Monthly Traffic Safety Analysis

9,648 CRASHES IN
CHICAGO, IL
APRIL 2018

All metrics benchmarked againstApril 2017

In April 2018, Chicago experienced a significant increase in traffic crashes and fatalities compared to April 2017. Total crashes rose from 5024 to 9648, marking a 92.04% increase year-over-year. The most notable shift was in fatalities, which increased from 2 in April 2017 to 11 in April 2018, a 450% rise.

9,648

92.0%was 5,024

Total Crash Events

11

450.0%was 2

Persons Killed

1,784

250.5%was 509

Persons Injured

2,559

83.6%was 1,394

Hit-and-Run Crashes

Note: "Persons Killed" (11) counts individual fatalities across all crash events. "Fatal" in the severity table below (11) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 21 crashes with unreported severity are not shown in the severity breakdown.

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-04-01 to 2018-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data indicates a substantial upward trend year-over-year. Total crashes increased by 4624, from 5024 in April 2017 to 9648 in April 2018. This represents a 92.04% increase in the total number of crash incidents.

2,559

Hit-and-Run Crashes — April 2018

83.6% vs prior (1,394)

The number of hit-and-run crashes increased by 1165, from 1394 in April 2017 to 2559 in April 2018. Despite this increase in count, the hit-and-run rate decreased slightly from 27.7% of total crashes in April 2017 to 26.5% in April 2018.

Vulnerable Road User Casualties

7

Pedestrians Killed

Prior: 0%

0

Cyclists Killed

Prior: 00.0%

4

Motorists Killed

Prior: 2100.0%

0

Other Killed

Prior: 00.0%

236

Pedestrians Injured

Prior: 52353.8%

75

Cyclists Injured

Prior: 28167.9%

1,472

Motorists Injured

Prior: 428243.9%

1

Other Injured

Prior: 10.0%

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-04-01 to 2018-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted year-over-year, with the peak day changing from Saturday in April 2017 (938 crashes) to Monday in April 2018 (1696 crashes). The peak hour also shifted from 3 PM in April 2017 (406 crashes) to 4 PM in April 2018 (715 crashes), indicating a later afternoon peak in the current period.

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-04-01 to 2018-04-30 · Crash date field aggregated by weekday

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-04-01 to 2018-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution shows an increase in fatal and injury crashes. The fatal crash rate rose from 0.04% in April 2017 to 0.11% in April 2018. Serious injuries (Severity A) as a proportion of total crashes increased from 0.9% to 1.8%, while minor injuries (Severity B) increased from 3.7% to 7.4% year-over-year.

Outcome by Severity (Crash Events)

Fatal11fatal crashes0.1%
450.0%prior 2
Serious Injury169serious injury crashes1.8%
259.6%prior 47
Minor Injury717minor injury crashes7.4%
283.4%prior 187
Possible Injury401possible injury crashes4.2%
182.4%prior 142
No Injury8,329no injury crashes86.3%
79.6%prior 4,638

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-04-01 to 2018-04-30 · KABCO injury classification scale

Severity Distribution

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-04-01 to 2018-04-30 · Most severe injury per crash record

Top Contributing Factors

Contributing factors saw substantial increases in counts across the board. 'Failing to Yield Right-of-Way' increased by 611 crashes (118.4% change in count) from 516 to 1127, becoming the top factor in April 2018 with an 11.7% share. 'Following Too Closely' also rose significantly by 393 crashes (62.5% change in count) from 629 to 1022, holding a 10.6% share in the current period.

Officer-Reported Primary Contributing Cause

FAILING TO YIELD RIGHT-OF-WAY1,127 (11.7%)118.4%prior 516
FOLLOWING TOO CLOSELY1,022 (10.6%)62.5%prior 629
IMPROPER OVERTAKING/PASSING483 (5%)76.3%prior 274
IMPROPER BACKING438 (4.5%)106.6%prior 212
FAILING TO REDUCE SPEED TO AVOID CRASH407 (4.2%)171.3%prior 150
IMPROPER LANE USAGE376 (3.9%)112.4%prior 177
IMPROPER TURNING/NO SIGNAL334 (3.5%)167.2%prior 125
DRIVING SKILLS/KNOWLEDGE/EXPERIENCE308 (3.2%)87.8%prior 164
WEATHER232 (2.4%)241.2%prior 68
DISREGARDING TRAFFIC SIGNALS170 (1.8%)174.2%prior 62

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-04-01 to 2018-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a notable shift in adverse weather and road conditions contributing to crashes. Crashes occurring during 'SNOW' weather conditions increased from 2 in April 2017 to 507 in April 2018. Similarly, crashes on 'SNOW OR SLUSH' road surfaces increased from 1 to 207, and crashes on 'ICE' road surfaces appeared with 199 incidents in April 2018, having not been recorded in April 2017.

