Monthly Traffic Safety Analysis

4,995 CRASHES IN
CHICAGO, IL
OCTOBER 2016

Total crashes in Chicago during October 2016 were 4995, resulting in 3 fatalities and 479 injuries. The most frequent contributing factor to crashes was "FOLLOWING TOO CLOSELY," accounting for 12.2% of all incidents. These figures highlight the overall crash landscape for the period.

4,995

Total Crash Events

3

Persons Killed

479

Persons Injured

25.3%

Hit-and-Run Rate

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 8 crashes with unreported severity are not shown in the severity breakdown.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Aggregate counts from crash, person, and vehicle records

1,265

Hit-and-Run Crashes — October 2016

There were 1265 hit-and-run crashes reported in October 2016, representing 25.3% of all crashes. This indicates that approximately one in four crashes involved a driver leaving the scene. Hit-and-run status is based on the responding officer's initial determination.

Vulnerable Road User Casualties

Motorists were the most impacted group, with 3 fatalities and 391 injuries reported. While no pedestrian or cyclist fatalities occurred, 56 pedestrians and 32 cyclists sustained injuries. These figures highlight the human toll across different road user groups.

0

Pedestrians Killed

0

Cyclists Killed

3

Motorists Killed

56

Pedestrians Injured

32

Cyclists Injured

391

Motorists Injured

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash data for October 2016 indicates that Saturday was the peak day for crashes with 782 incidents, closely followed by Wednesday with 771 crashes. The peak hour for crashes was 3 PM, recording 406 incidents. A significant majority of crashes, 3322, occurred during daylight hours, while 1159 crashes occurred in darkness.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Crash date field aggregated by weekday

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Of the 4995 crashes reported, 92.8% (4634 incidents) resulted in no injuries. There were 3 fatal crashes, leading to 3 fatalities. An additional 350 crashes resulted in some level of injury, ranging from possible to serious.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.1%
Serious Injury43serious injury crashes0.9%
Minor Injury170minor injury crashes3.4%
Possible Injury137possible injury crashes2.7%
No Injury4,634no injury crashes92.8%

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · KABCO injury classification scale

Severity Distribution

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor to crashes was "FOLLOWING TOO CLOSELY," involved in 608 incidents, or 12.2% of all crashes. "FAILING TO YIELD RIGHT-OF-WAY" was the second most common factor, accounting for 506 crashes (10.1%). Other significant factors included "IMPROPER OVERTAKING/PASSING" (307 crashes) and "IMPROPER BACKING" (241 crashes).

Officer-Reported Primary Contributing Cause

FOLLOWING TOO CLOSELY608 (12.2%)
FAILING TO YIELD RIGHT-OF-WAY506 (10.1%)
IMPROPER OVERTAKING/PASSING307 (6.1%)
IMPROPER BACKING241 (4.8%)
IMPROPER LANE USAGE206 (4.1%)
IMPROPER TURNING/NO SIGNAL162 (3.2%)
FAILING TO REDUCE SPEED TO AVOID CRASH138 (2.8%)
DRIVING SKILLS/KNOWLEDGE/EXPERIENCE136 (2.7%)
DISREGARDING STOP SIGN48 (1%)
DISREGARDING TRAFFIC SIGNALS45 (0.9%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes occurred under clear weather conditions (4006 incidents), on dry road surfaces (3949 incidents), and during daylight hours (3322 incidents). However, adverse conditions also contributed to crashes, with 587 incidents occurring in rain and 708 on wet road surfaces. A total of 1159 crashes occurred during periods of darkness.

Weather

CLEAR4,006 (83.9%)
RAIN587 (12.3%)
CLOUDY/OVERCAST162 (3.4%)
OTHER8 (0.2%)
FOG/SMOKE/HAZE7 (0.1%)
SNOW2 (0.0%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Weather condition at time of crash

Lighting

DAYLIGHT3,322 (69.1%)
DARKNESS, LIGHTED ROAD854 (17.8%)
DARKNESS305 (6.3%)
DUSK205 (4.3%)
DAWN119 (2.5%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Lighting condition field

Road Surface

DRY3,949 (84.6%)
WET708 (15.2%)
OTHER11 (0.2%)
SAND, MUD, DIRT2 (0.0%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Road surface condition field

Vehicles & Demographics

The age group with the highest number of persons involved in crashes was 26-34, accounting for 1689 individuals. This was followed by the 35-44 age group with 1405 individuals. Chevrolet vehicles were involved in the most crashes, with 1227 incidents, while Toyota vehicles were involved in 1170 incidents.

Top Vehicle Makes (10,050 vehicles)

1
CHEVROLET1,227 (12.2%)
2
TOYOTA MOTOR COMPANY, LTD.1,170 (11.6%)
3
FORD974 (9.7%)
4
NISSAN794 (7.9%)
5
HONDA692 (6.9%)
6
DODGE442 (4.4%)
7
HYUNDAI377 (3.8%)
8
JEEP351 (3.5%)
9
CHRYSLER199 (2%)
10
KIA MOTORS CORP195 (1.9%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Vehicle unit records

3,569 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 (10,711 persons with recorded sex)

Male5,457 (50.9%)
Female4,314 (40.3%)
Non-Binary940 (8.8%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Person-level records linked to crash events

Speed Limit Zones

The 30 mph speed limit zone recorded the highest number of crashes, with 3784 incidents, representing 75.75% of all crashes. Within this zone, 0.053% of crashes were fatal. The 35 mph speed limit zone had the highest fatal crash percentage at 0.369%, with 1 fatal crash out of 271 total crashes in that zone.

Fatal crashes by zone: 30 mph: 2 of 3,784 (0.053%) · 35 mph: 1 of 271 (0.369%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Posted speed limit at crash location

Crashes by District

Police District 08 recorded the highest number of crashes, with 467 incidents, representing 9.35% of all crashes. District 01 followed with 434 crashes, and District 12 with 362 crashes. These districts show a concentration of crash activity within the city.

Crashes by District

"Other" combines 15 smaller categories (2,539 records): District 03 (266), District 06 (222), District 24 (197), District 09 (186), District 14 (178), District 10 (172), District 16 (172), District 22 (171), District 11 (156), District 02 (154), District 17 (152), District 04 (141), District 20 (140), District 15 (129), District 05 (103).

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Person-level records

First Crash Type

Rear-end collisions were the most frequent type of first crash, accounting for 1410 incidents, or 28.23% of all crashes. Crashes involving a parked motor vehicle were the second most common, with 1105 incidents. Pedestrian-involved crashes numbered 65, and pedalcyclist-involved crashes numbered 61.

First Crash Type

1
REAR END1,410 (28.2%)
2
PARKED MOTOR VEHICLE1,105 (22.1%)
3
SIDESWIPE SAME DIRECTION977 (19.6%)
4
TURNING624 (12.5%)
5
ANGLE464 (9.3%)
6
FIXED OBJECT131 (2.6%)
7
SIDESWIPE OPPOSITE DIRECTION66 (1.3%)
8
PEDESTRIAN65 (1.3%)
9
PEDALCYCLIST61 (1.2%)

Showing top 9 of 13 reported. 4 additional (92 total) not shown: HEAD ON, OTHER NONCOLLISION, OTHER OBJECT, ANIMAL.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Person-level records

Point of Impact

The "FRONT" of vehicles was the most common point of impact, recorded in 1887 incidents, representing 25.09% of all reported impact points. "REAR" impacts were also frequent, occurring in 1582 incidents. "FRONT-LEFT" and "FRONT-RIGHT" impacts were reported in 1250 and 1197 incidents, respectively.

Point of Impact

"Other" combines 5 smaller categories (658 records): REAR-RIGHT (571), OTHER (33), TOTAL (ALL AREAS) (22), UNDER CARRIAGE (22), ROOF (10).

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Person-level records

Pre-Crash Driver Action

The most common pre-crash action was vehicles going "STRAIGHT AHEAD," involved in 4502 incidents, or 48.97% of reported actions. "PARKED" vehicles were involved in 1169 incidents, and "SLOW/STOP IN TRAFFIC" was recorded for 803 incidents.

Pre-Crash Driver Action

1
STRAIGHT AHEAD4,502 (45.5%)
2
PARKED1,169 (11.8%)
3
UNKNOWN/NA842 (8.5%)
4
SLOW/STOP IN TRAFFIC803 (8.1%)
5
BACKING488 (4.9%)
6
TURNING LEFT456 (4.6%)
7
TURNING RIGHT308 (3.1%)
8
PASSING/OVERTAKING300 (3%)
9
CHANGING LANES232 (2.3%)

Showing top 9 of 26 reported. 17 additional (799 total) not shown: OTHER, ENTERING TRAFFIC LANE FROM PARKING, MERGING, STARTING IN TRAFFIC, SLOW/STOP - LEFT TURN, U-TURN, LEAVING TRAFFIC LANE TO PARK, AVOIDING VEHICLES/OBJECTS, SLOW/STOP - RIGHT TURN, PARKED IN TRAFFIC LANE, ENTER FROM DRIVE/ALLEY, SKIDDING/CONTROL LOSS, SLOW/STOP - LOAD/UNLOAD, NEGOTIATING A CURVE, TURNING ON RED, DRIVING WRONG WAY, DRIVERLESS.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · Person-level records

Pedestrian/Cyclist Action

The most common pedestrian action before a crash was "CROSSING - WITH SIGNAL," accounting for 30 incidents. "WITH TRAFFIC" was the second most frequent action, involved in 28 incidents.

Pedestrian/Cyclist Action

1
CROSSING - WITH SIGNAL30 (22.4%)
2
WITH TRAFFIC28 (20.9%)
3
UNKNOWN/NA25 (18.7%)
4
OTHER ACTION10 (7.5%)
5
NOT AT INTERSECTION10 (7.5%)
6
NO ACTION9 (6.7%)
7
AGAINST TRAFFIC8 (6%)
8
CROSSING - AGAINST SIGNAL5 (3.7%)
9
PARKED VEHICLE3 (2.2%)

Showing top 9 of 13 reported. 4 additional (6 total) not shown: TURNING LEFT, INTOXICATED PED/PEDAL, STANDING IN ROADWAY, TURNING RIGHT.

Source: Chicago Traffic Crashes · Socrata Open Data · 2016-10-01 to 2016-10-31 · 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: 2016-10-01 through 2016-10-31
  • Report generated: June 1, 2026

Data Coverage

  • Reporting period: 2016-10-01 through 2016-10-31 (31 days)
  • Geographic scope: Chicago, IL
  • Total crash records analyzed: 4,995
  • Total persons involved: 10,856
  • Total vehicles involved: 10,050

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/october-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 — October 2016 | ThatCarHitMe.com