Monthly Traffic Safety Analysis

8 CRASHES IN
TEMPLETON, MA
MAY 2022

All metrics benchmarked againstMay 2021

Total crashes in TEMPLETON decreased by 52.94% year-over-year, from 17 crashes in May 2021 to 8 crashes in May 2022. This significant reduction in overall crash incidents is accompanied by a substantial decrease in reported injuries, falling from 10 to 1. This marks a positive shift in traffic safety outcomes for the area.

8

-52.9%was 17

Total Crash Events

0

Persons Killed

1

-90.0%was 10

Persons Injured

1

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 · 2022-05-01 to 2022-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend for May 2022 in TEMPLETON indicates a notable decrease in crash activity compared to May 2021. Total crashes declined by 52.94%, from 17 to 8, while total injuries also saw a significant reduction, dropping from 10 to 1. Fatalities remained at zero in both periods.

1

Hit-and-Run Crashes — May 2022

12.5% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 10-90.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · 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, with the peak day moving from Friday in May 2021 (4 crashes) to Wednesday in May 2022 (4 crashes). Similarly, the peak hour for crashes shifted from 9 PM in May 2021 (3 crashes) to 4 PM in May 2022 (4 crashes). In May 2022, crashes were more concentrated on Wednesday afternoons, whereas May 2021 saw a more spread-out pattern throughout the week and later in the evening.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both May 2021 and May 2022. Total reported injuries decreased substantially from 10 in May 2021 to 1 in May 2022. Serious injury crashes (severity code A) decreased from 2 crashes in May 2021 to 1 crash in May 2022, while minor and possible injury crashes reported in May 2021 were absent in May 2022. The proportion of "No Injury" crashes increased from 64.7% of total crashes in May 2021 to 87.5% in May 2022.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes12.5%
-50.0%prior 2
No Injury7no injury crashes87.5%
-36.4%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Most severe injury per crash record

Top Contributing Factors

The most frequently cited contributing factor in May 2022 was "No improper driving," accounting for 6 crashes, which was the same count as in May 2021, but represented an increased share from 35.3% to 75% of total crashes. "Inattention" decreased in count from 3 crashes in May 2021 to 1 crash in May 2022, while "Distracted" remained at 1 crash in both periods. Several other factors, such as "Failure to keep in proper lane or running off road" and "Followed too closely," which were present in May 2021, were not observed in May 2022.

Officer-Reported Primary Contributing Cause

No improper driving6 (75%)0.0%prior 6
Distracted1 (12.5%)
Inattention1 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather decreased from 14 in May 2021 to 6 in May 2022, while crashes in cloudy conditions remained consistent at 2 in both periods. The "Cloudy/Rain" condition, which accounted for 1 crash in May 2021, was not reported in May 2022. Information on lighting and road surface conditions was not available for May 2022, preventing a year-over-year comparison for these categories.

Weather

Clear6 (75.0%)
-57.1%prior 14
Cloudy2 (25.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Weather condition at time of crash

Vehicles & Demographics

Top Vehicle Makes (13 vehicles)

1
NISSAN2 (15.4%)
2
HONDA2 (15.4%)
3
TOYOTA2 (15.4%)
-60.0%prior 5
4
CHEVROLET2 (15.4%)
-75.0%prior 8
5
SUBARU1 (7.7%)
6
DODGE1 (7.7%)
7
INFI1 (7.7%)
8
MAZDA1 (7.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Vehicle unit records

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

Sex Distribution (13 persons with recorded sex)

Female9 (69.2%)
-18.2%prior 11
Male4 (30.8%)
-81.0%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes decreased across most speed limit zones year-over-year. The 35 mph zone saw a decrease from 4 crashes to 2, the 40 mph zone from 5 crashes to 3, and the 55 mph zone from 3 crashes to 1. Crashes in the 30 mph zone, which had 3 incidents in May 2021, were not reported in May 2022, while the 45 mph zone maintained 2 crashes in both periods. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · 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: 2022-05-01 through 2022-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-05-01 through 2022-05-31 (31 days)
  • Geographic scope: TEMPLETON, MA
  • Total crash records analyzed: 8
  • Total persons involved: 14
  • Total vehicles involved: 13

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). "TEMPLETON, MA Crash Intelligence Report: May 2022." Published June 21, 2026. Reporting period: 2022-05-01 to 2022-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/templeton/may-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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Templeton, MA Crash Report — May 2022 | ThatCarHitMe.com