ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FAIRHAVEN, 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/fairhaven/2022-annual-report
Yearly Traffic Safety Analysis
561 CRASHES IN
FAIRHAVEN, MA
2022
In 2022, Fairhaven recorded 561 total traffic crashes, a 15.0% increase from the 488 crashes reported in 2021. While total injuries remained stable and fatalities decreased from one to zero, the most significant year-over-year change was a 127% increase in hit-and-run incidents, which rose from 11 in 2021 to 25 in 2022.
561
▲ 15.0%was 488
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
129
▲ 2.4%was 126
Persons Injured
25
▲ 127.3%was 11
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. 79 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
Overall, traffic crashes in Fairhaven trended upward from 2021 to 2022, with total incidents increasing by 15.0% from 488 to 561. While fatalities fell from one to zero, the total number of injuries saw a slight increase of 2.4%, from 126 in 2021 to 129 in 2022.
25
Hit-and-Run Crashes — 2022
▲ 127.3% vs prior (11)
The number of hit-and-run crashes increased significantly, more than doubling from 11 incidents in 2021 to 25 in 2022. This represents a 127% increase in the count of such events. Consequently, the hit-and-run rate, as a percentage of total crashes, nearly doubled from 2.3% to 4.5%, indicating a strong upward trend.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
4
Cyclists Injured
125
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
The temporal patterns of crashes showed some shifts between 2021 and 2022. While Friday remained the peak day for crashes in both years (82 in 2021, 100 in 2022), the peak hour moved from 3 p.m. in 2021 (44 crashes) to 12 p.m. in 2022 (53 crashes). Wednesdays also saw a notable increase in crashes, becoming the second-highest day in 2022 with 90 incidents, up from 61 the prior year.
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 improved in 2022, with fatal crashes decreasing from one in 2021 to zero. The proportion of crashes resulting in serious injury remained stable at 1.6% in both years. However, the distribution among non-fatal injury crashes shifted, with minor injury crashes increasing their share from 8.0% to 8.7% of all incidents, while possible injury crashes decreased from 8.6% to 6.2%.
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
While 'Inattention' and 'No improper driving' were the top two contributing factors in both periods, their order switched, with 'No improper driving' becoming the most cited factor in 2022 with 109 instances. The count for 'Inattention' decreased slightly from 108 to 104. More significant changes were observed in other categories; crashes attributed to 'Other improper action' more than doubled, increasing from 16 to 34, and 'Followed too closely' incidents rose from 15 to 22.
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
The environmental conditions under which crashes occurred remained largely consistent between 2021 and 2022. The vast majority of incidents in both years happened in 'Daylight' (69.7% in 2021 vs. 70.4% in 2022) and on 'Dry' road surfaces (80.1% vs. 80.4%). Crashes during 'Clear' weather also made up a similar share of the total in both periods (73.8% vs. 74.9%), indicating no significant shift in the proportion of crashes occurring in adverse conditions.
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 top three vehicle makes involved in crashes—Toyota, Ford, and Honda—remained the same in 2022 as in 2021. While the vehicle make distribution was stable, the demographics of persons involved showed a shift. The number of individuals aged 65 and older involved in crashes increased from 141 to 202, raising their share of total persons from 13.1% in 2021 to 15.7% in 2022.
Top Vehicle Makes (1,051 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
207 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,085 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
Crashes increased across most major speed zones from 2021 to 2022. The largest raw increase occurred in 25 mph zones, which saw incidents rise from 206 to 253, and their share of all speed-zoned crashes grew from 40.6% to 45.1%. The single fatal crash recorded in 2021 occurred in a 35 mph zone, while no fatal crashes were recorded in any speed zone in 2022.
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: FAIRHAVEN, MA
- Total crash records analyzed: 561
- Total persons involved: 1,287
- Total vehicles involved: 1,051
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). "FAIRHAVEN, 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/fairhaven/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