Monthly Traffic Safety Analysis

18 CRASHES IN
UPTON, MA
MAY 2024

All metrics benchmarked againstMay 2023

In May 2024, Upton experienced 18 crashes, a 10% decrease from the 20 crashes reported in May 2023. Total injuries saw a slight increase from 6 to 7, representing a 16.7% rise. The most notable year-over-year shift was the 75% reduction in crashes where 'No improper driving' was cited as a contributing factor, decreasing from 8 to 2 incidents.

18

-10.0%was 20

Total Crash Events

0

Persons Killed

7

16.7%was 6

Persons Injured

1

-50.0%was 2

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 · 2024-05-01 to 2024-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the number of crashes in Upton decreased by 10%, from 20 in May 2023 to 18 in May 2024. Fatalities remained stable at 0 in both periods. However, total injuries increased by 16.7%, rising from 6 injuries in May 2023 to 7 injuries in May 2024.

1

Hit-and-Run Crashes — May 2024

-50.0% vs prior (2)

Hit-and-run crashes decreased from 2 incidents in May 2023 to 1 incident in May 2024, representing a 50% reduction. Correspondingly, the hit-and-run rate decreased from 10% of all crashes in May 2023 to 5.6% in May 2024, indicating a downward trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

7

Motorists Injured

Prior: 616.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Friday in May 2023 (5 crashes) to Saturday in May 2024 (5 crashes). The peak hour for crashes remained 3 PM in both periods, although the count decreased from 5 crashes in May 2023 to 4 crashes in May 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at 0 in both May 2023 and May 2024. The current period saw 1 serious injury crash, which was not present in the prior period. Minor injury crashes decreased from 4 in May 2023 to 2 in May 2024, while possible injury crashes increased from 1 to 3 over the same period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes5.6%
Minor Injury2minor injury crashes11.1%
-50.0%prior 4
Possible Injury3possible injury crashes16.7%
200.0%prior 1
No Injury12no injury crashes66.7%
-7.7%prior 13

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'No improper driving' decreased significantly from 8 in May 2023 to 2 in May 2024, a 75% reduction in count. 'Inattention' as a contributing factor increased by 50%, rising from 4 crashes to 6 crashes. Additionally, 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' was cited in 3 crashes in May 2024, a factor not among the top contributors in May 2023.

Officer-Reported Primary Contributing Cause

Inattention6 (33.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (16.7%)
No improper driving2 (11.1%)-75.0%prior 8
Failed to yield right of way2 (11.1%)
Followed too closely2 (11.1%)
Wrong side or wrong way1 (5.6%)
Fatigued/asleep1 (5.6%)
Distracted1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Clear weather conditions were associated with 16 crashes in May 2024, a decrease from 19 crashes in May 2023. Crashes occurring during daylight hours decreased from 17 in May 2023 to 14 in May 2024. The prior period had 1 crash during dusk, while the current period reported 1 crash during dawn.

Weather

Clear16 (88.9%)
-15.8%prior 19
Rain1 (5.6%)
Rain/Cloudy1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Weather condition at time of crash

Lighting

Daylight14 (77.8%)
-17.6%prior 17
Dark - lighted roadway2 (11.1%)
Dark - roadway not lighted1 (5.6%)
Dawn1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Lighting condition field

Road Surface

Dry16 (88.9%)
Wet2 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (30 vehicles)

1
FORD5 (16.7%)
2
CHEVROLET4 (13.3%)
-20.0%prior 5
3
TOYOTA4 (13.3%)
-20.0%prior 5
4
HONDA3 (10%)
-50.0%prior 6
5
DODGE3 (10%)
6
RAM2 (6.7%)
7
NISSAN1 (3.3%)
8
ACURA1 (3.3%)
9
VOLKSWAGEN1 (3.3%)
10
BMW1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Vehicle unit records

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

Sex Distribution (36 persons with recorded sex)

Male25 (69.4%)
47.1%prior 17
Female11 (30.6%)
-38.9%prior 18

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 mph speed zones decreased from 12 in May 2023 to 7 in May 2024. Conversely, crashes in 40 mph speed zones increased from 2 to 5 between the two periods. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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: 2024-05-01 through 2024-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-05-01 through 2024-05-31 (31 days)
  • Geographic scope: UPTON, MA
  • Total crash records analyzed: 18
  • Total persons involved: 38
  • Total vehicles involved: 30

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: May 2024." Published June 21, 2026. Reporting period: 2024-05-01 to 2024-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/upton/may-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 — May 2024 | ThatCarHitMe.com