Monthly Traffic Safety Analysis

10,022 CRASHES IN
CHICAGO, IL
OCTOBER 2017

All metrics benchmarked againstOctober 2016

Total crashes in October 2017 reached 10022, marking a substantial 100.64% increase from the 4995 crashes reported in October 2016. This significant rise in overall crash volume represents the most notable year-over-year shift. Fatalities also increased by 66.67%, from 3 to 5, while injuries surged by 329.64%, from 479 to 2058.

10,022

100.6%was 4,995

Total Crash Events

5

66.7%was 3

Persons Killed

2,058

329.6%was 479

Persons Injured

2,484

96.4%was 1,265

Hit-and-Run Crashes

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 25 crashes with unreported severity are not shown in the severity breakdown.

Source: Chicago Traffic Crashes · Socrata Open Data · 2017-10-01 to 2017-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a sharp increase in crash activity year-over-year. Total crashes more than doubled, rising from 4995 in October 2016 to 10022 in October 2017, representing a 100.64% increase. Both fatalities and injuries also saw significant increases during this period, indicating a worsening safety trend.

2,484

Hit-and-Run Crashes — October 2017

96.4% vs prior (1,265)

The number of hit-and-run crashes increased from 1265 in October 2016 to 2484 in October 2017. However, the overall hit-and-run rate slightly decreased from 25.3% of total crashes in the prior period to 24.8% in the current period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

5

Motorists Killed

Prior: 366.7%

0

Other Killed

Prior: 00.0%

304

Pedestrians Injured

Prior: 56442.9%

160

Cyclists Injured

Prior: 32400.0%

1,593

Motorists Injured

Prior: 391307.4%

1

Other Injured

Prior: 0%

Source: Chicago Traffic Crashes · Socrata Open Data · 2017-10-01 to 2017-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Saturday in October 2016 (782 crashes) to Tuesday in October 2017 (1804 crashes). Despite this, the peak hour for crashes remained consistent at 3 p.m. in both periods, with the number of crashes at this hour increasing from 406 to 776.

Source: Chicago Traffic Crashes · Socrata Open Data · 2017-10-01 to 2017-10-31 · Crash date field aggregated by weekday

Source: Chicago Traffic Crashes · Socrata Open Data · 2017-10-01 to 2017-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The fatal crash rate decreased from 0.06% in October 2016 to 0.04% in October 2017, despite an increase in the absolute number of fatal crashes from 3 to 4. The proportion of crashes resulting in any injury (Serious, Minor, or Possible) significantly increased from 7% to 15.3% of total crashes year-over-year.

Severity is per crash event (most severe injury). 4 fatal crash events resulted in 5 persons killed.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0%
33.3%prior 3
Serious Injury200serious injury crashes2%
365.1%prior 43
Minor Injury839minor injury crashes8.4%
393.5%prior 170
Possible Injury494possible injury crashes4.9%
260.6%prior 137
No Injury8,460no injury crashes84.4%
82.6%prior 4,634

Source: Chicago Traffic Crashes · Socrata Open Data · 2017-10-01 to 2017-10-31 · KABCO injury classification scale

Severity Distribution

Source: Chicago Traffic Crashes · Socrata Open Data · 2017-10-01 to 2017-10-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors saw substantial increases in count, with 'FAILING TO YIELD RIGHT-OF-WAY' rising by 806 crashes (159.29%) from 506 to 1312, becoming the top factor. 'FOLLOWING TOO CLOSELY' also increased by 534 crashes (87.83%), from 608 to 1142, moving to the second position. 'IMPROPER OVERTAKING/PASSING' increased by 163 crashes (53.1%), from 307 to 470.

Officer-Reported Primary Contributing Cause

FAILING TO YIELD RIGHT-OF-WAY1,312 (13.1%)159.3%prior 506
FOLLOWING TOO CLOSELY1,142 (11.4%)87.8%prior 608
IMPROPER OVERTAKING/PASSING470 (4.7%)53.1%prior 307
IMPROPER LANE USAGE430 (4.3%)108.7%prior 206
FAILING TO REDUCE SPEED TO AVOID CRASH422 (4.2%)205.8%prior 138
IMPROPER BACKING400 (4%)66.0%prior 241
IMPROPER TURNING/NO SIGNAL324 (3.2%)100.0%prior 162
DRIVING SKILLS/KNOWLEDGE/EXPERIENCE307 (3.1%)125.7%prior 136
WEATHER206 (2.1%)442.1%prior 38
DISREGARDING TRAFFIC SIGNALS165 (1.6%)266.7%prior 45

Source: Chicago Traffic Crashes · Socrata Open Data · 2017-10-01 to 2017-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in rainy weather conditions notably increased from 11.75% in October 2016 to 22.73% in October 2017. Similarly, crashes on wet road surfaces saw a significant proportional rise, from 14.17% to 25.33% year-over-year. Daylight conditions continued to account for the majority of crashes in both periods.

