Monthly Traffic Safety Analysis

10 CRASHES IN
BERLIN, MA
MARCH 2023

All metrics benchmarked againstMarch 2022

Total crashes in BERLIN, MA remained stable at 10 in March 2023, consistent with the 10 crashes reported in March 2022. However, total injuries increased from 0 in March 2022 to 2 in March 2023. This represents the most significant year-over-year shift in safety outcomes.

10

Total Crash Events

0

Persons Killed

2

Persons Injured

0

Fatal Crash Events

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend for total crashes in BERLIN, MA remained stable, with 10 crashes recorded in March 2023, matching the 10 crashes from March 2022. Fatalities remained at 0 in both periods. However, total injuries increased from 0 in March 2022 to 2 in March 2023, indicating a negative shift in injury outcomes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Wednesday with 3 crashes in March 2022 to Tuesday with 3 crashes in March 2023. The peak hour for crashes remained consistent at 3 PM in both periods, with 3 crashes. Crashes on Sunday decreased from 3 to 1, while crashes on Tuesday increased from 0 to 3 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes20%
No Injury8no injury crashes80%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'No improper driving' increased from 2 crashes in March 2022 to 3 crashes in March 2023, a 50% increase in count. 'Followed too closely' remained stable with 1 crash in both periods. Factors such as 'Driving too fast for conditions' (2 crashes), 'Inattention' (2 crashes), and 'Distracted' (1 crash) were present in March 2022 but not in March 2023. Conversely, 'Failure to keep in proper lane or running off road' (3 crashes), 'Exceeded authorized speed limit' (1 crash), 'Failed to yield right of way' (1 crash), and 'Glare' (1 crash) emerged as contributing factors in March 2023.

Officer-Reported Primary Contributing Cause

Failure to keep in proper lane or running off road3 (30%)
No improper driving3 (30%)
Exceeded authorized speed limit1 (10%)
Failed to yield right of way1 (10%)
Followed too closely1 (10%)
Glare1 (10%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under 'Clear' weather conditions increased from 4 in March 2022 to 8 in March 2023. Similarly, crashes on 'Dry' road surfaces increased from 5 to 7 year-over-year. Conversely, crashes on 'Snow' road surfaces decreased from 3 to 2, and on 'Ice' road surfaces from 2 to 1. Crashes during 'Daylight' increased from 5 to 7, while 'Dawn' and 'Dusk' conditions, each accounting for 1 crash in March 2022, were not present in March 2023.

Weather

Clear8 (80.0%)
Snow/Cloudy2 (20.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash

Lighting

Daylight7 (70.0%)
40.0%prior 5
Dark - roadway not lighted2 (20.0%)
Dark - lighted roadway1 (10.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field

Road Surface

Dry7 (70.0%)
40.0%prior 5
Snow2 (20.0%)
Ice1 (10.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (14 vehicles)

1
FORD3 (21.4%)
2
TOYOTA3 (21.4%)
-50.0%prior 6
3
HONDA2 (14.3%)
4
LEXUS1 (7.1%)
5
SUBARU1 (7.1%)
6
CHEVROLET1 (7.1%)
7
VOLVO1 (7.1%)
8
FRHT1 (7.1%)
9
HYUNDAI1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records

Sex Distribution (16 persons with recorded sex)

Male12 (75.0%)
9.1%prior 11
Female4 (25.0%)
-50.0%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones shifted year-over-year, with 2 crashes each occurring in 20 mph and 25 mph zones in March 2023, which had no crashes in March 2022. Crashes in 35 mph zones decreased from 4 in March 2022 to 2 in March 2023. Additionally, 45 mph and 65 mph zones, which each recorded 1 crash in March 2022, had no crashes in March 2023. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-03-01 through 2023-03-31 (31 days)
  • Geographic scope: BERLIN, MA
  • Total crash records analyzed: 10
  • Total persons involved: 17
  • Total vehicles involved: 14

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). "BERLIN, MA Crash Intelligence Report: March 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/berlin/march-2023-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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Berlin, MA Crash Report — March 2023 | ThatCarHitMe.com