Yearly Traffic Safety Analysis

219 CRASHES IN
PLAINVILLE, MA
2022

All metrics benchmarked against2021

In Plainville, total vehicle crashes decreased by 6% from 233 incidents in 2021 to 219 in 2022. While overall collisions declined, the number of crashes attributed to exceeding the authorized speed limit increased from 3 to 8 year-over-year. The total number of fatalities remained stable at one death in each period, while reported injuries saw a 10.8% decrease from 65 to 58.

219

-6.0%was 233

Total Crash Events

1

Persons Killed

58

-10.8%was 65

Persons Injured

5

-50.0%was 10

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

The overall trend in traffic collisions showed a modest improvement year-over-year, with total crashes falling by 6% from 233 in 2021 to 219 in 2022. The number of people injured in these incidents also declined by 10.8%, from 65 to 58. Fatalities held steady, with one person killed in a crash in both 2022 and 2021.

5

Hit-and-Run Crashes — 2022

-50.0% vs prior (10)

Hit-and-run incidents decreased significantly between the two periods. The total number of hit-and-run crashes was halved, dropping from 10 in 2021 to 5 in 2022. Correspondingly, the hit-and-run rate, or the percentage of total crashes that were hit-and-runs, fell from 4.3% in 2021 to 2.3% in 2022, indicating a clear downward trend.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Motorists Killed

Prior: 1-100.0%

0

Pedestrians Injured

Prior: 00.0%

58

Motorists Injured

Prior: 64-9.4%

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

Temporal crash patterns shifted between the two periods. In 2022, the peak day for crashes was Thursday, with 42 incidents, a change from 2021 when Monday was the peak day with 45 crashes. The peak hour for collisions also shifted slightly, moving from a tie between 1 p.m. and 3 p.m. in 2021 (24 crashes each) to 12 p.m. in 2022 (25 crashes), though the midday hours remained the most frequent time for incidents in both years.

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

The severity of crashes saw mixed changes year-over-year. While the number of fatal crashes remained unchanged at one incident in both 2021 and 2022, the number of serious injury crashes increased from 2 to 3. Conversely, crashes resulting in minor injuries decreased from 21 to 17, and those with possible injuries fell from 27 to 24. The proportion of crashes with no reported injuries increased from 76.8% in 2021 to 79.0% in 2022.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.5%
0.0%prior 1
Serious Injury3serious injury crashes1.4%
50.0%prior 2
Minor Injury17minor injury crashes7.8%
-19.0%prior 21
Possible Injury24possible injury crashes11%
-11.1%prior 27
No Injury173no injury crashes79%
-3.4%prior 179

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 top three contributing factors to crashes remained consistent across both years, though their counts varied. 'Inattention' was the leading factor in both periods but saw its count decrease by 19% from 73 crashes in 2021 to 59 in 2022. Crashes where 'no improper driving' was noted increased from 41 to 47, and those involving 'failed to yield right of way' rose from 35 to 39. Notably, crashes where 'exceeded authorized speed limit' was a factor increased from 1 in 2021 to 5 in 2022.

Officer-Reported Primary Contributing Cause

Inattention59 (26.9%)-19.2%prior 73
No improper driving47 (21.5%)14.6%prior 41
Failed to yield right of way39 (17.8%)11.4%prior 35
Followed too closely14 (6.4%)7.7%prior 13
Failure to keep in proper lane or running off road8 (3.7%)-38.5%prior 13
Exceeded authorized speed limit5 (2.3%)
Distracted5 (2.3%)-28.6%prior 7
Over-correcting/over-steering4 (1.8%)
Disregarded traffic signs, signals, road markings3 (1.4%)-66.7%prior 9
Fatigued/asleep3 (1.4%)-40.0%prior 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

The conditions under which crashes occurred were largely similar year-over-year. In both 2022 and 2021, the majority of incidents happened in daylight (73.1% and 79.4%, respectively) on dry roads (80.4% and 78.1%) in clear weather (74.9% and 72.5%). There were no significant shifts in the proportions of crashes occurring in adverse lighting, weather, or road surface conditions between the two periods.

Weather

Clear/Clear102 (46.6%)
13.3%prior 90
Clear62 (28.3%)
-21.5%prior 79
Rain13 (5.9%)
0.0%prior 13
Cloudy9 (4.1%)
-35.7%prior 14
Cloudy/Cloudy8 (3.7%)
0.0%prior 8
Rain/Cloudy6 (2.7%)
20.0%prior 5
Cloudy/Rain5 (2.3%)
Snow/Snow3 (1.4%)
-62.5%prior 8
Clear/Cloudy3 (1.4%)
Rain/Rain2 (0.9%)
-60.0%prior 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

Daylight160 (73.1%)
-13.5%prior 185
Dark - lighted roadway28 (12.8%)
-9.7%prior 31
Dark - roadway not lighted12 (5.5%)
9.1%prior 11
Dusk11 (5.0%)
Dawn6 (2.7%)
Dark - unknown roadway lighting2 (0.9%)

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

Road Surface

Dry176 (80.4%)
-3.3%prior 182
Wet35 (16.0%)
-2.8%prior 36
Snow6 (2.7%)
20.0%prior 5
Sand, mud, dirt, oil, gravel2 (0.9%)
-60.0%prior 5

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

Vehicles & Demographics

The top vehicle makes involved in crashes showed high consistency, with Toyota and Ford ranking first and second in both years. In 2022, Honda (34 vehicles) replaced Nissan (26 vehicles) as the third most common make, compared to 2021 when Nissan held the third spot with 37 vehicles. The age distribution of persons involved in crashes shifted, with a notable decrease in the 55-64 age group (from 81 to 55 people) and increases in the 16-20 (from 50 to 69) and 65+ (from 54 to 64) age groups.

Top Vehicle Makes (425 vehicles)

1
TOYOTA70 (16.5%)
4.5%prior 67
2
FORD48 (11.3%)
-12.7%prior 55
3
HONDA34 (8%)
-5.6%prior 36
4
JEEP32 (7.5%)
28.0%prior 25
5
NISSAN26 (6.1%)
-29.7%prior 37
6
HYUNDAI20 (4.7%)
5.3%prior 19
7
CHEVROLET18 (4.2%)
-47.1%prior 34
8
DODGE16 (3.8%)
14.3%prior 14
9
SUBARU14 (3.3%)
40.0%prior 10
10
GMC12 (2.8%)
100.0%prior 6

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

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

Sex Distribution (482 persons with recorded sex)

Male253 (52.5%)
1.6%prior 249
Female229 (47.5%)
0.0%prior 229

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

Analysis of crashes by speed zone indicates a decrease in incidents occurring in zones posted at 40 mph or higher, which fell from 101 crashes in 2021 to 83 in 2022. Crashes in zones 35 mph or lower also saw a slight reduction from 91 to 84 incidents. The single fatal crash in 2022 occurred in a 65 mph zone; a comparison cannot be made for the 2021 fatality as its associated speed zone was not recorded in the data.

Fatal crashes by zone: 65 mph: 1 of 18 (5.556%)

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: PLAINVILLE, MA
  • Total crash records analyzed: 219
  • Total persons involved: 503
  • Total vehicles involved: 425

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). "PLAINVILLE, 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/plainville/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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Plainville, MA Crash Report — 2022 | ThatCarHitMe.com