Weather

CLEAR7,078 (72.5%)
76.7%prior 4,006
RAIN2,278 (23.3%)
288.1%prior 587
CLOUDY/OVERCAST380 (3.9%)
134.6%prior 162
OTHER14 (0.1%)
75.0%prior 8
SNOW6 (0.1%)
200.0%prior 2
FOG/SMOKE/HAZE5 (0.1%)
-28.6%prior 7
SEVERE CROSS WIND GATE1 (0.0%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2017-10-01 to 2017-10-31 · Weather condition at time of crash

Lighting

DAYLIGHT6,237 (63.9%)
87.7%prior 3,322
DARKNESS, LIGHTED ROAD2,336 (23.9%)
173.5%prior 854
DARKNESS588 (6.0%)
92.8%prior 305
DUSK400 (4.1%)
95.1%prior 205
DAWN197 (2.0%)
65.5%prior 119

Source: Chicago Traffic Crashes · Socrata Open Data · 2017-10-01 to 2017-10-31 · Lighting condition field

Road Surface

DRY7,015 (73.2%)
77.6%prior 3,949
WET2,539 (26.5%)
258.6%prior 708
OTHER17 (0.2%)
54.5%prior 11
SAND, MUD, DIRT7 (0.1%)
250.0%prior 2
SNOW OR SLUSH3 (0.0%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2017-10-01 to 2017-10-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes—Chevrolet, Toyota, and Ford—remained consistent across both periods, all experiencing increased counts in line with the overall rise in crashes. The age distribution of persons involved in crashes showed the 26-34 age group consistently having the highest representation, with their proportional involvement remaining relatively stable despite increased raw numbers.

Top Vehicle Makes (20,458 vehicles)

1
CHEVROLET2,287 (11.2%)
86.4%prior 1,227
2
TOYOTA MOTOR COMPANY, LTD.2,222 (10.9%)
89.9%prior 1,170
3
FORD1,991 (9.7%)
104.4%prior 974
4
NISSAN1,669 (8.2%)
110.2%prior 794
5
HONDA1,449 (7.1%)
109.4%prior 692
6
DODGE868 (4.2%)
96.4%prior 442
7
HYUNDAI760 (3.7%)
101.6%prior 377
8
JEEP706 (3.5%)
101.1%prior 351
9
CHRYSLER455 (2.2%)
128.6%prior 199
10
KIA MOTORS CORP437 (2.1%)
124.1%prior 195

Source: Chicago Traffic Crashes · Socrata Open Data · 2017-10-01 to 2017-10-31 · Vehicle unit records

6,264 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 (22,080 persons with recorded sex)

Male11,679 (52.9%)
114.0%prior 5,457
Female8,806 (39.9%)
104.1%prior 4,314
Non-Binary1,595 (7.2%)
69.7%prior 940

Source: Chicago Traffic Crashes · Socrata Open Data · 2017-10-01 to 2017-10-31 · Person-level records linked to crash events

Speed Limit Zones

The 30 mph speed limit zone continued to account for the largest share of crashes, increasing from 3784 to 7569 crashes year-over-year. The fatal crash rate within the 30 mph zone remained unchanged at 0.053% in both periods. The 35 mph zone saw its fatal crash rate decrease from 0.369% to 0%.

Fatal crashes by zone: 30 mph: 4 of 7,569 (0.053%)

Source: Chicago Traffic Crashes · Socrata Open Data · 2017-10-01 to 2017-10-31 · 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: 2017-10-01 through 2017-10-31
  • Report generated: June 1, 2026

Data Coverage

  • Reporting period: 2017-10-01 through 2017-10-31 (31 days)
  • Geographic scope: Chicago, IL
  • Total crash records analyzed: 10,022
  • Total persons involved: 22,462
  • Total vehicles involved: 20,458

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-2017-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 — October 2017 vs October 2016 | ThatCarHitMe.com