Monthly Traffic Safety Analysis

45 CRASHES IN
BEVERLY, MA
MAY 2022

All metrics benchmarked againstMay 2021

In May 2022, BEVERLY, MA experienced 45 crashes, a significant increase from the 29 crashes recorded in May 2021. This represents a 55.17% rise in total crashes year-over-year. The most notable shift was the more than doubling of crashes involving a 'Failed to yield right of way' contributing factor, increasing from 3 to 10.

45

55.2%was 29

Total Crash Events

0

Persons Killed

14

180.0%was 5

Persons Injured

9

200.0%was 3

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 9 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a substantial increase in crashes, with total crashes rising from 29 in May 2021 to 45 in May 2022. This constitutes a 55.17% increase in crash incidents year-over-year.

9

Hit-and-Run Crashes — May 2022

200.0% vs prior (3)

Hit-and-run incidents significantly increased, with 9 crashes reported in May 2022 compared to 3 in May 2021, representing a 200% increase in count. The hit-and-run rate also rose from 10.3% of all crashes in May 2021 to 20% in May 2022, indicating an upward trend.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

13

Motorists Injured

Prior: 5160.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes shifted between the two periods. In May 2022, the peak day for crashes was Sunday with 12 incidents, compared to Saturday with 8 incidents in May 2021. The peak hour for crashes also shifted slightly, with 4 PM being the peak in May 2022 (6 crashes) and 5 PM being the peak in May 2021 (6 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either May 2021 or May 2022. The total number of injured persons increased from 5 in May 2021 to 14 in May 2022, marking a 180% increase. Crashes resulting in any injury (Serious, Minor, or Possible) increased from 5 in May 2021 to 10 in May 2022, a 100% rise.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.2%
Minor Injury6minor injury crashes13.3%
500.0%prior 1
Possible Injury3possible injury crashes6.7%
-25.0%prior 4
No Injury26no injury crashes57.8%
30.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw notable changes year-over-year. 'Failed to yield right of way' crashes increased from 3 to 10, a 233.3% change in count. 'Inattention' crashes rose from 2 to 6, a 200% change in count. Conversely, 'Followed too closely' crashes decreased from 4 to 1, a 75% change in count, and 'Distracted' crashes decreased from 2 to 1, a 50% change in count.

Officer-Reported Primary Contributing Cause

Failed to yield right of way10 (22.2%)
Inattention6 (13.3%)
Disregarded traffic signs, signals, road markings3 (6.7%)
No improper driving3 (6.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (4.4%)
Other improper action2 (4.4%)
Driving too fast for conditions1 (2.2%)
Distracted1 (2.2%)
Wrong side or wrong way1 (2.2%)
Fatigued/asleep1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in adverse conditions remained relatively low across both periods. Crashes on dry road surfaces increased from 24 in May 2021 to 40 in May 2022, while crashes on wet road surfaces slightly decreased from 5 to 4. Crashes occurring in daylight increased from 25 to 34, and crashes in dark-lighted roadway conditions increased from 2 to 8.

Weather

Clear/Clear32 (71.1%)
60.0%prior 20
Cloudy/Cloudy5 (11.1%)
Clear/Cloudy2 (4.4%)
Rain/Cloudy1 (2.2%)
Rain/Rain1 (2.2%)
Clear1 (2.2%)
Unknown/Unknown1 (2.2%)
Cloudy/Clear1 (2.2%)
Fog, smog, smoke/Fog, smog, smoke1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Weather condition at time of crash

Lighting

Daylight34 (77.3%)
36.0%prior 25
Dark - lighted roadway8 (18.2%)
Dark - roadway not lighted2 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Lighting condition field

Road Surface

Dry40 (90.9%)
66.7%prior 24
Wet4 (9.1%)
-20.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (84 vehicles)

1
FORD8 (9.5%)
2
TOYOTA7 (8.3%)
-22.2%prior 9
3
SUBARU6 (7.1%)
4
HONDA6 (7.1%)
5
NISSAN5 (6%)
6
CHEVROLET4 (4.8%)
-33.3%prior 6
7
JEEP3 (3.6%)
8
AUDI2 (2.4%)
9
MAZDA2 (2.4%)
10
VOLKSWAGEN2 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Vehicle unit records

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

Sex Distribution (88 persons with recorded sex)

Female46 (52.3%)
155.6%prior 18
Male42 (47.7%)
90.9%prior 22

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph speed zones increased from 15 in May 2021 to 30 in May 2022, making it the most frequent speed zone for crashes in both periods. Crashes in 55 mph speed zones decreased from 3 in May 2021 to 1 in May 2022. No fatal crashes were recorded in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · 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: 2022-05-01 through 2022-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-05-01 through 2022-05-31 (31 days)
  • Geographic scope: BEVERLY, MA
  • Total crash records analyzed: 45
  • Total persons involved: 118
  • Total vehicles involved: 84

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). "BEVERLY, MA Crash Intelligence Report: May 2022." Published June 21, 2026. Reporting period: 2022-05-01 to 2022-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/beverly/may-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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Beverly, MA Crash Report — May 2022 | ThatCarHitMe.com