Monthly Traffic Safety Analysis

9,614 CRASHES IN
MASSACHUSETTS, MA
APRIL 2022

All metrics benchmarked againstApril 2021

In April 2022, there were 9,614 total crashes recorded, representing an 8.8% increase from the 8,836 crashes in April 2021. While total incidents and injuries (2,952, up from 2,656) rose, the most notable year-over-year shift was a significant 42.5% decrease in fatalities, which fell from 40 to 23.

9,614

8.8%was 8,836

Total Crash Events

23

-42.5%was 40

Persons Killed

2,952

11.1%was 2,656

Persons Injured

723

19.9%was 603

Hit-and-Run Crashes

Note: "Persons Killed" (23) counts individual fatalities across all crash events. "Fatal" in the severity table below (23) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 911 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crash trends for April show a year-over-year increase in volume. The total number of crashes rose by 8.8%, from 8,836 in April 2021 to 9,614 in April 2022. Concurrently, the number of injuries increased by 11.1% from 2,656 to 2,952, while total fatalities decreased from 40 to 23.

723

Hit-and-Run Crashes — April 2022

19.9% vs prior (603)

Hit-and-run incidents increased both in absolute numbers and as a percentage of total crashes. The count of hit-and-run crashes rose by 19.9% from 603 in April 2021 to 723 in April 2022. The hit-and-run rate also trended upward, increasing from 6.8% of all crashes in the prior period to 7.5% in the current period.

Vulnerable Road User Casualties

4

Pedestrians Killed

Prior: 7-42.9%

0

Cyclists Killed

Prior: 00.0%

19

Motorists Killed

Prior: 33-42.4%

0

Other Killed

Prior: 00.0%

107

Pedestrians Injured

Prior: 8328.9%

57

Cyclists Injured

Prior: 5014.0%

2,776

Motorists Injured

Prior: 2,51610.3%

12

Other Injured

Prior: 771.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The primary temporal patterns of crashes remained consistent year-over-year. Friday was the peak day for crashes in both April 2022 (1,960 crashes) and April 2021 (1,867 crashes). The 4 PM hour was also the consistent peak hour in both periods, with 802 and 757 crashes, respectively. A notable shift occurred in the ranking of other weekdays, with crashes on Thursday decreasing while incidents on Saturday increased, making it the second-busiest day in April 2022 with 1,542 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes decreased year-over-year, driven by a drop in fatal incidents. The rate of fatal crashes per 100 total crashes fell from 0.40 in April 2021 to 0.24 in April 2022. The proportion of crashes resulting in any level of injury remained stable, accounting for 22.8% of crashes in 2022 compared to 22.1% in 2021. The share of crashes resulting in 'No Injury' decreased slightly from 68.6% to 67.4%.

Outcome by Severity (Crash Events)

Fatal23fatal crashes0.2%
-34.3%prior 35
Serious Injury174serious injury crashes1.8%
4.8%prior 166
Minor Injury1,292minor injury crashes13.4%
18.6%prior 1,089
Possible Injury733possible injury crashes7.6%
4.9%prior 699
No Injury6,481no injury crashes67.4%
6.9%prior 6,060

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Most severe injury per crash record

Top Contributing Factors

The top five contributing factors for crashes were identical in both periods, with 'Inattention' being the most cited improper driving action. The count of crashes involving inattention increased by 9.4%, from 1,332 to 1,457. Incidents where a driver 'Followed too closely' saw a notable count increase of 16.4%, rising from 745 to 867. The number of crashes attributed to 'Failed to yield right of way' grew from 887 to 896, while 'Failure to keep in proper lane' remained nearly unchanged.

Officer-Reported Primary Contributing Cause

No improper driving2,040 (21.2%)3.6%prior 1,969
Inattention1,457 (15.2%)9.4%prior 1,332
Failed to yield right of way896 (9.3%)1.0%prior 887
Followed too closely867 (9%)16.4%prior 745
Failure to keep in proper lane or running off road406 (4.2%)-0.2%prior 407
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner388 (4%)16.9%prior 332
Other improper action351 (3.7%)6.4%prior 330
Disregarded traffic signs, signals, road markings252 (2.6%)9.6%prior 230
Distracted241 (2.5%)20.5%prior 200
Fatigued/asleep154 (1.6%)45.3%prior 106

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A larger proportion of crashes in April 2022 occurred under clear conditions compared to the prior year. Crashes on dry roads made up 86.0% of the total, up from 81.5% in April 2021, while the share of crashes on wet roads declined from 15.4% to 12.3%. In terms of lighting, the proportion of crashes in daylight decreased from 76.0% to 73.6%, while the share of incidents on dark, lighted roadways increased from 14.8% to 17.2%.

Weather

Clear6,497 (68.5%)
19.2%prior 5,450
Cloudy927 (9.8%)
10.9%prior 836
Clear/Clear599 (6.3%)
9.9%prior 545
Rain590 (6.2%)
-9.6%prior 653
Cloudy/Rain206 (2.2%)
-22.3%prior 265
Clear/Cloudy171 (1.8%)
-13.6%prior 198
Clear/Unknown89 (0.9%)
-6.3%prior 95
Clear/Other81 (0.9%)
-10.0%prior 90
Rain/Cloudy79 (0.8%)
-25.5%prior 106
Cloudy/Cloudy72 (0.8%)
18.0%prior 61

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Weather condition at time of crash

Lighting

Daylight7,081 (74.3%)
5.5%prior 6,715
Dark - lighted roadway1,652 (17.3%)
26.6%prior 1,305
Dark - roadway not lighted376 (3.9%)
-1.1%prior 380
Dusk227 (2.4%)
15.2%prior 197
Dawn136 (1.4%)
25.9%prior 108
Dark - unknown roadway lighting48 (0.5%)
11.6%prior 43
Other7 (0.1%)
-36.4%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Lighting condition field

Road Surface

Dry8,272 (87.1%)
14.8%prior 7,205
Wet1,179 (12.4%)
-13.6%prior 1,365
Sand, mud, dirt, oil, gravel17 (0.2%)
0.0%prior 17
Water (standing, moving)10 (0.1%)
66.7%prior 6
Slush7 (0.1%)
-84.8%prior 46
Other5 (0.1%)
Reported but invalid4 (0.0%)
Snow1 (0.0%)
-99.1%prior 107
Ice1 (0.0%)
-90.9%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Road surface condition field

Vehicles & Demographics

The demographic profile of vehicles and persons involved in crashes showed high stability year-over-year. The top five vehicle makes involved in crashes were Toyota, Honda, Ford, Chevrolet, and Nissan in both periods, with counts for each increasing in line with the overall rise in crashes. The age distribution of all persons involved was also consistent, with the 26-34 age group comprising the largest share in both April 2022 (16.7%) and April 2021 (17.2%).

Top Vehicle Makes (17,840 vehicles)

1
TOYOTA2,841 (15.9%)
12.9%prior 2,516
2
HONDA2,280 (12.8%)
11.6%prior 2,043
3
FORD1,915 (10.7%)
8.2%prior 1,770
4
CHEVROLET1,324 (7.4%)
2.6%prior 1,290
5
NISSAN1,210 (6.8%)
4.2%prior 1,161
6
JEEP768 (4.3%)
4.8%prior 733
7
SUBARU664 (3.7%)
20.9%prior 549
8
HYUNDAI637 (3.6%)
-1.2%prior 645
9
DODGE402 (2.3%)
-0.2%prior 403
10
KIA388 (2.2%)
8.7%prior 357

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Vehicle unit records

2,642 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (19,179 persons with recorded sex)

Male10,739 (56.0%)
7.7%prior 9,974
Female8,424 (43.9%)
9.7%prior 7,677
X / Unspecified11 (0.1%)
450.0%prior 2
R5 (0.0%)
25.0%prior 4

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes increased across all major speed zone categories year-over-year, with the largest volume occurring in zones posted at 30 mph or less in both periods. Despite the rise in total crashes, the number of fatalities decreased across all speed bands. Most significantly, in zones with speed limits of 55 mph or higher, fatalities dropped from 11 in April 2021 to 4 in April 2022, even as total crashes in those zones increased from 990 to 1,065.

Fatal crashes by zone: 10 mph: 1 of 157 (0.637%) · 25 mph: 2 of 1,821 (0.11%) · 30 mph: 5 of 2,707 (0.185%) · 35 mph: 2 of 1,304 (0.153%) · 40 mph: 3 of 639 (0.469%) · 45 mph: 2 of 331 (0.604%) · 50 mph: 2 of 200 (1%) · 55 mph: 1 of 462 (0.216%) · 60 mph: 1 of 47 (2.128%) · 65 mph: 2 of 550 (0.364%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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: 2022-04-01 through 2022-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-04-01 through 2022-04-30 (30 days)
  • Geographic scope: massachusetts, MA
  • Total crash records analyzed: 9,614
  • Total persons involved: 22,012
  • Total vehicles involved: 17,840

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). "massachusetts, MA Crash Intelligence Report: April 2022." Published June 21, 2026. Reporting period: 2022-04-01 to 2022-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/statewide/april-2022-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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Massachusetts (Statewide) Crash Report — April 2022 | ThatCarHitMe.com