Yearly Traffic Safety Analysis

179 CRASHES IN
MENDON, MA
2022

All metrics benchmarked against2021

In 2022, Mendon recorded 179 total traffic crashes, a 4.8% decrease from the 188 crashes reported in 2021. While overall crashes and injuries declined, the number of fatalities rose from one to two. The most significant year-over-year shift was the number of crashes involving a driver suspected of being under the influence of alcohol, which increased from 2 in 2021 to 6 in 2022.

179

-4.8%was 188

Total Crash Events

2

100.0%was 1

Persons Killed

57

-9.5%was 63

Persons Injured

12

71.4%was 7

Hit-and-Run Crashes

Note: "Persons Killed" (2) 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. 2 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 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Mendon show a slight decrease year-over-year. Total crashes fell by 4.8%, from 188 in 2021 to 179 in 2022, and the number of people injured decreased by 9.5% from 63 to 57. However, the number of fatalities doubled from one person in 2021 to two in 2022.

12

Hit-and-Run Crashes — 2022

71.4% vs prior (7)

Hit-and-run crashes increased significantly in both count and rate. The number of hit-and-run incidents rose from 7 in 2021 to 12 in 2022, a 71.4% increase. The hit-and-run rate, representing the share of total crashes that were hit-and-runs, also increased from 3.7% in 2021 to 6.7% in 2022.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 1100.0%

57

Motorists Injured

Prior: 62-8.1%

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 timing of crashes shifted between the two periods. In 2022, the peak day for crashes was Sunday with 36 incidents, a change from 2021 when Wednesday was the peak day with 32 incidents. The peak hour also shifted later in the day, from 2 p.m. (21 crashes) in 2021 to 4 p.m. (23 crashes) in 2022.

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 showed a mixed trend year-over-year. While the number of fatal crashes remained unchanged at one, the number of people killed doubled from one to two, leading to a slight increase in the fatal crash rate from 0.53% to 0.56%. The proportion of crashes involving any level of injury (Serious, Minor, or Possible) decreased from 27.1% (51 crashes) in 2021 to 22.3% (40 crashes) in 2022, while the share of no-injury crashes grew from 70.7% to 76.0%.

Severity is per crash event (most severe injury). 1 fatal crash events resulted in 2 persons killed.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.6%
0.0%prior 1
Serious Injury5serious injury crashes2.8%
-16.7%prior 6
Minor Injury21minor injury crashes11.7%
-30.0%prior 30
Possible Injury14possible injury crashes7.8%
-6.7%prior 15
No Injury136no injury crashes76%
2.3%prior 133

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 ranking of top contributing factors changed between 2021 and 2022. The count of crashes attributed to 'No improper driving' more than doubled, rising from 22 to 51, making it the top factor in 2022. Conversely, 'Followed too closely,' the top factor in 2021 with 36 crashes, saw its count decrease by 16.7% to 30 incidents in 2022. The count for 'Failed to yield right of way' held steady at 33 crashes in both years.

Officer-Reported Primary Contributing Cause

No improper driving51 (28.5%)131.8%prior 22
Failed to yield right of way33 (18.4%)0.0%prior 33
Followed too closely30 (16.8%)-16.7%prior 36
Failure to keep in proper lane or running off road16 (8.9%)77.8%prior 9
Disregarded traffic signs, signals, road markings11 (6.1%)
Driving too fast for conditions7 (3.9%)-12.5%prior 8
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (2.2%)-55.6%prior 9
Inattention3 (1.7%)-82.4%prior 17
Made an improper turn3 (1.7%)
Exceeded authorized speed limit3 (1.7%)-70.0%prior 10

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

There was a notable shift in lighting conditions for crashes year-over-year. The proportion of crashes occurring in daylight decreased from 74.5% (140 incidents) in 2021 to 60.9% (109 incidents) in 2022. Correspondingly, the share of crashes in dark conditions (lighted, not lighted, or unknown) increased from 21.3% in 2021 to 32.4% in 2022. The proportion of crashes on adverse road surfaces like wet, snow, or ice saw a smaller increase, from 20.2% in 2021 to 25.1% in 2022.

Weather

Clear113 (63.1%)
-6.6%prior 121
Cloudy14 (7.8%)
-46.2%prior 26
Clear/Clear9 (5.0%)
80.0%prior 5
Snow7 (3.9%)
-41.7%prior 12
Rain7 (3.9%)
-12.5%prior 8
Snow/Blowing sand, snow6 (3.4%)
Cloudy/Rain6 (3.4%)
20.0%prior 5
Sleet, hail (freezing rain or drizzle)3 (1.7%)
Rain/Cloudy3 (1.7%)
Snow/Sleet, hail (freezing rain or drizzle)2 (1.1%)

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

Lighting

Daylight109 (60.9%)
-22.1%prior 140
Dark - lighted roadway40 (22.3%)
53.8%prior 26
Dark - roadway not lighted16 (8.9%)
60.0%prior 10
Dusk7 (3.9%)
Dawn5 (2.8%)
Dark - unknown roadway lighting2 (1.1%)

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

Road Surface

Dry134 (74.9%)
-10.7%prior 150
Wet28 (15.6%)
7.7%prior 26
Snow9 (5.0%)
0.0%prior 9
Ice7 (3.9%)
Slush1 (0.6%)

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

Vehicles & Demographics

The makes of vehicles most frequently involved in crashes shifted between periods. In 2021, Ford was the most common make with 50 vehicles, followed by Toyota (47) and Chevrolet (36). In 2022, Chevrolet became the top make with 39 vehicles, followed by Toyota (38) and Honda (35), while Ford's involvement dropped to 30 vehicles. The share of persons aged 65+ involved in crashes also decreased, from 11.8% of all persons in 2021 to 8.6% in 2022.

Top Vehicle Makes (307 vehicles)

1
CHEVROLET39 (12.7%)
8.3%prior 36
2
TOYOTA38 (12.4%)
-19.1%prior 47
3
HONDA35 (11.4%)
66.7%prior 21
4
FORD30 (9.8%)
-40.0%prior 50
5
NISSAN23 (7.5%)
4.5%prior 22
6
JEEP23 (7.5%)
35.3%prior 17
7
SUBARU19 (6.2%)
90.0%prior 10
8
DODGE9 (2.9%)
-30.8%prior 13
9
KIA MOTORS CORP6 (2%)
10
MAZDA6 (2%)

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

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

Sex Distribution (392 persons with recorded sex)

Male224 (57.1%)
6.2%prior 211
Female165 (42.1%)
-14.1%prior 192
R3 (0.8%)

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 across different speed zones changed year-over-year. Crashes in 35 mph zones decreased from 45 in 2021 to 31 in 2022. In contrast, crashes in higher speed zones increased, with incidents in 40 mph zones rising from 33 to 41 and those in 45 mph zones increasing from 15 to 23. The single fatal crash in 2021 occurred in a 30 mph zone, while the single fatal crash in 2022 was in a 45 mph zone.

Fatal crashes by zone: 45 mph: 1 of 23 (4.348%)

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: MENDON, MA
  • Total crash records analyzed: 179
  • Total persons involved: 418
  • Total vehicles involved: 307

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). "MENDON, 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/mendon/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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Mendon, MA Crash Report — 2022 | ThatCarHitMe.com