Weather

CLEAR7,349 (78.8%)
88.7%prior 3,895
RAIN1,167 (12.5%)
43.0%prior 816
SNOW507 (5.4%)
25250.0%prior 2
CLOUDY/OVERCAST229 (2.5%)
97.4%prior 116
OTHER44 (0.5%)
450.0%prior 8
SLEET/HAIL24 (0.3%)
FOG/SMOKE/HAZE3 (0.0%)
50.0%prior 2
SEVERE CROSS WIND GATE2 (0.0%)
100.0%prior 1

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-04-01 to 2018-04-30 · Weather condition at time of crash

Lighting

DAYLIGHT6,845 (73.0%)
87.6%prior 3,648
DARKNESS, LIGHTED ROAD1,724 (18.4%)
112.8%prior 810
DARKNESS360 (3.8%)
57.9%prior 228
DUSK254 (2.7%)
93.9%prior 131
DAWN197 (2.1%)
203.1%prior 65

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-04-01 to 2018-04-30 · Lighting condition field

Road Surface

DRY7,033 (77.3%)
85.7%prior 3,788
WET1,635 (18.0%)
76.8%prior 925
SNOW OR SLUSH207 (2.3%)
20600.0%prior 1
ICE199 (2.2%)
OTHER20 (0.2%)
122.2%prior 9
SAND, MUD, DIRT2 (0.0%)
-33.3%prior 3

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-04-01 to 2018-04-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 10131 in April 2017 to 19692 in April 2018. The number of pedestrians involved as vehicle types rose from 69 to 274, and bicycles from 51 to 106. Top vehicle makes like Chevrolet, Toyota, and Ford maintained their leading positions, with their involvement counts increasing proportionally to the overall rise in crashes.

Top Vehicle Makes (19,692 vehicles)

1
CHEVROLET2,232 (11.3%)
87.4%prior 1,191
2
TOYOTA MOTOR COMPANY, LTD.2,199 (11.2%)
89.2%prior 1,162
3
FORD1,877 (9.5%)
82.2%prior 1,030
4
NISSAN1,560 (7.9%)
95.0%prior 800
5
HONDA1,393 (7.1%)
121.8%prior 628
6
DODGE893 (4.5%)
93.7%prior 461
7
HYUNDAI768 (3.9%)
81.6%prior 423
8
JEEP709 (3.6%)
102.6%prior 350
9
CHRYSLER422 (2.1%)
81.9%prior 232
10
KIA MOTORS CORP415 (2.1%)
84.4%prior 225

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-04-01 to 2018-04-30 · Vehicle unit records

5,928 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 (21,283 persons with recorded sex)

Male11,297 (53.1%)
98.7%prior 5,685
Female8,337 (39.2%)
91.0%prior 4,364
Non-Binary1,649 (7.7%)
78.3%prior 925

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-04-01 to 2018-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed limit zone increased from 3708 to 7138, accounting for the majority of crashes in both periods. Fatalities in the 30 mph zone rose from 2 in April 2017 to 9 in April 2018, with the fatal rate in this zone increasing from 0.054% to 0.126%. Additionally, 15 mph and 35 mph zones, which had no fatalities in April 2017, each recorded 1 fatal crash in April 2018.

Fatal crashes by zone: 15 mph: 1 of 306 (0.327%) · 30 mph: 9 of 7,138 (0.126%) · 35 mph: 1 of 657 (0.152%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-04-01 to 2018-04-30 · 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: 2018-04-01 through 2018-04-30
  • Report generated: June 1, 2026

Data Coverage

  • Reporting period: 2018-04-01 through 2018-04-30 (30 days)
  • Geographic scope: Chicago, IL
  • Total crash records analyzed: 9,648
  • Total persons involved: 21,596
  • Total vehicles involved: 19,692

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/april-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

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Chicago, IL Year-over-Year Crash Report — April 2018 vs April 2017 | ThatCarHitMe.com