Monthly Traffic Safety Analysis

18 CRASHES IN
UPTON, MA
OCTOBER 2024

All metrics benchmarked againstOctober 2023

In October 2024, Upton experienced 18 crashes, an increase of 5.9% compared to the 17 crashes reported in October 2023. The most notable shift was a 150% increase in total injuries, rising from 2 in the prior period to 5 in the current period.

18

5.9%was 17

Total Crash Events

0

Persons Killed

5

150.0%was 2

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 · 2024-10-01 to 2024-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash activity in Upton showed a slight upward trend, with total crashes increasing by 5.9% from 17 in October 2023 to 18 in October 2024. While fatalities remained at 0 in both periods, total injuries significantly rose by 150%, from 2 to 5.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 2150.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · 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. In October 2024, Thursday became the peak day with 8 crashes, a substantial increase from 1 crash on Thursdays in October 2023, which had Wednesday as its peak day with 5 crashes. The peak hour also shifted from 5 PM with 5 crashes in the prior period to 4 PM with 5 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity patterns changed, with total injuries increasing by 150% from 2 in October 2023 to 5 in October 2024. The current period recorded 1 serious injury crash (5.6% of total crashes), whereas no serious injury crashes were reported in the prior period. Possible injury crashes increased from 1 (5.9% share) to 2 (11.1% share) year-over-year.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes5.6%
Minor Injury1minor injury crashes5.6%
0.0%prior 1
Possible Injury2possible injury crashes11.1%
100.0%prior 1
No Injury14no injury crashes77.8%
-6.7%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Most severe injury per crash record

Top Contributing Factors

Analysis of contributing factors reveals shifts in crash causation. Inattention, previously the highest factor with 5 crashes, decreased to 3 crashes in the current period, representing a 40% reduction in count. Conversely, 'No improper driving' crashes increased by 200%, from 1 in the prior period to 3 in the current period, and 'Glare' emerged as a factor with 2 crashes in the current period, not present in the prior.

Officer-Reported Primary Contributing Cause

Inattention3 (16.7%)-40.0%prior 5
No improper driving3 (16.7%)
Glare2 (11.1%)
Failure to keep in proper lane or running off road1 (5.6%)
Fatigued/asleep1 (5.6%)
Distracted1 (5.6%)
Exceeded authorized speed limit1 (5.6%)
Driving too fast for conditions1 (5.6%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (5.6%)
Visibility obstructed1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Lighting conditions showed notable changes year-over-year. Crashes occurring in daylight decreased from 15 in October 2023 to 11 in October 2024. The current period saw 4 crashes in 'Dark - roadway not lighted' conditions and 2 crashes in 'Dark - lighted roadway' conditions, categories that were not present in the prior period's data. Additionally, 'Dawn' crashes, which accounted for 1 crash in the prior period, were not reported in the current period.

Lighting

Daylight11 (61.1%)
-26.7%prior 15
Dark - roadway not lighted4 (22.2%)
Dark - lighted roadway2 (11.1%)
Dark - unknown roadway lighting1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Lighting condition field

Vehicles & Demographics

Top Vehicle Makes (31 vehicles)

1
FORD9 (29%)
2
TOYOTA3 (9.7%)
3
VOLKSWAGEN2 (6.5%)
4
HD2 (6.5%)
5
HONDA2 (6.5%)
6
JEEP2 (6.5%)
7
KIA2 (6.5%)
8
JAGU1 (3.2%)
9
GMC1 (3.2%)
10
CHEVROLET1 (3.2%)
-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Vehicle unit records

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

Sex Distribution (37 persons with recorded sex)

Female19 (51.4%)
111.1%prior 9
Male18 (48.6%)
-5.3%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crash distribution across speed limits changed, with crashes in 30 mph zones increasing from 7 in October 2023 to 9 in October 2024. Crashes in 40 mph zones decreased by 50%, from 2 to 1. Notably, 2 crashes occurred in 5 mph zones in the current period, a category not present in the prior period, while 2 crashes in 65 mph zones from the prior period were absent in the current data.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · 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: 2024-10-01 through 2024-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-10-01 through 2024-10-31 (31 days)
  • Geographic scope: UPTON, MA
  • Total crash records analyzed: 18
  • Total persons involved: 39
  • Total vehicles involved: 31

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: October 2024." Published June 21, 2026. Reporting period: 2024-10-01 to 2024-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/upton/october-2024-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 — October 2024 | ThatCarHitMe.com