Monthly Traffic Safety Analysis

15 CRASHES IN
UPTON, MA
NOVEMBER 2022

All metrics benchmarked againstNovember 2021

In November 2022, Upton experienced 15 total crashes, a substantial increase of 114.29% compared to the 7 crashes reported in November 2021. Concurrently, total injuries rose from 1 in November 2021 to 5 in November 2022, marking a 400% increase year-over-year. A notable shift includes the appearance of 2 DUI crashes in the current period, compared to none in the prior period.

15

114.3%was 7

Total Crash Events

0

Persons Killed

5

400.0%was 1

Persons Injured

0

Fatal Crash Events

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

Overall, crash activity in Upton showed a significant upward trend from November 2021 to November 2022. Total crashes more than doubled, increasing by 114.29% from 7 to 15, while total injuries saw an even steeper rise, climbing by 400% from 1 to 5.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 1400.0%

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 temporal distribution of crashes shifted year-over-year, with the peak day moving from Thursday in November 2021 (2 crashes) to Wednesday in November 2022 (5 crashes). The peak hour for crashes also changed, occurring at 7 AM with 3 crashes in November 2021, and shifting to 6 AM, also with 3 crashes, in November 2022.

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. However, total injuries increased from 1 in the prior period to 5 in the current period, with the proportion of crashes resulting in injury rising from 14.3% (1 of 7 crashes) to 20% (3 of 15 crashes). The current period also saw 1 serious injury crash and 2 minor injury crashes, compared to only 1 possible injury crash in the prior period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes6.7%
Minor Injury2minor injury crashes13.3%
No Injury12no injury crashes80%
100.0%prior 6

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 factor, 'Inattention,' saw a significant increase in crash count, rising from 1 crash in November 2021 to 5 crashes in November 2022. 'No improper driving' also increased from 2 crashes to 3 crashes year-over-year. 'Failed to yield right of way' remained consistent with 1 crash in both periods, while 'Followed too closely' (1 crash) from the prior period was not a top factor in the current period. New factors appearing in the current period include 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' (2 crashes), 'Over-correcting/over-steering' (1 crash), 'Distracted' (1 crash), and 'Fatigued/asleep' (1 crash).

Officer-Reported Primary Contributing Cause

Inattention5 (33.3%)
No improper driving3 (20%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (13.3%)
Over-correcting/over-steering1 (6.7%)
Distracted1 (6.7%)
Failed to yield right of way1 (6.7%)
Fatigued/asleep1 (6.7%)

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

Regarding lighting conditions, crashes occurring during daylight increased from 4 in November 2021 to 9 in November 2022. Crashes in 'Dark - lighted roadway' conditions also rose from 1 to 3, while 'Dark - roadway not lighted' and 'Dawn' conditions each accounted for 1 crash in both periods. The data for weather and road surface conditions was not available for comparison in the prior period.

Weather

Clear13 (86.7%)
Cloudy1 (6.7%)
Rain1 (6.7%)

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

Lighting

Daylight9 (60.0%)
Dark - lighted roadway3 (20.0%)
Dark - roadway not lighted1 (6.7%)
Dawn1 (6.7%)
Other1 (6.7%)

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

Road Surface

Dry12 (80.0%)
Wet2 (13.3%)
Water (standing, moving)1 (6.7%)

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

Vehicles & Demographics

Top Vehicle Makes (25 vehicles)

1
FORD6 (24%)
2
TOYOTA4 (16%)
3
NISSAN3 (12%)
4
JEEP2 (8%)
5
CHEVROLET2 (8%)
6
HONDA2 (8%)
7
HYUNDAI1 (4%)
8
DODGE1 (4%)
9
GMC1 (4%)
10
CADI1 (4%)

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

Sex Distribution (30 persons with recorded sex)

Female16 (53.3%)
45.5%prior 11
Male14 (46.7%)
100.0%prior 7

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

Crash distribution across speed zones showed a notable shift, with the current period recording crashes in higher speed limit zones of 45 mph (2 crashes) and 65 mph (2 crashes), which were not present in the prior period. The 40 mph zone saw an increase from 2 crashes in November 2021 to 3 crashes in November 2022. 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: UPTON, MA
  • Total crash records analyzed: 15
  • Total persons involved: 30
  • Total vehicles involved: 25

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). "UPTON, 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/upton/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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Upton, MA Crash Report — November 2022 | ThatCarHitMe.com