Yearly Traffic Safety Analysis

284 CRASHES IN
AMESBURY, MA
2023

All metrics benchmarked against2022

In 2023, Amesbury recorded 284 total traffic crashes, a slight decrease from the 287 crashes in 2022. While the overall crash volume remained stable with a 1% year-over-year decline, the number of people injured in these incidents rose significantly. Total injuries increased by 46.4%, from 56 in 2022 to 82 in 2023, marking the most notable shift in the city's crash profile.

284

-1.0%was 287

Total Crash Events

1

Persons Killed

82

46.4%was 56

Persons Injured

18

-10.0%was 20

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 7 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Amesbury were mixed year-over-year. The total number of crashes saw a marginal decrease of 1%, from 287 in 2022 to 284 in 2023, indicating a stable volume of incidents. However, the severity of these crashes worsened, with total injuries climbing by 46.4% from 56 to 82, while fatalities held constant at one person in each year.

18

Hit-and-Run Crashes — 2023

-10.0% vs prior (20)

Hit-and-run incidents showed a downward trend in 2023 compared to the previous year. The total count of hit-and-run crashes decreased from 20 to 18. Correspondingly, the hit-and-run rate, as a percentage of all crashes, also declined from 7.0% in 2022 to 6.3% in 2023.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 10.0%

0

Other Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 30.0%

7

Cyclists Injured

Prior: 1600.0%

71

Motorists Injured

Prior: 5236.5%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some consistency and some shifts between the two periods. Friday remained the peak day for crashes in both 2023 (49 crashes) and 2022 (54 crashes). However, the peak hour for collisions moved one hour later, from the 3 PM hour in 2022 (35 crashes) to the 4 PM hour in 2023 (29 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the number of fatal crashes remained unchanged at one for both 2023 and 2022, the proportion of injury-related crashes increased. The count of serious injury crashes rose from 3 in 2022 to 8 in 2023, and minor injury crashes increased from 27 to 39. Consequently, the share of crashes resulting in no injury decreased from 77.0% in 2022 to 76.1% in 2023.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
0.0%prior 1
Serious Injury8serious injury crashes2.8%
166.7%prior 3
Minor Injury39minor injury crashes13.7%
44.4%prior 27
Possible Injury13possible injury crashes4.6%
0.0%prior 13
No Injury216no injury crashes76.1%
-2.3%prior 221

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes remained similar, though their counts shifted. 'Inattention' remained the second-most cited factor, with its crash count increasing from 44 in 2022 to 49 in 2023. 'Failed to yield right of way' saw its count increase by 41.2%, from 17 crashes to 24, moving it into the top three factors for 2023. Conversely, crashes attributed to 'No improper driving' decreased from a count of 108 to 90.

Officer-Reported Primary Contributing Cause

No improper driving90 (31.7%)-16.7%prior 108
Inattention49 (17.3%)11.4%prior 44
Failed to yield right of way24 (8.5%)41.2%prior 17
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner23 (8.1%)64.3%prior 14
Failure to keep in proper lane or running off road13 (4.6%)-35.0%prior 20
Other improper action9 (3.2%)50.0%prior 6
Distracted8 (2.8%)-11.1%prior 9
Driving too fast for conditions7 (2.5%)40.0%prior 5
Visibility obstructed7 (2.5%)
Physical impairment6 (2.1%)20.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained largely consistent year-over-year, with the majority of incidents in both periods occurring in daylight and on dry roads. In 2023, 76.1% of crashes happened on dry surfaces, compared to 78.0% in 2022. There was a slight increase in crashes on wet roads, from 36 incidents in 2022 to 44 in 2023, but the overall distribution of crashes by weather and lighting conditions did not change significantly.

Weather

Clear201 (71.3%)
-1.5%prior 204
Cloudy25 (8.9%)
0.0%prior 25
Rain13 (4.6%)
30.0%prior 10
Snow11 (3.9%)
10.0%prior 10
Cloudy/Rain7 (2.5%)
40.0%prior 5
Snow/Sleet, hail (freezing rain or drizzle)4 (1.4%)
Sleet, hail (freezing rain or drizzle)3 (1.1%)
Clear/Unknown3 (1.1%)
-50.0%prior 6
Cloudy/Other2 (0.7%)
Clear/Other2 (0.7%)
-75.0%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight208 (73.2%)
1.5%prior 205
Dark - lighted roadway49 (17.3%)
-2.0%prior 50
Dusk13 (4.6%)
44.4%prior 9
Dark - roadway not lighted11 (3.9%)
-26.7%prior 15
Dawn2 (0.7%)
-66.7%prior 6
Dark - unknown roadway lighting1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry216 (76.1%)
-3.6%prior 224
Wet44 (15.5%)
22.2%prior 36
Snow17 (6.0%)
13.3%prior 15
Ice5 (1.8%)
-54.5%prior 11
Slush2 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes saw a notable shift in ranking. While Toyota remained the top make in 2023, its count dropped from 80 to 61; Ford's involvement increased from 43 to 60 vehicles, moving it from third to second place. Analysis of persons involved shows a significant demographic change, with the number of individuals in the 0-15 age group more than doubling from 33 in 2022 to 79 in 2023.

Top Vehicle Makes (496 vehicles)

1
TOYOTA61 (12.3%)
-23.8%prior 80
2
FORD60 (12.1%)
39.5%prior 43
3
HONDA58 (11.7%)
-17.1%prior 70
4
CHEVROLET47 (9.5%)
34.3%prior 35
5
JEEP28 (5.6%)
47.4%prior 19
6
NISSAN21 (4.2%)
-25.0%prior 28
7
HYUNDAI21 (4.2%)
23.5%prior 17
8
SUBARU20 (4%)
-28.6%prior 28
9
GMC18 (3.6%)
38.5%prior 13
10
MERCEDES-BENZ10 (2%)
42.9%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (586 persons with recorded sex)

Male326 (55.6%)
19.0%prior 274
Female259 (44.2%)
1.2%prior 256
X / Unspecified1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes by speed zone shifted slightly toward lower-speed areas. Crashes in 25 mph zones increased from 117 in 2022 to 131 in 2023, while incidents in 40 mph and 65 mph zones saw minor decreases. The location of the single fatal crash also shifted, occurring in a 25 mph zone in 2023, compared to a 65 mph zone in the prior year.

Fatal crashes by zone: 25 mph: 1 of 131 (0.763%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: AMESBURY, MA
  • Total crash records analyzed: 284
  • Total persons involved: 652
  • Total vehicles involved: 496

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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/amesbury/2023-annual-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 — 2023 | ThatCarHitMe.com