Yearly Traffic Safety Analysis

118,952 CRASHES IN
CHICAGO, IL
2018

All metrics benchmarked against2017

In 2018, Chicago recorded 118,952 total traffic crashes, a 42.0% increase from the 83,786 crashes reported in 2017. This period also saw a significant rise in harmful outcomes, with total fatalities increasing by 47.7% from 88 to 130 and total injuries climbing by 72.2% from 13,031 to 22,442. The most notable year-over-year shift was the substantial increase in the overall volume of crashes and the associated rise in injuries.

118,952

42.0%was 83,786

Total Crash Events

130

47.7%was 88

Persons Killed

22,442

72.2%was 13,031

Persons Injured

31,590

42.6%was 22,160

Hit-and-Run Crashes

Note: "Persons Killed" (130) counts individual fatalities across all crash events. "Fatal" in the severity table below (114) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 224 crashes with unreported severity are not shown in the severity breakdown.

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data from Chicago indicates a sharply rising trend in traffic incidents year-over-year. Total crashes increased by 42.0% from 83,786 in 2017 to 118,952 in 2018. This upward trend was also reflected in crash outcomes, with a 47.7% increase in fatalities and a 72.2% increase in injuries during the same period.

31,590

Hit-and-Run Crashes — 2018

42.6% vs prior (22,160)

The number of hit-and-run crashes increased significantly, rising by 42.6% from 22,160 in 2017 to 31,590 in 2018. However, the hit-and-run rate as a percentage of total crashes remained relatively stable. The rate increased slightly from 26.4% in 2017 to 26.6% in 2018, indicating that the growth in hit-and-run incidents was proportional to the overall increase in total crashes.

Vulnerable Road User Casualties

31

Pedestrians Killed

Prior: 1693.8%

5

Cyclists Killed

Prior: 425.0%

91

Motorists Killed

Prior: 6833.8%

3

Other Killed

Prior: 0%

3,000

Pedestrians Injured

Prior: 1,68578.0%

1,322

Cyclists Injured

Prior: 85554.6%

18,112

Motorists Injured

Prior: 10,48472.8%

8

Other Injured

Prior: 714.3%

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained consistent between 2017 and 2018, despite a significant increase in overall volume. Friday continued to be the peak day for crashes in both years, with incidents rising from 13,769 to 19,031. Similarly, the 4 p.m. hour remained the peak time for collisions, increasing from 6,485 crashes in 2017 to 8,933 in 2018.

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-12-31 · Crash date field aggregated by weekday

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the rate of fatal crashes remained stable at 0.1% of all incidents in both 2017 and 2018, the proportion of crashes resulting in injuries increased. In 2018, 13.8% of crashes involved an injury (Serious, Minor, or Possible), up from 11.4% in 2017. Correspondingly, the share of crashes resulting in 'No Injury' decreased from 88.3% in 2017 to 85.9% in 2018.

Severity is per crash event (most severe injury). 114 fatal crash events resulted in 130 persons killed.

Outcome by Severity (Crash Events)

Fatal114fatal crashes0.1%
46.2%prior 78
Serious Injury2,141serious injury crashes1.8%
70.9%prior 1,253
Minor Injury9,335minor injury crashes7.8%
85.2%prior 5,041
Possible Injury4,996possible injury crashes4.2%
52.8%prior 3,270
No Injury102,142no injury crashes85.9%
38.0%prior 73,993

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-12-31 · KABCO injury classification scale

Severity Distribution

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors saw a shift in ranking between the two periods. In 2018, 'Failing to Yield Right-of-Way' became the top factor with 14,089 crashes, a 43.6% increase in count from 9,810 in 2017 when it was the second-ranked cause. 'Following Too Closely,' the top factor in 2017 with 9,955 crashes, dropped to second place in 2018 with 12,674 crashes, representing a 27.3% increase in count. While the counts for both factors rose, the share of total crashes attributed to 'Following Too Closely' decreased from a 11.9% share in 2017 to a 10.7% share in 2018.

Officer-Reported Primary Contributing Cause

FAILING TO YIELD RIGHT-OF-WAY14,089 (11.8%)43.6%prior 9,810
FOLLOWING TOO CLOSELY12,674 (10.7%)27.3%prior 9,955
IMPROPER OVERTAKING/PASSING5,784 (4.9%)46.6%prior 3,945
IMPROPER BACKING5,309 (4.5%)42.5%prior 3,725
FAILING TO REDUCE SPEED TO AVOID CRASH5,075 (4.3%)60.9%prior 3,155
IMPROPER LANE USAGE4,996 (4.2%)45.9%prior 3,425
IMPROPER TURNING/NO SIGNAL4,194 (3.5%)59.2%prior 2,635
DRIVING SKILLS/KNOWLEDGE/EXPERIENCE3,636 (3.1%)43.9%prior 2,527
DISREGARDING TRAFFIC SIGNALS2,248 (1.9%)80.3%prior 1,247
WEATHER2,005 (1.7%)61.8%prior 1,239

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both years occurred in clear weather and daylight, but there were shifts in the proportions of crashes under adverse conditions. The share of crashes happening on dry road surfaces decreased from 77.8% in 2017 to 74.5% in 2018. Concurrently, the proportion of crashes occurring in snow conditions increased from 2.4% of all crashes in 2017 to 3.9% in 2018.

