Monthly Traffic Safety Analysis

4,720 CRASHES IN
CHICAGO, IL
NOVEMBER 2016

During November 2016 in Chicago, there were 4720 traffic crashes, resulting in 1 fatality and 397 injuries. A significant majority of these crashes, 93.7%, were reported with no injuries. The data indicates that 26.5% of all crashes involved a hit-and-run incident.

4,720

Total Crash Events

1

Persons Killed

397

Persons Injured

26.5%

Hit-and-Run Rate

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 7 crashes with unreported severity are not shown in the severity breakdown.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Aggregate counts from crash, person, and vehicle records

1,253

Hit-and-Run Crashes — November 2016

During November 2016, Chicago recorded 1253 hit-and-run crashes, representing 26.5% of all reported incidents. This indicates that over one-quarter of crashes involved a driver leaving the scene. The hit-and-run status is determined by the responding officer's initial assessment.

Vulnerable Road User Casualties

During November 2016, 1 motorist was killed, and 330 motorists were injured in traffic crashes. Pedestrians experienced 49 injuries, with no pedestrian fatalities reported. Cyclists sustained 18 injuries, and no cyclist fatalities were recorded during this period.

0

Pedestrians Killed

0

Cyclists Killed

1

Motorists Killed

49

Pedestrians Injured

18

Cyclists Injured

330

Motorists Injured

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Traffic crashes in Chicago during November 2016 peaked on Wednesday with 938 incidents, and the highest hourly concentration occurred at 5 PM with 414 crashes. The majority of crashes, 58.1%, happened during daylight hours. Crashes occurring in darkness, including lighted roads, accounted for 31.4% of the total.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Crash date field aggregated by weekday

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

In November 2016, 93.7% of crashes resulted in no injuries, totaling 4422 incidents. Injury crashes, including serious, minor, and possible injuries, accounted for 6.1% of all crashes. There was 1 fatal crash recorded, which resulted in 1 fatality during this period.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0%
Serious Injury27serious injury crashes0.6%
Minor Injury154minor injury crashes3.3%
Possible Injury109possible injury crashes2.3%
No Injury4,422no injury crashes93.7%

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · KABCO injury classification scale

Severity Distribution

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Most severe injury per crash record

Top Contributing Factors

The most frequently cited contributing factor in crashes was 'FOLLOWING TOO CLOSELY', involved in 598 incidents, or 12.7% of the total. 'FAILING TO YIELD RIGHT-OF-WAY' was the second leading factor, contributing to 441 crashes (9.3%). 'IMPROPER OVERTAKING/PASSING' was also a notable factor, occurring in 251 crashes, representing 5.3% of the incidents.

Officer-Reported Primary Contributing Cause

FOLLOWING TOO CLOSELY598 (12.7%)
FAILING TO YIELD RIGHT-OF-WAY441 (9.3%)
IMPROPER OVERTAKING/PASSING251 (5.3%)
IMPROPER LANE USAGE192 (4.1%)
IMPROPER BACKING192 (4.1%)
DRIVING SKILLS/KNOWLEDGE/EXPERIENCE147 (3.1%)
IMPROPER TURNING/NO SIGNAL140 (3%)
FAILING TO REDUCE SPEED TO AVOID CRASH105 (2.2%)
DISREGARDING TRAFFIC SIGNALS49 (1%)
DISREGARDING STOP SIGN49 (1%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes, 80.4%, occurred under clear weather conditions, with 77.8% happening on dry road surfaces. Adverse weather conditions such as rain, fog, sleet, or snow were present in 13.1% of crashes. Similarly, wet or snowy/slushy road surfaces were reported in 15.2% of incidents.

Weather

CLEAR3,793 (84.1%)
RAIN606 (13.4%)
CLOUDY/OVERCAST89 (2.0%)
FOG/SMOKE/HAZE11 (0.2%)
OTHER8 (0.2%)
SLEET/HAIL1 (0.0%)
SNOW1 (0.0%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Weather condition at time of crash

Lighting

DAYLIGHT2,741 (60.3%)
DARKNESS, LIGHTED ROAD1,025 (22.5%)
DARKNESS458 (10.1%)
DUSK227 (5.0%)
DAWN96 (2.1%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Lighting condition field

Road Surface

DRY3,670 (83.4%)
WET714 (16.2%)
OTHER12 (0.3%)
SAND, MUD, DIRT1 (0.0%)
SNOW OR SLUSH1 (0.0%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Road surface condition field

Vehicles & Demographics

The age group 26-34 was most represented among persons involved in crashes, with 1564 individuals, followed by 35-44 (1290 persons) and 45-54 (1150 persons). The most frequently involved vehicle makes were Chevrolet with 1129 instances, Toyota Motor Company, Ltd. with 1118, and Ford with 925.

Top Vehicle Makes (9,543 vehicles)

1
CHEVROLET1,129 (11.8%)
2
TOYOTA MOTOR COMPANY, LTD.1,118 (11.7%)
3
FORD925 (9.7%)
4
NISSAN753 (7.9%)
5
HONDA650 (6.8%)
6
DODGE482 (5.1%)
7
HYUNDAI362 (3.8%)
8
JEEP295 (3.1%)
9
CHRYSLER237 (2.5%)
10
KIA MOTORS CORP191 (2%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Vehicle unit records

3,411 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 (10,126 persons with recorded sex)

Male5,122 (50.6%)
Female4,075 (40.2%)
Non-Binary929 (9.2%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Person-level records linked to crash events

Speed Limit Zones

The 30 mph speed limit zone accounted for the highest number of crashes, with 3653 incidents, representing 77.4% of all crashes. Within the 30 mph zone, 0% of crashes were fatal. The only fatal crash occurred in a 10 mph speed limit zone, where 1.064% of crashes were fatal.

