Monthly Traffic Safety Analysis

18 CRASHES IN
WHITMAN, MA
MAY 2023

All metrics benchmarked againstMay 2022

WHITMAN experienced a notable decrease in total crashes in May 2023 compared to May 2022, with 18 crashes versus 28 crashes, representing a 35.7% reduction. The most significant year-over-year shift was the overall reduction in crash incidents, accompanied by a decrease in crashes attributed to 'Inattention' and 'Failed to yield right of way'. However, the rate of hit-and-run crashes more than tripled during this period.

18

-35.7%was 28

Total Crash Events

0

Persons Killed

6

-14.3%was 7

Persons Injured

2

100.0%was 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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in WHITMAN showed a downward trend in May 2023 compared to May 2022, with total crashes decreasing by 35.7% from 28 to 18. This reduction was also reflected in total injuries, which decreased by 14.3% from 7 to 6. The data indicates a general improvement in traffic safety metrics for the period.

2

Hit-and-Run Crashes — May 2023

100.0% vs prior (1)

Hit-and-run crashes increased from 1 incident in May 2022 to 2 incidents in May 2023, representing a 100% increase. Consequently, the hit-and-run rate more than tripled, rising from 3.6% of all crashes in May 2022 to 11.1% in May 2023.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

5

Motorists Injured

Prior: 7-28.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted year-over-year. In May 2023, the peak day for crashes was Thursday with 6 incidents, whereas in May 2022, Monday was the peak day with 9 incidents. The peak hour for crashes also shifted, with 4 crashes occurring at 4 p.m. in May 2023, compared to 5 crashes at 5 p.m. in May 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities in either May 2023 or May 2022. The proportion of minor injury crashes increased from 14.3% (4 crashes) in May 2022 to 22.2% (4 crashes) in May 2023, despite the same count of minor injury crashes. Additionally, possible injury crashes, which were absent in May 2022, accounted for 2 crashes (11.1%) in May 2023.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes22.2%
0.0%prior 4
Possible Injury2possible injury crashes11.1%
No Injury11no injury crashes61.1%
-52.2%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record

Top Contributing Factors

The count of crashes attributed to 'No improper driving' increased from 3 in May 2022 to 6 in May 2023, representing a 100% increase. Conversely, 'Inattention' as a contributing factor saw a 44.4% decrease in count, from 9 crashes in May 2022 to 5 crashes in May 2023. 'Failed to yield right of way' also decreased by 33.3% in count, from 6 crashes to 4 crashes.

Officer-Reported Primary Contributing Cause

No improper driving6 (33.3%)
Inattention5 (27.8%)-44.4%prior 9
Failed to yield right of way4 (22.2%)-33.3%prior 6
Operating defective equipment1 (5.6%)
Visibility obstructed1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 24 in May 2022 to 13 in May 2023, while crashes on 'Dry' road surfaces decreased from 27 to 15. The proportion of crashes under 'Clear' weather conditions decreased from 85.7% to 72.2% year-over-year. Similarly, the proportion of crashes on 'Dry' road surfaces decreased from 96.4% to 83.3%, indicating a slight increase in the relative occurrence of crashes under adverse conditions.

Weather

Clear13 (72.2%)
-45.8%prior 24
Cloudy3 (16.7%)
Cloudy/Rain1 (5.6%)
Rain1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash

Lighting

Daylight17 (94.4%)
-22.7%prior 22
Dark - lighted roadway1 (5.6%)
-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field

Road Surface

Dry15 (83.3%)
-44.4%prior 27
Wet3 (16.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (35 vehicles)

1
TOYOTA6 (17.1%)
20.0%prior 5
2
FORD4 (11.4%)
-60.0%prior 10
3
NISSAN4 (11.4%)
4
HYUNDAI2 (5.7%)
5
SUBARU2 (5.7%)
6
KW1 (2.9%)
7
LINC1 (2.9%)
8
MAZDA1 (2.9%)
9
TRAI1 (2.9%)
10
VCTY1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records

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

Sex Distribution (37 persons with recorded sex)

Male24 (64.9%)
-42.9%prior 42
Female13 (35.1%)
-43.5%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 35 mph speed zone decreased significantly from 10 incidents in May 2022 to 2 incidents in May 2023. While crashes in the 40 mph zone saw a minor reduction from 6 to 5 incidents, crashes in the 45 mph zone increased from 0 to 2 incidents. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-05-01 through 2023-05-31 (31 days)
  • Geographic scope: WHITMAN, MA
  • Total crash records analyzed: 18
  • Total persons involved: 45
  • Total vehicles involved: 35

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). "WHITMAN, MA Crash Intelligence Report: May 2023." Published June 21, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/whitman/may-2023-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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Whitman, MA Crash Report — May 2023 | ThatCarHitMe.com