Monthly Traffic Safety Analysis

366 CRASHES IN
WORCESTER, MA
FEBRUARY 2022

All metrics benchmarked againstFebruary 2021

Total crashes in Worcester decreased by 3.2% year-over-year, from 378 in February 2021 to 366 in February 2022. The most notable shift was the increase in total fatalities from 0 in the prior period to 1 in the current period.

366

-3.2%was 378

Total Crash Events

1

Persons Killed

85

1.2%was 84

Persons Injured

87

Hit-and-Run Crashes

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. 65 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes decreased by 3.2% year-over-year, with total crashes falling from 378 in February 2021 to 366 in February 2022. This indicates a slight downward trend in the number of crash incidents.

87

Hit-and-Run Crashes — February 2022

0.0% vs prior (87)

The number of hit-and-run crashes remained constant at 87 in both periods. However, the hit-and-run rate slightly increased from 23% in the prior period to 23.8% in the current period, reflecting a decrease in overall total crashes.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Motorists Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 30.0%

82

Motorists Injured

Prior: 811.2%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Tuesday remained the peak day for crashes in both periods, recording 67 crashes in the prior period and 59 in the current period. The peak hour shifted from 2 p.m. with 39 crashes in the prior period to 3 p.m. with 32 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes increased from 0 in the prior period to 1 in the current period, raising the fatal crash rate from 0% to 0.27%. Serious injury crashes decreased from 5 to 2, while minor injury crashes slightly increased from 31 to 32. Overall total injuries saw a minor increase from 84 to 85.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
Serious Injury2serious injury crashes0.5%
-60.0%prior 5
Minor Injury32minor injury crashes8.7%
3.2%prior 31
Possible Injury26possible injury crashes7.1%
-25.7%prior 35
No Injury240no injury crashes65.6%
11.1%prior 216

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Most severe injury per crash record

Top Contributing Factors

The factor 'No improper driving' decreased by 22 crashes, from 155 to 133. 'Followed too closely' increased by 15 crashes, from 13 to 28, moving it to the second most frequent factor. 'Failed to yield right of way' and 'Inattention' both decreased by 5 crashes, from 25 to 20 and 18 to 13 respectively.

Officer-Reported Primary Contributing Cause

No improper driving133 (36.3%)-14.2%prior 155
Followed too closely28 (7.7%)115.4%prior 13
Failed to yield right of way20 (5.5%)-20.0%prior 25
Inattention13 (3.6%)-27.8%prior 18
Disregarded traffic signs, signals, road markings12 (3.3%)-29.4%prior 17
Driving too fast for conditions12 (3.3%)-7.7%prior 13
Other improper action9 (2.5%)28.6%prior 7
Failure to keep in proper lane or running off road8 (2.2%)33.3%prior 6
Distracted6 (1.6%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather increased from 154 to 194, while those in 'Snow' weather decreased from 52 to 18. Similarly, crashes on 'Dry' road surfaces increased from 172 to 204, but those on 'Snow' surfaces decreased from 77 to 41. Crashes occurring in 'Daylight' decreased from 222 to 207.

Weather

Clear194 (55.7%)
26.0%prior 154
Clear/Clear38 (10.9%)
22.6%prior 31
Cloudy37 (10.6%)
-17.8%prior 45
Snow18 (5.2%)
-65.4%prior 52
Cloudy/Rain11 (3.2%)
Rain10 (2.9%)
-33.3%prior 15
Snow/Sleet, hail (freezing rain or drizzle)6 (1.7%)
20.0%prior 5
Cloudy/Snow5 (1.4%)
-68.8%prior 16
Clear/Cloudy5 (1.4%)
Sleet, hail (freezing rain or drizzle)4 (1.1%)
-66.7%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Weather condition at time of crash

Lighting

Daylight207 (58.5%)
-6.8%prior 222
Dark - lighted roadway118 (33.3%)
-9.2%prior 130
Dark - roadway not lighted12 (3.4%)
Dusk11 (3.1%)
22.2%prior 9
Dark - unknown roadway lighting4 (1.1%)
Dawn2 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Lighting condition field

Road Surface

Dry204 (58.8%)
18.6%prior 172
Wet75 (21.6%)
7.1%prior 70
Snow41 (11.8%)
-46.8%prior 77
Ice22 (6.3%)
-46.3%prior 41
Slush5 (1.4%)
-16.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Road surface condition field

Vehicles & Demographics

Toyota remained the most common vehicle make involved, though its count decreased from 133 to 127. Honda moved from the third to the second most common make, with its count increasing from 61 to 80. The 0-15 age group saw an increase in persons involved from 22 to 39, and the 16-20 age group increased from 46 to 79.

Top Vehicle Makes (724 vehicles)

1
TOYOTA127 (17.5%)
-4.5%prior 133
2
HONDA80 (11%)
31.1%prior 61
3
FORD72 (9.9%)
-1.4%prior 73
4
NISSAN53 (7.3%)
8.2%prior 49
5
CHEVROLET46 (6.4%)
12.2%prior 41
6
SUBARU31 (4.3%)
19.2%prior 26
7
JEEP23 (3.2%)
-32.4%prior 34
8
HYUNDAI20 (2.8%)
-13.0%prior 23
9
DODGE18 (2.5%)
-5.3%prior 19
10
GMC18 (2.5%)
-30.8%prior 26

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Vehicle unit records

186 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (674 persons with recorded sex)

Male393 (58.3%)
8.0%prior 364
Female281 (41.7%)
14.7%prior 245

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased from 102 to 65, and this zone recorded 1 fatal crash in the current period compared to 0 in the prior period. Crashes in the 50 mph speed zone increased from 25 to 47. The 65 mph speed zone maintained 10 crashes in both periods.

Fatal crashes by zone: 30 mph: 1 of 65 (1.538%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Posted speed limit at crash location

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly 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: Arcgis_yearly 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: 2022-02-01 through 2022-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-02-01 through 2022-02-28 (28 days)
  • Geographic scope: WORCESTER, MA
  • Total crash records analyzed: 366
  • Total persons involved: 892
  • Total vehicles involved: 724

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). "WORCESTER, MA Crash Intelligence Report: February 2022." Published June 21, 2026. Reporting period: 2022-02-01 to 2022-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/worcester/february-2022-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

ThatCarHitMe.com · An Injuria.ai Company

Worcester, MA Crash Report — February 2022 | ThatCarHitMe.com