Monthly Traffic Safety Analysis

14 CRASHES IN
AMESBURY, MA
APRIL 2023

All metrics benchmarked againstApril 2022

In April 2023, Amesbury experienced 14 total crashes, a decrease of 39.1% compared to the 23 crashes reported in April 2022. Despite the reduction in total crashes, total injuries increased significantly by 600%, from 1 injury in the prior period to 7 injuries in the current period. The most notable year-over-year shift was the substantial decrease in overall crash incidents while injury counts rose.

14

-39.1%was 23

Total Crash Events

0

Persons Killed

7

600.0%was 1

Persons Injured

1

-66.7%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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a significant decrease in total crashes, falling by 39.1% from 23 crashes in April 2022 to 14 crashes in April 2023. Conversely, total injuries saw a substantial increase of 600%, rising from 1 injury to 7 injuries over the same period. Fatalities remained at zero in both periods.

1

Hit-and-Run Crashes — April 2023

-66.7% vs prior (3)

Hit-and-run crashes decreased by 2 incidents, from 3 in April 2022 to 1 in April 2023. The hit-and-run rate also decreased, falling from 13% of total crashes in the prior period to 7.1% in the current period, indicating a downward trend.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

6

Motorists Injured

Prior: 1500.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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 in April 2022, which had 5 crashes, to Saturday in April 2023, which recorded 7 crashes. The peak hour also changed, moving from 11 PM with 3 crashes in the prior period to 5 PM with 3 crashes in the current period. Notably, Wednesday and Friday, which had 5 and 4 crashes respectively in the prior year, reported no crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities in either period. Total injuries increased by 600%, from 1 injury in April 2022 to 7 injuries in April 2023. The proportion of crashes resulting in minor injuries (code 'B') significantly increased, accounting for 35.7% of crashes in the current period (5 crashes) compared to 4.3% (1 crash) in the prior period.

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes35.7%
400.0%prior 1
No Injury8no injury crashes57.1%
-55.6%prior 18

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Most severe injury per crash record

Top Contributing Factors

Among common contributing factors, 'No improper driving' decreased by 4 crashes, from 9 in the prior period to 5 in the current period. 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' and 'Inattention' each decreased by 2 crashes. Several factors, including 'Over-correcting/over-steering' and 'Distracted,' appeared in the current period with 1 crash each, having not been present in the prior period's data.

Officer-Reported Primary Contributing Cause

No improper driving5 (35.7%)-44.4%prior 9
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (14.3%)
Inattention1 (7.1%)
Over-correcting/over-steering1 (7.1%)
Physical impairment1 (7.1%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (7.1%)
Distracted1 (7.1%)
Wrong side or wrong way1 (7.1%)
Failed to yield right of way1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 19 in April 2022 to 11 in April 2023, while crashes in rainy conditions increased from 1 to 2. The percentage of crashes on dry road surfaces decreased from 91.3% (21 of 23 crashes) to 85.7% (12 of 14 crashes). Crashes occurring in daylight decreased by 7, from 17 to 10, while crashes in dark-lighted roadway conditions remained constant at 4.

Weather

Clear11 (78.6%)
-42.1%prior 19
Rain2 (14.3%)
Clear/Cloudy1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Weather condition at time of crash

Lighting

Daylight10 (71.4%)
-41.2%prior 17
Dark - lighted roadway4 (28.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Lighting condition field

Road Surface

Dry12 (85.7%)
-42.9%prior 21
Wet2 (14.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (21 vehicles)

1
HONDA3 (14.3%)
2
TOYOTA3 (14.3%)
-40.0%prior 5
3
FORD3 (14.3%)
-40.0%prior 5
4
SUBARU3 (14.3%)
5
GMC2 (9.5%)
6
CHEVROLET2 (9.5%)
-66.7%prior 6
7
MAZDA2 (9.5%)
8
VOLKSWAGEN1 (4.8%)
9
NISSAN1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Vehicle unit records

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

Sex Distribution (27 persons with recorded sex)

Female14 (51.9%)
-6.7%prior 15
Male13 (48.1%)
-35.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones decreased by 5 crashes, from 10 in the prior period to 5 in the current period. Crashes in 40 mph zones also decreased by 2 crashes, from 4 to 2. The current period recorded 2 crashes in 5 mph zones and 1 crash in a 45 mph zone, categories not present in the prior period's data.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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: 2023-04-01 through 2023-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-04-01 through 2023-04-30 (30 days)
  • Geographic scope: AMESBURY, MA
  • Total crash records analyzed: 14
  • Total persons involved: 28
  • Total vehicles involved: 21

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: April 2023." Published June 21, 2026. Reporting period: 2023-04-01 to 2023-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/amesbury/april-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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Amesbury, MA Crash Report — April 2023 | ThatCarHitMe.com