), District 14 (186), District 06 (185), District 09 (178), District 10 (175), District 17 (169), District 25 (163), District 04 (161), District 11 (150), District 20 (130), District 22 (130), District 02 (127), District 16 (120), District 15 (102), District 05 (93).
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · Person-level records
First Crash Type
The most common first crash type was 'REAR END', accounting for 1,278 incidents or 28.6% of all crashes. This was followed by 'PARKED MOTOR VEHICLE' incidents, which numbered 1,003, representing 22.5% of the total. 'SIDESWIPE SAME DIRECTION' was the third most frequent type with 835 crashes.
First Crash Type
Showing top 9 of 14 reported. 5 additional (73 total) not shown: HEAD ON, OTHER OBJECT, OTHER NONCOLLISION, ANIMAL, OVERTURNED.
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · Person-level records
Point of Impact
The 'FRONT' area was the most common point of impact reported in 1,827 instances. The 'REAR' was the second most frequent impact area, with 1,519 reported instances. 'FRONT-LEFT' and 'FRONT-RIGHT' were also significant, with 998 and 964 instances respectively, indicating primary impact zones.
Point of Impact
"Other" combines 5 smaller categories (575 records): REAR-RIGHT (474), TOTAL (ALL AREAS) (43), OTHER (36), UNDER CARRIAGE (18), ROOF (4).
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · Person-level records
Pre-Crash Driver Action
The most frequent pre-crash action reported was 'STRAIGHT AHEAD', occurring in 3,947 instances. 'PARKED' was the second most common action, reported in 1,050 instances. 'SLOW/STOP IN TRAFFIC' was noted in 768 instances, highlighting these as dominant actions immediately preceding crashes.
Pre-Crash Driver Action
Showing top 9 of 26 reported. 17 additional (655 total) not shown: OTHER, ENTERING TRAFFIC LANE FROM PARKING, LEAVING TRAFFIC LANE TO PARK, MERGING, STARTING IN TRAFFIC, SLOW/STOP - LEFT TURN, U-TURN, AVOIDING VEHICLES/OBJECTS, ENTER FROM DRIVE/ALLEY, PARKED IN TRAFFIC LANE, SLOW/STOP - RIGHT TURN, SKIDDING/CONTROL LOSS, SLOW/STOP - LOAD/UNLOAD, NEGOTIATING A CURVE, DRIVING WRONG WAY, DRIVERLESS, TURNING ON RED.
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · Person-level records
Pedestrian/Cyclist Action
Among reported pedestrian actions, 'WITH TRAFFIC' was the most frequent, occurring in 21 instances. 'OTHER ACTION' was noted in 17 instances, and 'CROSSING - WITH SIGNAL' in 10 instances. These actions represent common behaviors by pedestrians involved in crash events.
Pedestrian/Cyclist Action
Showing top 9 of 14 reported. 5 additional (10 total) not shown: ENTER FROM DRIVE/ALLEY, TURNING LEFT, INTOXICATED PED/PEDAL, TURNING RIGHT, PLAYING IN ROADWAY.
Source: Chicago Traffic Crashes · Socrata Open Data · 2016-08-01 to 2016-08-31 · 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: 2016-08-01 through 2016-08-31
- Report generated: June 1, 2026
Data Coverage
- Reporting period: 2016-08-01 through 2016-08-31 (31 days)
- Geographic scope: Chicago, IL
- Total crash records analyzed: 4,461
- Total persons involved: 9,622
- Total vehicles involved: 8,964
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/august-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: 2016-08-01 – 2016-08-31
Generated: June 1, 2026 · All rights reserved