Monthly Traffic Safety Analysis

58 CRASHES IN
FAIRHAVEN, MA
NOVEMBER 2022

All metrics benchmarked againstNovember 2021

In November 2022, Fairhaven experienced 58 crashes, an 11.5% increase compared to 52 crashes in November 2021. A notable shift was the emergence of hit-and-run crashes, with 3 reported in the current period compared to none in the prior year.

58

11.5%was 52

Total Crash Events

0

Persons Killed

14

40.0%was 10

Persons Injured

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. 6 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Fairhaven showed an increasing trend year-over-year, with total crashes rising from 52 in November 2021 to 58 in November 2022. This represents an 11.5% increase in total crash incidents. Total injuries also increased from 10 to 14 during this period.

3

Hit-and-Run Crashes — November 2022

5.2% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

14

Motorists Injured

Prior: 955.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal patterns of crashes in Fairhaven shifted between the two periods. The peak day for crashes moved from Friday in November 2021 (10 crashes) to Tuesday and Wednesday in November 2022 (14 crashes each). The peak crash hour also shifted from 6 PM in the prior year to 12 PM in the current period, both recording 8 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities and fatal crashes remained at zero in both November 2021 and November 2022. Total injuries increased from 10 in the prior period to 14 in the current period. The proportion of crashes resulting in possible injuries rose from 3.8% to 10.3% of all crashes, while minor injury crashes decreased from 11.5% to 6.9%.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes6.9%
-33.3%prior 6
Possible Injury6possible injury crashes10.3%
200.0%prior 2
No Injury42no injury crashes72.4%
10.5%prior 38

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors saw shifts year-over-year. 'Inattention' increased significantly from 12 crashes in November 2021 to 19 crashes in November 2022, making it the most frequent factor. Conversely, 'No improper driving' decreased from 17 crashes to 10 crashes, shifting from the top factor to the second most common. 'Other improper action' also saw an increase, from 2 crashes to 4 crashes.

Officer-Reported Primary Contributing Cause

Inattention19 (32.8%)58.3%prior 12
No improper driving10 (17.2%)-41.2%prior 17
Other improper action4 (6.9%)
Followed too closely3 (5.2%)
Distracted2 (3.4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (3.4%)
Glare1 (1.7%)
Exceeded authorized speed limit1 (1.7%)
Failed to yield right of way1 (1.7%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 42 in November 2021 to 47 in November 2022, while crashes during rainy conditions (Rain, Cloudy/Rain, Rain/Cloudy combined) decreased from 7 to 4. Crashes occurring in daylight remained stable at 30 incidents in both periods. However, crashes in 'Dark - lighted roadway' conditions increased from 12 to 17, and those during 'Dusk' increased from 1 to 3.

Weather

Clear47 (85.5%)
11.9%prior 42
Cloudy4 (7.3%)
Cloudy/Rain2 (3.6%)
Rain1 (1.8%)
Rain/Cloudy1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Weather condition at time of crash

Lighting

Daylight30 (52.6%)
0.0%prior 30
Dark - lighted roadway17 (29.8%)
41.7%prior 12
Dark - roadway not lighted6 (10.5%)
0.0%prior 6
Dusk3 (5.3%)
Other1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Lighting condition field

Road Surface

Dry48 (85.7%)
11.6%prior 43
Wet7 (12.5%)
-22.2%prior 9
Sand, mud, dirt, oil, gravel1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Road surface condition field

Vehicles & Demographics

The number of persons aged 65 and older involved in crashes saw a significant increase, rising from 15 in November 2021 to 30 in November 2022. Toyota became the most frequently involved vehicle make, with its count increasing from 12 to 25, while Ford remained stable at 12. Honda also saw an increase in involvement, from 5 to 10 incidents.

Top Vehicle Makes (110 vehicles)

1
TOYOTA25 (22.7%)
108.3%prior 12
2
FORD12 (10.9%)
0.0%prior 12
3
HONDA10 (9.1%)
100.0%prior 5
4
CHEVROLET8 (7.3%)
60.0%prior 5
5
KIA7 (6.4%)
40.0%prior 5
6
HYUNDAI5 (4.5%)
7
SUBARU5 (4.5%)
8
JEEP5 (4.5%)
-28.6%prior 7
9
VOLKSWAGEN4 (3.6%)
-20.0%prior 5
10
BMW3 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Vehicle unit records

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

Sex Distribution (119 persons with recorded sex)

Female66 (55.5%)
40.4%prior 47
Male53 (44.5%)
10.4%prior 48

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone increased from 22 incidents in November 2021 to 31 incidents in November 2022. Similarly, crashes in the 35 mph speed zone rose from 8 to 14 during the same period. Conversely, crashes in the 10 mph zone decreased from 4 to 1, and in the 15 mph zone from 5 to 3. No fatal crashes were recorded in any speed zone in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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: 2022-11-01 through 2022-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-11-01 through 2022-11-30 (30 days)
  • Geographic scope: FAIRHAVEN, MA
  • Total crash records analyzed: 58
  • Total persons involved: 140
  • Total vehicles involved: 110

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: November 2022." Published June 21, 2026. Reporting period: 2022-11-01 to 2022-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fairhaven/november-2022-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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Fairhaven, MA Crash Report — November 2022 | ThatCarHitMe.com