Yearly Traffic Safety Analysis

8 CRASHES IN
ROYALSTON, MA
2022

All metrics benchmarked against2021

In 2022, Royalston recorded 8 total crashes, representing a 166.7% increase from the 3 crashes reported in 2021. The most significant change year-over-year was the occurrence of a fatal crash in 2022, which resulted in one death; no fatal crashes were recorded in the prior year. Total injuries also doubled from one to two.

8

166.7%was 3

Total Crash Events

1

Persons Killed

2

100.0%was 1

Persons Injured

1

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety metrics in Royalston worsened from 2021 to 2022. The total number of crashes increased from 3 to 8, and the number of people injured rose from 1 to 2. Most notably, the city experienced one fatality in 2022, compared to zero in the previous year.

1

Hit-and-Run Crashes — 2022

12.5% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

2

Motorists Injured

Prior: 1100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The daily pattern of crashes shifted between the two periods. In 2021, the peak day was Wednesday with 2 incidents. In 2022, crashes were more evenly spread across the week, with Sunday, Tuesday, Wednesday, and Thursday each recording 2 crashes. Hourly data was sparse in both years, with no distinct peak hour emerging in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased significantly in 2022. A fatal crash occurred, accounting for 12.5% of all incidents, whereas no fatal crashes were recorded in 2021. While the absolute number of minor injury crashes remained constant at one, its proportion of total crashes fell from 33.3% in 2021 to 12.5% in 2022 due to the overall increase in crash volume. The share of non-injury crashes was similar, at 66.7% in 2021 and 62.5% in 2022.

Outcome by Severity (Crash Events)

Fatal1fatal crashes12.5%
Minor Injury1minor injury crashes12.5%
0.0%prior 1
No Injury5no injury crashes62.5%
150.0%prior 2

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes changed between the two years. In 2022, 'Driving too fast for conditions' was the most common factor, cited in 3 crashes; this factor was not recorded in 2021. In contrast, 'Failure to keep in proper lane or running off road' was a factor in one crash in 2021 but did not appear in the 2022 data. The count of crashes attributed to 'No improper driving' increased from 1 in 2021 to 2 in 2022.

Officer-Reported Primary Contributing Cause

Driving too fast for conditions3 (37.5%)
No improper driving2 (25%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A comparison of crash conditions shows a notable increase in incidents occurring in darkness. In 2022, 50% of crashes (4 incidents) happened on unlit dark roadways, a rise from 2021 where one such crash (33.3% of the total) was recorded. The number of crashes in daylight also increased from one to four. Comparative data for weather and road surface conditions was not available for the 2021 period, precluding a year-over-year analysis for those specific factors.

Weather

Clear5 (62.5%)
Cloudy2 (25.0%)
Fog, smog, smoke1 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Dark - roadway not lighted4 (50.0%)
Daylight4 (50.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry4 (50.0%)
Sand, mud, dirt, oil, gravel2 (25.0%)
Snow2 (25.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (8 vehicles)

1
CHEVROLET2 (25%)
2
HONDA2 (25%)
3
SUBARU2 (25%)
4
HYUNDAI1 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

Sex Distribution (9 persons with recorded sex)

Male7 (77.8%)
Female2 (22.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes by speed zone shifted toward the 35 mph zone in 2022. Crashes in this zone increased from 1 in 2021 to 6 in 2022, and this zone also contained the year's single fatal crash. Crashes in 30 mph zones increased from one to two. Conversely, one crash occurred in a 45 mph zone in 2021, but no crashes were recorded in that speed zone in 2022.

Fatal crashes by zone: 35 mph: 1 of 6 (16.667%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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 2022-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: ROYALSTON, MA
  • Total crash records analyzed: 8
  • Total persons involved: 10
  • Total vehicles involved: 8

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). "ROYALSTON, MA Crash Intelligence Report: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/royalston/2022-annual-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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Royalston, MA Crash Report — 2022 | ThatCarHitMe.com