ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · AMESBURY, MA · 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/amesbury/2022-annual-report
Yearly Traffic Safety Analysis
287 CRASHES IN
AMESBURY, MA
2022
In 2022, Amesbury recorded 287 total traffic crashes, a 16.2% increase from the 247 crashes reported in 2021. While total injuries decreased slightly and fatalities remained stable at one, the most notable year-over-year shift was a 185.7% increase in hit-and-run incidents, which rose from 7 in 2021 to 20 in 2022.
287
▲ 16.2%was 247
Total Crash Events
1
Persons Killed
56
▼ -6.7%was 60
Persons Injured
20
▲ 185.7%was 7
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. 22 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend shows a rise in traffic incidents in Amesbury. Total crashes increased by 16.2% from 247 in 2021 to 287 in 2022. Despite this increase in crash volume, the number of fatalities was unchanged at one, and the total number of injuries decreased slightly from 60 to 56.
20
Hit-and-Run Crashes — 2022
▲ 185.7% vs prior (7)
Hit-and-run crashes increased significantly in both count and rate. The number of hit-and-run incidents rose from 7 in 2021 to 20 in 2022, representing a 185.7% increase. Consequently, the hit-and-run rate as a percentage of all crashes more than doubled, climbing from 2.8% in the prior year to 7.0% in the current year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
3
Pedestrians Injured
1
Cyclists Injured
52
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Temporal crash patterns shifted between the two periods. While Friday remained the peak day for crashes in both years (47 in 2021, 54 in 2022), the peak hour for incidents moved an hour earlier. In 2022, the most crashes occurred at 3 PM with 35 incidents, compared to a 4 PM peak of 22 crashes in 2021.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes showed a mixed profile year-over-year. The number of fatal crashes remained stable at one in both 2022 and 2021, though the fatal crash rate per 100 crashes decreased slightly from 0.40 to 0.35 due to the higher total crash volume. The proportion of crashes resulting in any level of injury (Fatal, Serious, Minor, or Possible) decreased from 18.2% in 2021 to 15.0% in 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes changed significantly year-over-year. In 2022, 'No improper driving' was the most cited factor with 108 crashes, an 83% increase in count from 59 in 2021. Conversely, crashes attributed to 'Inattention' decreased by 24% in count, from 58 in 2021 to 44 in 2022, moving it from the top-ranked factor to a distant second. Crashes involving 'Failed to yield right of way' also saw a notable increase in count from 10 to 17.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in 2022 were slightly more likely to occur in ideal conditions compared to 2021. The share of crashes happening in daylight increased from 67.2% to 71.4%, and those on dry road surfaces remained stable at approximately 78%. Similarly, crashes in clear weather constituted a larger portion of the total, rising from a 67.2% share in 2021 to a 71.1% share in 2022.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes saw a shift in rankings. Toyota became the most frequently involved make in 2022 with 80 vehicles, up from 47 in 2021 when it was ranked fourth. Ford, the top-ranked make in 2021 with 56 vehicles, dropped to third place in 2022 with 43 vehicles. The age distribution of persons involved in crashes remained broadly consistent across both years, with no significant proportional shifts observed in any age bracket.
Top Vehicle Makes (506 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
63 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (530 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
There was a significant shift in the speed zones where crashes occurred. Crashes in 25 mph zones increased substantially from 41 in 2021 to 117 in 2022. In contrast, crashes in 30 mph zones fell sharply from 62 to 15. The location of the year's single fatal crash also shifted, occurring in a 65 mph zone in 2022, whereas the prior year's fatal crash was in a 30 mph zone.
Fatal crashes by zone: 65 mph: 1 of 48 (2.083%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: AMESBURY, MA
- Total crash records analyzed: 287
- Total persons involved: 601
- Total vehicles involved: 506
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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/amesbury/2022-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved