Monthly Traffic Safety Analysis

83 CRASHES IN
WESTON, MA
NOVEMBER 2022

All metrics benchmarked againstNovember 2021

In November 2022, WESTON experienced 83 crashes, an 18.6% increase compared to the 70 crashes recorded in November 2021. Total injuries also saw a substantial rise, increasing by 68.4% from 19 to 32 over the same period. There were no fatalities reported in either November 2021 or November 2022.

83

18.6%was 70

Total Crash Events

0

Persons Killed

32

68.4%was 19

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.

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

The overall trend indicates a rise in crash incidents year-over-year, with total crashes increasing by 18.6% from 70 in November 2021 to 83 in November 2022. Concurrently, the number of injured persons also significantly increased by 68.4%, from 19 to 32. Fatalities remained stable at zero in both periods.

3

Hit-and-Run Crashes — November 2022

3.6% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

32

Motorists Injured

Prior: 1877.8%

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

The peak day for crashes remained Tuesday in both periods, with 14 crashes in November 2021 and 18 crashes in November 2022. The peak crash hour shifted from 8 AM (7 crashes) in November 2021 to 5 PM (13 crashes) in November 2022, indicating a shift in peak crash activity to later in the day.

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

Fatal crashes remained at zero in both November 2021 and November 2022. The total number of injured persons increased from 19 in November 2021 to 32 in November 2022, a 68.4% increase. Notably, one serious injury crash (Severity A) was reported in November 2022, whereas none were recorded in the prior period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.2%
Minor Injury15minor injury crashes18.1%
114.3%prior 7
Possible Injury11possible injury crashes13.3%
175.0%prior 4
No Injury56no injury crashes67.5%
-3.4%prior 58

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 top contributing factor shifted from 'No improper driving' in November 2021 (21 crashes) to 'Followed too closely' in November 2022 (32 crashes), marking a 77.8% increase in count for the latter. 'No improper driving' decreased by 33.3% in count, from 21 crashes to 14 crashes. 'Inattention' increased by 60% in count, from 5 crashes to 8 crashes.

Officer-Reported Primary Contributing Cause

Followed too closely32 (38.6%)77.8%prior 18
No improper driving14 (16.9%)-33.3%prior 21
Inattention8 (9.6%)60.0%prior 5
Failure to keep in proper lane or running off road4 (4.8%)
Failed to yield right of way4 (4.8%)
Driving too fast for conditions4 (4.8%)-42.9%prior 7
Fatigued/asleep3 (3.6%)
Distracted2 (2.4%)
Operating defective equipment1 (1.2%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (1.2%)

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 52 in November 2021 to 57 in November 2022, though their share of total crashes decreased from 74.3% to 68.7%. Crashes on dry road surfaces increased from 57 to 70 year-over-year, maintaining a high proportion of total crashes at 84.3% in November 2022. Crashes in 'Dark - roadway not lighted' and 'Dark - lighted roadway' conditions remained relatively stable, with 16 and 17 crashes respectively in November 2021, and 17 and 16 crashes in November 2022.

Weather

Clear57 (68.7%)
9.6%prior 52
Cloudy10 (12.0%)
Rain7 (8.4%)
Clear/Cloudy6 (7.2%)
Cloudy/Rain3 (3.6%)
-40.0%prior 5

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

Lighting

Daylight43 (51.8%)
26.5%prior 34
Dark - roadway not lighted17 (20.5%)
6.3%prior 16
Dark - lighted roadway16 (19.3%)
-5.9%prior 17
Dark - unknown roadway lighting3 (3.6%)
Dawn2 (2.4%)
Dusk2 (2.4%)

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

Road Surface

Dry70 (84.3%)
22.8%prior 57
Wet12 (14.5%)
0.0%prior 12
Water (standing, moving)1 (1.2%)

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

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 121 in November 2021 to 173 in November 2022, a 43.0% rise. Toyota became the most frequently involved make, with 27 vehicles in November 2022 compared to 12 in November 2021, while Ford's involvement slightly decreased from 14 to 13 vehicles.

Top Vehicle Makes (173 vehicles)

1
TOYOTA27 (15.6%)
125.0%prior 12
2
HONDA22 (12.7%)
100.0%prior 11
3
SUBARU18 (10.4%)
260.0%prior 5
4
FORD13 (7.5%)
-7.1%prior 14
5
CHEVROLET11 (6.4%)
37.5%prior 8
6
KIA9 (5.2%)
7
NISSAN8 (4.6%)
-20.0%prior 10
8
BMW8 (4.6%)
33.3%prior 6
9
JP4 (2.3%)
10
VOLKSWAGEN4 (2.3%)

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

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

Sex Distribution (194 persons with recorded sex)

Male119 (61.3%)
38.4%prior 86
Female75 (38.7%)
27.1%prior 59

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 65 mph speed zone saw a significant increase, rising from 8 in November 2021 to 21 in November 2022, a 162.5% increase. Crashes in the 35 mph zone also increased from 19 to 25. Conversely, crashes in the 25 mph zone decreased from 9 to 3. No fatal crashes were recorded in any speed zone during 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: WESTON, MA
  • Total crash records analyzed: 83
  • Total persons involved: 203
  • Total vehicles involved: 173

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). "WESTON, 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/weston/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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Weston, MA Crash Report — November 2022 | ThatCarHitMe.com