Yearly Traffic Safety Analysis

278 CRASHES IN
ACTON, MA
2022

All metrics benchmarked against2021

In 2022, Acton recorded 278 total crashes, a 36.9% increase from the 203 crashes in 2021. The most significant change was the occurrence of two fatal crashes resulting in two deaths, compared to zero in the prior year. Overall injuries also rose from 53 to 72, a 35.8% increase.

278

36.9%was 203

Total Crash Events

2

Persons Killed

72

35.8%was 53

Persons Injured

6

-14.3%was 7

Hit-and-Run Crashes

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 12 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

Traffic collisions in Acton increased significantly year-over-year. Total crashes rose by 36.9% from 203 in 2021 to 278 in 2022, while total reported injuries increased by 35.8% from 53 to 72. The city also experienced two fatalities in 2022, whereas none were recorded in the previous year.

6

Hit-and-Run Crashes — 2022

-14.3% vs prior (7)

The number of hit-and-run incidents decreased slightly in 2022, falling to 6 crashes from 7 in the previous year. This change, combined with the overall increase in total crashes, resulted in a lower hit-and-run rate. The rate of hit-and-run crashes declined from 3.4% in 2021 to 2.2% in 2022.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

1

Motorists Killed

Prior: 0%

4

Pedestrians Injured

Prior: 0%

68

Motorists Injured

Prior: 5328.3%

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 temporal patterns of crashes showed some shifts between the two periods. While Friday remained the peak day for crashes in both 2021 (46 crashes) and 2022 (52 crashes), the peak hour for collisions moved later in the day. In 2022, the most crashes occurred at 6 p.m. (25 crashes), a shift from the 3 p.m. peak (21 crashes) observed in 2021.

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 notably in 2022, with the city recording two fatal crashes after having none in 2021, resulting in a fatal crash rate of 0.72 per 100 crashes. While the count of serious injury crashes decreased slightly from 5 to 4, crashes involving possible injuries more than doubled from 15 to 31. Consequently, the share of crashes resulting in no injury decreased from 76.4% in 2021 to 72.7% in 2022.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.7%
Serious Injury4serious injury crashes1.4%
-20.0%prior 5
Minor Injury27minor injury crashes9.7%
12.5%prior 24
Possible Injury31possible injury crashes11.2%
106.7%prior 15
No Injury202no injury crashes72.7%
30.3%prior 155

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

In 2022, 'Inattention' became the leading contributing factor, with the count of such crashes rising by 70.6% from 34 to 58. This displaced 'No improper driving' from the top rank, even though its count also increased from 40 to 45. Another significant change was the 92.3% increase in the count of crashes attributed to 'Driving too fast for conditions', which grew from 13 incidents in 2021 to 25 in 2022.

Officer-Reported Primary Contributing Cause

Inattention58 (20.9%)70.6%prior 34
No improper driving45 (16.2%)12.5%prior 40
Failed to yield right of way26 (9.4%)18.2%prior 22
Driving too fast for conditions25 (9%)92.3%prior 13
Followed too closely20 (7.2%)33.3%prior 15
Failure to keep in proper lane or running off road13 (4.7%)160.0%prior 5
Disregarded traffic signs, signals, road markings11 (4%)10.0%prior 10
Other improper action11 (4%)120.0%prior 5
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner7 (2.5%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway6 (2.2%)

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 proportion of crashes occurring in adverse conditions increased in 2022 compared to the prior year. Crashes on snow-covered roads rose from 10 to 25, and incidents on icy roads tripled from 4 to 12. While most collisions in both years happened on dry roads, their share of total crashes fell from 74.4% in 2021 to 68.3% in 2022. Similarly, the share of crashes in daylight conditions decreased from 73.9% to 68.0%.

Weather

Clear154 (56.0%)
83.3%prior 84
Cloudy24 (8.7%)
100.0%prior 12
Rain18 (6.5%)
38.5%prior 13
Snow17 (6.2%)
240.0%prior 5
Clear/Clear15 (5.5%)
-72.2%prior 54
Clear/Cloudy10 (3.6%)
Cloudy/Rain7 (2.5%)
16.7%prior 6
Clear/Other4 (1.5%)
Rain/Cloudy3 (1.1%)
Cloudy/Clear3 (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

Daylight189 (68.2%)
26.0%prior 150
Dark - lighted roadway43 (15.5%)
38.7%prior 31
Dark - roadway not lighted27 (9.7%)
68.8%prior 16
Dusk11 (4.0%)
Dawn5 (1.8%)
Dark - unknown roadway lighting2 (0.7%)

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

Road Surface

Dry190 (68.8%)
25.8%prior 151
Wet46 (16.7%)
31.4%prior 35
Snow25 (9.1%)
150.0%prior 10
Ice12 (4.3%)
Slush2 (0.7%)
Water (standing, moving)1 (0.4%)

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 three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained the same in both years, with all seeing an increase in crash counts. The number of crashes involving Hondas rose by 52.1% (from 48 to 73) and Fords by 54.1% (from 37 to 57). Regarding the demographics of all persons involved in crashes, the 16-20 age group saw a notable increase in involvement, from 57 individuals in 2021 to 80 in 2022.

Top Vehicle Makes (468 vehicles)

1
TOYOTA92 (19.7%)
17.9%prior 78
2
HONDA73 (15.6%)
52.1%prior 48
3
FORD57 (12.2%)
54.1%prior 37
4
SUBARU38 (8.1%)
90.0%prior 20
5
NISSAN28 (6%)
133.3%prior 12
6
CHEVROLET25 (5.3%)
0.0%prior 25
7
JEEP20 (4.3%)
11.1%prior 18
8
MAZDA10 (2.1%)
25.0%prior 8
9
BMW10 (2.1%)
10
ACURA9 (1.9%)
-10.0%prior 10

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

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

Sex Distribution (535 persons with recorded sex)

Male292 (54.6%)
20.2%prior 243
Female243 (45.4%)
28.6%prior 189

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

Crashes increased across most speed zones in 2022, with a notable surge in lower-speed areas. Collisions in 30 mph zones more than doubled, rising from 38 to 84 incidents year-over-year. The two fatal crashes recorded in 2022 both occurred in a 40 mph zone, a speed limit that saw its total crash count increase from 26 to 45. In 2021, no fatal crashes were recorded in any speed zone.

Fatal crashes by zone: 40 mph: 2 of 45 (4.444%)

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: ACTON, MA
  • Total crash records analyzed: 278
  • Total persons involved: 585
  • Total vehicles involved: 468

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). "ACTON, 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/acton/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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Acton, MA Crash Report — 2022 | ThatCarHitMe.com