Fatal crashes by zone: 10 mph: 1 of 94 (1.064%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Posted speed limit at crash location

Crashes by District

District 08 recorded the highest number of crashes with 425 incidents, accounting for 9.0% of all crashes. District 01 followed with 385 crashes, and District 12 reported 356 crashes. These districts represent areas with higher concentrations of traffic incidents.

Crashes by District

"Other" combines 15 smaller categories (2,499 records): District 07 (247), District 06 (206), District 09 (200), District 16 (199), District 24 (178), District 10 (166), District 20 (165), District 14 (159), District 11 (156), District 04 (154), District 02 (153), District 22 (152), District 15 (134), District 17 (127), District 05 (103).

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Person-level records

First Crash Type

The most common first crash type was 'REAR END' collisions, accounting for 1375 incidents. Crashes involving 'PARKED MOTOR VEHICLE' were also frequent, with 1030 occurrences. 'SIDESWIPE SAME DIRECTION' collisions represented another significant category, with 920 reported incidents.

First Crash Type

1
REAR END1,375 (29.1%)
2
PARKED MOTOR VEHICLE1,030 (21.8%)
3
SIDESWIPE SAME DIRECTION920 (19.5%)
4
TURNING611 (12.9%)
5
ANGLE445 (9.4%)
6
FIXED OBJECT92 (1.9%)
7
SIDESWIPE OPPOSITE DIRECTION79 (1.7%)
8
PEDESTRIAN63 (1.3%)
9
PEDALCYCLIST45 (1%)

Showing top 9 of 14 reported. 5 additional (60 total) not shown: OTHER OBJECT, HEAD ON, OTHER NONCOLLISION, ANIMAL, TRAIN.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Person-level records

Point of Impact

The 'FRONT' of vehicles was the most frequent point of impact, recorded in 1816 instances. 'REAR' impacts were the second most common, with 1510 occurrences. 'FRONT-LEFT' impacts were also significant, appearing in 1232 instances.

Point of Impact

"Other" combines 5 smaller categories (556 records): REAR-RIGHT (503), OTHER (23), TOTAL (ALL AREAS) (17), UNDER CARRIAGE (7), ROOF (6).

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Person-level records

Pre-Crash Driver Action

The most common pre-crash action reported was 'STRAIGHT AHEAD', accounting for 4399 instances, or 51.0% of known actions. Vehicles that were 'PARKED' represented 1079 instances, or 12.5%. Another frequent action was 'SLOW/STOP IN TRAFFIC', occurring 712 times, which is 8.3% of known actions.

Pre-Crash Driver Action

1
STRAIGHT AHEAD4,399 (46.7%)
2
PARKED1,079 (11.5%)
3
UNKNOWN/NA832 (8.8%)
4
SLOW/STOP IN TRAFFIC712 (7.6%)
5
TURNING LEFT458 (4.9%)
6
BACKING412 (4.4%)
7
TURNING RIGHT305 (3.2%)
8
PASSING/OVERTAKING266 (2.8%)
9
CHANGING LANES200 (2.1%)

Showing top 9 of 27 reported. 18 additional (755 total) not shown: OTHER, ENTERING TRAFFIC LANE FROM PARKING, STARTING IN TRAFFIC, MERGING, LEAVING TRAFFIC LANE TO PARK, U-TURN, SLOW/STOP - LEFT TURN, AVOIDING VEHICLES/OBJECTS, ENTER FROM DRIVE/ALLEY, SLOW/STOP - RIGHT TURN, PARKED IN TRAFFIC LANE, NEGOTIATING A CURVE, SLOW/STOP - LOAD/UNLOAD, SKIDDING/CONTROL LOSS, DRIVING WRONG WAY, TURNING ON RED, DIVERGING, DRIVERLESS.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · Person-level records

Pedestrian/Cyclist Action

Among reported pedestrian actions, 'WITH TRAFFIC' was the most common, accounting for 30 instances or 31.6% of known actions. 'CROSSING - WITH SIGNAL' was observed in 25 instances, representing 26.3% of known actions. 'OTHER ACTION' was noted 14 times.

Pedestrian/Cyclist Action

1
WITH TRAFFIC30 (25.9%)
2
CROSSING - WITH SIGNAL25 (21.6%)
3
UNKNOWN/NA21 (18.1%)
4
OTHER ACTION14 (12.1%)
5
NOT AT INTERSECTION7 (6%)
6
CROSSING - AGAINST SIGNAL6 (5.2%)
7
NO ACTION5 (4.3%)
8
PARKED VEHICLE3 (2.6%)
9
WORKING IN ROADWAY1 (0.9%)

Showing top 9 of 13 reported. 4 additional (4 total) not shown: ENTER FROM DRIVE/ALLEY, INTOXICATED PED/PEDAL, PLAYING/WORKING ON VEHICLE, AGAINST TRAFFIC.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-11-01 to 2016-11-30 · 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: 2016-11-01 through 2016-11-30
  • Report generated: June 1, 2026

Data Coverage

  • Reporting period: 2016-11-01 through 2016-11-30 (30 days)
  • Geographic scope: Chicago, IL
  • Total crash records analyzed: 4,720
  • Total persons involved: 10,274
  • Total vehicles involved: 9,543

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/november-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

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Chicago, IL Crash Report — November 2016 | ThatCarHitMe.com