Monthly Traffic Safety Analysis

435 CRASHES IN
WORCESTER, MA
JANUARY 2022

All metrics benchmarked againstJanuary 2021

In January 2022, WORCESTER, MA experienced 435 crashes, marking a 28.32% increase compared to the 339 crashes recorded in January 2021. A significant shift was the increase in total fatalities from 0 in January 2021 to 1 in January 2022. Additionally, DUI-related crashes decreased from 6 to 0 year-over-year.

435

28.3%was 339

Total Crash Events

1

Persons Killed

103

2.0%was 101

Persons Injured

68

13.3%was 60

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash trends in WORCESTER, MA show an increase year-over-year. Total crashes rose by 96, a 28.32% increase from 339 in January 2021 to 435 in January 2022. This period also saw an increase in total fatalities, from 0 to 1, and a slight increase in total injuries, from 101 to 103.

68

Hit-and-Run Crashes — January 2022

13.3% vs prior (60)

Hit-and-run incidents increased in count from 60 in January 2021 to 68 in January 2022. However, the hit-and-run rate relative to total crashes decreased from 17.7% in January 2021 to 15.6% in January 2022. This indicates that while the absolute number of hit-and-run crashes rose, they constitute a smaller proportion of the overall increase in crashes.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 3-33.3%

1

Cyclists Injured

Prior: 0%

100

Motorists Injured

Prior: 955.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year. In January 2021, the peak crash day was Thursday with 66 incidents, while in January 2022, Wednesday became the peak day with 91 crashes. The peak crash hour also changed, moving from 1 p.m. with 38 crashes in January 2021 to 2 p.m. with 36 crashes in January 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution of crashes saw an increase in fatal incidents, with 1 fatal crash (0.2% of total) in January 2022 compared to 0 fatal crashes in January 2021. Serious injury crashes (severity A) increased from 1 (0.3% of total) to 6 (1.4% of total) year-over-year. Conversely, the proportion of possible injury crashes (severity C) decreased from 12.4% to 9%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.2%
Serious Injury6serious injury crashes1.4%
500.0%prior 1
Minor Injury31minor injury crashes7.1%
3.3%prior 30
Possible Injury39possible injury crashes9%
-7.1%prior 42
No Injury286no injury crashes65.7%
49.0%prior 192

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw notable changes in crash counts year-over-year. Crashes attributed to 'No improper driving' increased by 32 incidents, from 131 to 163, representing a 24.4% count increase. 'Failed to yield right of way' crashes rose by 7, from 17 to 24, a 41.2% count increase. Conversely, 'Failure to keep in proper lane or running off road' decreased by 5 incidents, from 11 to 6, a 45.5% count decrease, and 'Distracted' crashes decreased by 5, from 8 to 3, a 62.5% count decrease.

Officer-Reported Primary Contributing Cause

No improper driving163 (37.5%)24.4%prior 131
Failed to yield right of way24 (5.5%)41.2%prior 17
Inattention20 (4.6%)25.0%prior 16
Disregarded traffic signs, signals, road markings15 (3.4%)36.4%prior 11
Followed too closely14 (3.2%)55.6%prior 9
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway10 (2.3%)100.0%prior 5
Driving too fast for conditions9 (2.1%)12.5%prior 8
Exceeded authorized speed limit7 (1.6%)
Made an improper turn7 (1.6%)16.7%prior 6
Failure to keep in proper lane or running off road6 (1.4%)-45.5%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions, including 'Clear/Clear', increased from 194 in January 2021 to 265 in January 2022. Incidents on 'Dry' road surfaces rose from 213 to 243, while those on 'Wet' surfaces increased from 35 to 60. Notably, crashes on 'Ice' surfaces more than doubled, increasing from 24 to 57 year-over-year.

Weather

Clear219 (51.4%)
30.4%prior 168
Cloudy51 (12.0%)
37.8%prior 37
Clear/Clear46 (10.8%)
76.9%prior 26
Snow27 (6.3%)
-30.8%prior 39
Rain/Sleet, hail (freezing rain or drizzle)9 (2.1%)
Snow/Sleet, hail (freezing rain or drizzle)8 (1.9%)
-20.0%prior 10
Rain8 (1.9%)
33.3%prior 6
Cloudy/Rain6 (1.4%)
Sleet, hail (freezing rain or drizzle)6 (1.4%)
Snow/Snow6 (1.4%)
-14.3%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Weather condition at time of crash

Lighting

Daylight267 (63.0%)
47.5%prior 181
Dark - lighted roadway129 (30.4%)
1.6%prior 127
Dusk11 (2.6%)
10.0%prior 10
Dark - roadway not lighted9 (2.1%)
12.5%prior 8
Dawn5 (1.2%)
0.0%prior 5
Dark - unknown roadway lighting3 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Lighting condition field

Road Surface

Dry243 (57.2%)
14.1%prior 213
Snow62 (14.6%)
19.2%prior 52
Wet60 (14.1%)
71.4%prior 35
Ice57 (13.4%)
137.5%prior 24
Slush2 (0.5%)
-60.0%prior 5
Sand, mud, dirt, oil, gravel1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Road surface condition field

Vehicles & Demographics

The age distribution of persons involved in crashes showed increases across most age groups, with the largest increase in the 35-44 age group, rising from 92 to 146 individuals. The 26-34 age group also saw a significant increase from 147 to 200 individuals. Regarding vehicle makes, Toyota remained the most involved make, increasing from 108 to 156 vehicles, with Honda and Ford also seeing increases in their involvement.

Top Vehicle Makes (830 vehicles)

1
TOYOTA156 (18.8%)
44.4%prior 108
2
HONDA93 (11.2%)
3.3%prior 90
3
FORD75 (9%)
29.3%prior 58
4
CHEVROLET67 (8.1%)
24.1%prior 54
5
NISSAN55 (6.6%)
31.0%prior 42
6
SUBARU43 (5.2%)
95.5%prior 22
7
HYUNDAI38 (4.6%)
26.7%prior 30
8
JEEP29 (3.5%)
7.4%prior 27
9
LEXUS18 (2.2%)
63.6%prior 11
10
DODGE17 (2%)
30.8%prior 13

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Vehicle unit records

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

Sex Distribution (780 persons with recorded sex)

Male447 (57.3%)
32.6%prior 337
Female332 (42.6%)
39.5%prior 238
X / Unspecified1 (0.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph speed zones saw a slight increase from 82 in January 2021 to 86 in January 2022. A more pronounced increase was observed in higher speed zones, with 50 mph zones rising from 18 to 27 crashes and 65 mph zones increasing from 9 to 16 crashes. Fatal crash rates remained at 0% across all reported speed zones in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · 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: 2022-01-01 through 2022-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-01-31 (31 days)
  • Geographic scope: WORCESTER, MA
  • Total crash records analyzed: 435
  • Total persons involved: 985
  • Total vehicles involved: 830

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: January 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/worcester/january-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

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