Weather

CLEAR94,008 (82.3%)
38.9%prior 67,663
RAIN10,744 (9.4%)
29.4%prior 8,302
SNOW4,621 (4.0%)
129.8%prior 2,011
CLOUDY/OVERCAST3,853 (3.4%)
66.8%prior 2,310
OTHER418 (0.4%)
94.4%prior 215
FOG/SMOKE/HAZE378 (0.3%)
270.6%prior 102
SLEET/HAIL190 (0.2%)
140.5%prior 79
SEVERE CROSS WIND GATE11 (0.0%)
-38.9%prior 18

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-12-31 · Weather condition at time of crash

Lighting

DAYLIGHT78,162 (67.9%)
42.3%prior 54,929
DARKNESS, LIGHTED ROAD25,250 (21.9%)
43.3%prior 17,625
DARKNESS5,842 (5.1%)
29.0%prior 4,528
DUSK3,602 (3.1%)
36.0%prior 2,649
DAWN2,182 (1.9%)
58.0%prior 1,381

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-12-31 · Lighting condition field

Road Surface

DRY88,589 (79.4%)
35.8%prior 65,216
WET17,443 (15.6%)
56.9%prior 11,116
SNOW OR SLUSH4,224 (3.8%)
116.2%prior 1,954
ICE918 (0.8%)
86.2%prior 493
OTHER346 (0.3%)
114.9%prior 161
SAND, MUD, DIRT71 (0.1%)
44.9%prior 49

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes—Chevrolet, Toyota, and Ford—remained consistent in ranking from 2017 to 2018, with the number of involvements for each make increasing substantially. The demographic profile of persons involved in crashes also showed stability, with the 26-34 age group representing the largest cohort in both years. This group's share of total persons involved remained steady, accounting for 15.8% in 2017 and 16.2% in 2018.

Top Vehicle Makes (241,887 vehicles)

1
CHEVROLET27,291 (11.3%)
38.6%prior 19,697
2
TOYOTA MOTOR COMPANY, LTD.26,509 (11%)
39.0%prior 19,075
3
FORD23,716 (9.8%)
44.1%prior 16,461
4
NISSAN19,503 (8.1%)
41.0%prior 13,830
5
HONDA17,358 (7.2%)
47.9%prior 11,740
6
DODGE10,526 (4.4%)
37.3%prior 7,667
7
HYUNDAI9,643 (4%)
43.7%prior 6,712
8
JEEP8,886 (3.7%)
50.8%prior 5,894
9
KIA MOTORS CORP5,271 (2.2%)
51.0%prior 3,491
10
CHRYSLER4,838 (2%)
28.6%prior 3,763

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records

74,837 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 (262,111 persons with recorded sex)

Male140,117 (53.5%)
44.6%prior 96,911
Female101,266 (38.6%)
42.0%prior 71,290
Non-Binary20,728 (7.9%)
39.7%prior 14,839

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-12-31 · Person-level records linked to crash events

Speed Limit Zones

The 30 mph speed zone was the location for the vast majority of crashes in both periods, with incidents in this zone increasing from 62,127 in 2017 to 88,081 in 2018. The rate of fatal crashes within the 30 mph zone saw a slight increase from 0.090% to 0.099% year-over-year. In contrast, while the number of crashes in the 35 mph zone also rose, the fatal crash rate within that zone decreased from 0.193% in 2017 to 0.147% in 2018.

Fatal crashes by zone: 15 mph: 2 of 3,813 (0.052%) · 20 mph: 2 of 4,542 (0.044%) · 25 mph: 7 of 7,164 (0.098%) · 30 mph: 87 of 88,081 (0.099%) · 35 mph: 12 of 8,163 (0.147%) · 40 mph: 1 of 1,099 (0.091%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2018-01-01 to 2018-12-31 · 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: 2018-01-01 through 2018-12-31
  • Report generated: June 1, 2026

Data Coverage

  • Reporting period: 2018-01-01 through 2018-12-31 (365 days)
  • Geographic scope: Chicago, IL
  • Total crash records analyzed: 118,952
  • Total persons involved: 265,716
  • Total vehicles involved: 241,887

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/2018-annual-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 — 2018 vs 2017 | ThatCarHitMe.com