Monthly Traffic Safety Analysis

462 CRASHES IN
WORCESTER, MA
MAY 2023

All metrics benchmarked againstMay 2022

WORCESTER experienced a notable increase in total crashes from May 2022 to May 2023, rising from 387 to 462, which represents a 19.38% increase. This period also saw a significant 60% increase in hit-and-run crashes, growing from 70 to 112. Overall, the data indicates an upward trend in crash incidents year-over-year.

462

19.4%was 387

Total Crash Events

1

Persons Killed

146

20.7%was 121

Persons Injured

112

60.0%was 70

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend for crashes in WORCESTER from May 2022 to May 2023 is upward, with total crashes increasing by 75, from 387 to 462. Fatalities remained stable at 1 in both periods, while total injuries rose by 25, from 121 to 146. This reflects a general increase in crash activity year-over-year.

112

Hit-and-Run Crashes — May 2023

60.0% vs prior (70)

Hit-and-run crashes increased substantially from 70 in May 2022 to 112 in May 2023, representing a 60% increase in count. The hit-and-run rate also rose from 18.1% to 24.2% of total crashes. This indicates a clear upward trend in hit-and-run incidents year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

6

Pedestrians Injured

Prior: 2200.0%

3

Cyclists Injured

Prior: 250.0%

137

Motorists Injured

Prior: 11519.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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 Tuesday with 69 crashes in May 2022 to Saturday with 80 crashes in May 2023. Similarly, the peak hour changed from 12p with 35 crashes in May 2022 to 5p with 42 crashes in May 2023. These shifts indicate a change in the timing of peak crash occurrences.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of fatal crashes remained at 1 in both May 2022 and May 2023, though the fatal crash rate slightly decreased from 0.26% to 0.22% due to the increased total crashes. Serious injury crashes (severity A) increased from 7 to 13, while minor injury crashes (severity B) rose from 43 to 51. Overall, total injuries increased from 121 to 146 persons.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.2%
0.0%prior 1
Serious Injury13serious injury crashes2.8%
85.7%prior 7
Minor Injury51minor injury crashes11%
18.6%prior 43
Possible Injury38possible injury crashes8.2%
18.8%prior 32
No Injury279no injury crashes60.4%
15.3%prior 242

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record

Top Contributing Factors

The most frequent contributing factor, 'No improper driving,' increased by 12 crashes, from 135 in May 2022 to 147 in May 2023. 'Failure to keep in proper lane or running off road' saw a significant increase of 7 crashes, rising from 9 to 16. Conversely, 'Failed to yield right of way' decreased by 3 crashes, from 20 to 17, and 'Inattention' decreased by 2 crashes, from 17 to 15.

Officer-Reported Primary Contributing Cause

No improper driving147 (31.8%)8.9%prior 135
Followed too closely25 (5.4%)13.6%prior 22
Failed to yield right of way17 (3.7%)-15.0%prior 20
Failure to keep in proper lane or running off road16 (3.5%)77.8%prior 9
Inattention15 (3.2%)-11.8%prior 17
Disregarded traffic signs, signals, road markings15 (3.2%)15.4%prior 13
Made an improper turn7 (1.5%)
Other improper action7 (1.5%)0.0%prior 7
Exceeded authorized speed limit5 (1.1%)0.0%prior 5
Distracted5 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased by 52, from 252 to 304, consistent with the overall rise in crashes. The count of crashes on 'Wet' road surfaces increased by 21, from 29 to 50, and crashes during 'Rain' increased from 11 to 24. Conversely, crashes during 'Cloudy' conditions decreased by 23, from 40 to 17.

Weather

Clear304 (67.3%)
20.6%prior 252
Clear/Clear67 (14.8%)
19.6%prior 56
Rain24 (5.3%)
118.2%prior 11
Cloudy17 (3.8%)
-57.5%prior 40
Cloudy/Rain11 (2.4%)
22.2%prior 9
Clear/Cloudy6 (1.3%)
Cloudy/Cloudy5 (1.1%)
Unknown/Unknown5 (1.1%)
Rain/Cloudy4 (0.9%)
Rain/Rain4 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash

Lighting

Daylight338 (75.1%)
15.4%prior 293
Dark - lighted roadway89 (19.8%)
34.8%prior 66
Dusk9 (2.0%)
28.6%prior 7
Dark - unknown roadway lighting7 (1.6%)
Dark - roadway not lighted4 (0.9%)
-20.0%prior 5
Dawn3 (0.7%)
-57.1%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field

Road Surface

Dry395 (87.8%)
15.2%prior 343
Wet50 (11.1%)
72.4%prior 29
Reported but invalid3 (0.7%)
Snow1 (0.2%)
Water (standing, moving)1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 772 to 926 year-over-year. Toyota, Honda, and Ford remained the top three vehicle makes involved in crashes, with Toyota seeing an increase of 37 vehicles (from 152 to 189) and Honda an increase of 26 vehicles (from 85 to 111). Notably, the 21-25 age group saw a substantial increase of 54 persons involved in crashes, rising from 94 to 148, while the 65+ age group also increased by 24 persons, from 56 to 80.

Top Vehicle Makes (926 vehicles)

1
TOYOTA189 (20.4%)
24.3%prior 152
2
HONDA111 (12%)
30.6%prior 85
3
FORD95 (10.3%)
31.9%prior 72
4
NISSAN50 (5.4%)
-19.4%prior 62
5
SUBARU44 (4.8%)
46.7%prior 30
6
JEEP42 (4.5%)
50.0%prior 28
7
CHEVROLET40 (4.3%)
-20.0%prior 50
8
HYUNDAI30 (3.2%)
-11.8%prior 34
9
ACURA25 (2.7%)
108.3%prior 12
10
VOLKSWAGEN21 (2.3%)
250.0%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records

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

Sex Distribution (928 persons with recorded sex)

Male501 (54.0%)
17.9%prior 425
Female427 (46.0%)
30.2%prior 328

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events

Speed Limit Zones

The number of crashes occurring in 30 mph speed zones increased from 75 in May 2022 to 109 in May 2023, a rise of 34 crashes. A fatal crash was recorded in a 30 mph zone in May 2023, where none occurred in May 2022. Crashes in 50 mph zones also increased from 28 to 35, though no fatalities were recorded in this zone in either period.

Fatal crashes by zone: 30 mph: 1 of 109 (0.917%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-05-01 through 2023-05-31 (31 days)
  • Geographic scope: WORCESTER, MA
  • Total crash records analyzed: 462
  • Total persons involved: 1,145
  • Total vehicles involved: 926

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: May 2023." Published June 21, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/worcester/may-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 — May 2023 | ThatCarHitMe.com