Monthly Traffic Safety Analysis

395 CRASHES IN
WORCESTER, MA
MARCH 2023

All metrics benchmarked againstMarch 2022

In March 2023, there were 395 total crashes in Worcester, a slight decrease from 403 crashes reported in March 2022, representing a 2.0% reduction. Despite the overall decrease in crashes, DUI-related incidents saw a significant increase, doubling from 5 crashes in March 2022 to 10 crashes in March 2023.

395

-2.0%was 403

Total Crash Events

0

Persons Killed

112

36.6%was 82

Persons Injured

85

13.3%was 75

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 62 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash incidents in Worcester decreased slightly by 2.0% year-over-year, from 403 crashes in March 2022 to 395 in March 2023. However, total injuries rose by 36.6%, increasing from 82 injured persons in March 2022 to 112 in March 2023. Fatalities remained at zero for both periods.

85

Hit-and-Run Crashes — March 2023

13.3% vs prior (75)

Hit-and-run incidents increased year-over-year, rising by 13.3% from 75 crashes in March 2022 to 85 crashes in March 2023. Concurrently, the hit-and-run rate, as a proportion of total crashes, also increased from 18.6% in March 2022 to 21.5% in March 2023, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

6

Pedestrians Injured

Prior: 450.0%

1

Cyclists Injured

Prior: 0%

105

Motorists Injured

Prior: 7736.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes showed some shifts year-over-year. The peak day for crashes moved from Thursday in March 2022 (72 crashes) to Friday in March 2023 (72 crashes), with Friday crashes increasing by 35.8% from 53 to 72 incidents. The peak crash hour also shifted from 3 PM (40 crashes) in March 2022 to 5 PM (36 crashes) in March 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero for both March 2022 and March 2023. However, the number of serious injury crashes (Severity A) significantly increased by 450%, from 2 incidents in March 2022 to 11 in March 2023. This also led to an overall increase in total injuries, which rose by 36.6% from 82 to 112 persons injured year-over-year.

Outcome by Severity (Crash Events)

Serious Injury11serious injury crashes2.8%
450.0%prior 2
Minor Injury33minor injury crashes8.4%
-5.7%prior 35
Possible Injury34possible injury crashes8.6%
30.8%prior 26
No Injury255no injury crashes64.6%
-2.7%prior 262

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw notable year-over-year changes in crash counts. Crashes attributed to 'Operating vehicle in an erratic, reckless, careless, negligent or aggressive manner' increased significantly by 550%, from 2 incidents in March 2022 to 13 in March 2023. 'Failed to yield right of way' crashes rose by 36.4%, from 22 to 30, while 'Inattention' crashes increased by 53.8%, from 13 to 20 incidents. Conversely, 'Followed too closely' crashes decreased by 42.9%, from 21 to 12 incidents.

Officer-Reported Primary Contributing Cause

No improper driving132 (33.4%)-5.0%prior 139
Failed to yield right of way30 (7.6%)36.4%prior 22
Inattention20 (5.1%)53.8%prior 13
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner13 (3.3%)
Failure to keep in proper lane or running off road13 (3.3%)-18.8%prior 16
Followed too closely12 (3%)-42.9%prior 21
Distracted8 (2%)
Disregarded traffic signs, signals, road markings7 (1.8%)-36.4%prior 11
Other improper action6 (1.5%)-45.5%prior 11
Physical impairment5 (1.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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 rainy conditions decreased by 42.9%, from 28 in March 2022 to 16 in March 2023, and crashes during snowy conditions decreased by 47.4%, from 19 to 10. Similarly, crashes on icy road surfaces saw a significant 87.5% reduction, from 8 incidents to 1 year-over-year, while crashes on dry road surfaces increased by 6.6%, from 290 to 309.

Weather

Clear231 (60.5%)
3.6%prior 223
Clear/Clear45 (11.8%)
-2.2%prior 46
Cloudy38 (9.9%)
-2.6%prior 39
Rain13 (3.4%)
-50.0%prior 26
Snow9 (2.4%)
-50.0%prior 18
Clear/Cloudy8 (2.1%)
Cloudy/Cloudy8 (2.1%)
Snow/Sleet, hail (freezing rain or drizzle)8 (2.1%)
Cloudy/Rain5 (1.3%)
-16.7%prior 6
Rain/Rain3 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash

Lighting

Daylight276 (72.1%)
0.7%prior 274
Dark - lighted roadway97 (25.3%)
-5.8%prior 103
Dusk5 (1.3%)
-44.4%prior 9
Dark - roadway not lighted3 (0.8%)
-57.1%prior 7
Dawn1 (0.3%)
Other1 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field

Road Surface

Dry309 (80.5%)
6.6%prior 290
Wet47 (12.2%)
-26.6%prior 64
Snow26 (6.8%)
13.0%prior 23
Slush1 (0.3%)
Ice1 (0.3%)
-87.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field

Vehicles & Demographics

The age distribution of persons involved in crashes showed a notable shift, with individuals aged 0-15 decreasing by 32.7% (from 52 to 35) and those aged 16-20 decreasing by 21.3% (from 75 to 59). Conversely, the 26-34 age group saw a 23.7% increase in involvement, rising from 152 to 188 persons. Among vehicle makes, Toyota crashes decreased by 15.6% (from 174 to 147), while Honda involvement increased by 8.6% (from 81 to 88).

Top Vehicle Makes (774 vehicles)

1
TOYOTA147 (19%)
-15.5%prior 174
2
HONDA88 (11.4%)
8.6%prior 81
3
FORD63 (8.1%)
-1.6%prior 64
4
CHEVROLET55 (7.1%)
-14.1%prior 64
5
NISSAN55 (7.1%)
14.6%prior 48
6
JEEP40 (5.2%)
8.1%prior 37
7
SUBARU36 (4.7%)
12.5%prior 32
8
HYUNDAI30 (3.9%)
36.4%prior 22
9
GMC17 (2.2%)
-10.5%prior 19
10
MERCEDES-BENZ17 (2.2%)
88.9%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records

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

Sex Distribution (809 persons with recorded sex)

Male459 (56.7%)
20.5%prior 381
Female350 (43.3%)
6.1%prior 330

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events

Speed Limit Zones

No fatal crashes were recorded in any speed zone for either March 2022 or March 2023. Crashes occurring in 30 mph zones decreased by 12.2%, from 74 incidents in March 2022 to 65 in March 2023. Conversely, crashes in 35 mph zones saw a significant 133.3% increase, rising from 3 to 7 incidents, and crashes in 65 mph zones increased by 25%, from 8 to 10 incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-03-01 through 2023-03-31 (31 days)
  • Geographic scope: WORCESTER, MA
  • Total crash records analyzed: 395
  • Total persons involved: 996
  • Total vehicles involved: 774

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: March 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/worcester/march-2023-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 — March 2023 | ThatCarHitMe.com