Monthly Traffic Safety Analysis

5 CRASHES IN
AMESBURY, MA
MARCH 2026

All metrics benchmarked againstMarch 2025

In March 2026, Amesbury experienced 5 crashes, a 58.33% decrease compared to the 12 crashes recorded in March 2025. While total crashes decreased, there was a notable emergence of 'Driving too fast for conditions' as a contributing factor, present in 3 crashes in the current period compared to 0 in the prior period.

5

-58.3%was 12

Total Crash Events

0

Persons Killed

2

100.0%was 1

Persons Injured

1

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Amesbury showed a significant downward trend in March 2026, with a 58.33% decrease in total crashes compared to March 2025. The number of crashes fell from 12 in the prior year to 5 in the current period.

1

Hit-and-Run Crashes — March 2026

20.0% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 1100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year, with the peak day moving from Thursday in March 2025 (3 crashes) to Monday in March 2026 (2 crashes). The peak crash hour also changed from 11 AM in the prior period (2 crashes) to 9 PM in the current period (1 crash), indicating a shift towards later evening incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both March 2026 and March 2025. While total injuries increased from 1 to 2, the distribution of injury severity changed, with March 2026 reporting 1 serious injury crash (20% of total crashes) and 1 minor injury crash (20%), whereas March 2025 only reported 1 minor injury crash (8.3% of total crashes).

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes20%
Minor Injury1minor injury crashes20%
0.0%prior 1
No Injury3no injury crashes60%
-72.7%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factors shifted notably year-over-year. 'Driving too fast for conditions' increased from 0 crashes in March 2025 to 3 crashes in March 2026, becoming the dominant factor at 60% of current crashes. 'Followed too closely' remained constant at 1 crash in both periods, while factors such as 'No improper driving' and 'Inattention', each present in 2 crashes in March 2025, were not reported in March 2026.

Officer-Reported Primary Contributing Cause

Driving too fast for conditions3 (60%)
Failure to keep in proper lane or running off road1 (20%)
Followed too closely1 (20%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Weather conditions during crashes were more varied in March 2026, with 2 crashes occurring in clear conditions and 3 crashes occurring in sleet/hail/snow conditions, compared to March 2025 where 10 crashes occurred in clear conditions. Road surface conditions also reflected this, with 2 crashes on wet surfaces and 1 on slush in March 2026, a notable increase in adverse surface conditions compared to 1 crash on a wet surface in March 2025. Lighting conditions saw a shift, with 'Dark - roadway not lighted' accounting for 2 crashes in March 2026, whereas it was not a reported condition in March 2025.

Weather

Clear2 (40.0%)
-80.0%prior 10
Clear/Clear1 (20.0%)
Sleet, hail (freezing rain or drizzle)/Snow1 (20.0%)
Snow/Sleet, hail (freezing rain or drizzle)1 (20.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Weather condition at time of crash

Lighting

Dark - roadway not lighted2 (40.0%)
Daylight2 (40.0%)
-80.0%prior 10
Dawn1 (20.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Lighting condition field

Road Surface

Dry2 (40.0%)
-81.8%prior 11
Wet2 (40.0%)
Slush1 (20.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (9 vehicles)

1
TOYOTA3 (33.3%)
2
FREIGHTLINER CO1 (11.1%)
3
HYUNDAI1 (11.1%)
4
DODGE1 (11.1%)
5
NISSAN1 (11.1%)
6
INTERNATIONAL H1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Vehicle unit records

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

Sex Distribution (8 persons with recorded sex)

Male5 (62.5%)
-61.5%prior 13
Female3 (37.5%)
-62.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes by speed limit zones changed significantly year-over-year. In March 2026, all 5 crashes occurred in a 65 mph speed limit zone, with no fatalities. This is a substantial increase from March 2025, when only 1 crash occurred in a 65 mph zone, and the majority (7 crashes) occurred in 25 mph zones.

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

Data Coverage

  • Reporting period: 2026-03-01 through 2026-03-31 (31 days)
  • Geographic scope: AMESBURY, MA
  • Total crash records analyzed: 5
  • Total persons involved: 10
  • Total vehicles involved: 9

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