Monthly Traffic Safety Analysis

18 CRASHES IN
WHITMAN, MA
MARCH 2024

All metrics benchmarked againstMarch 2023

WHITMAN experienced a slight increase in total crashes in March 2024, with 18 crashes compared to 17 in March 2023, representing a 5.9% rise. The most notable shift was the doubling of hit-and-run crashes, increasing from 1 in March 2023 to 2 in March 2024, causing the hit-and-run rate to rise from 5.9% to 11.1%.

18

5.9%was 17

Total Crash Events

0

Persons Killed

3

50.0%was 2

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 · 2024-03-01 to 2024-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in WHITMAN saw a slight increase year-over-year, with total crashes rising by 5.9% from 17 in March 2023 to 18 in March 2024. Total injuries also increased by 50%, from 2 in March 2023 to 3 in March 2024, while fatalities remained at zero in both periods.

2

Hit-and-Run Crashes — March 2024

100.0% vs prior (1)

Hit-and-run crashes doubled year-over-year, increasing from 1 incident in March 2023 to 2 incidents in March 2024. This resulted in the hit-and-run rate rising from 5.9% of total crashes in March 2023 to 11.1% in March 2024, indicating an upward trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

3

Motorists Injured

Prior: 250.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · 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 significantly year-over-year. The peak day for crashes moved from Wednesday with 6 incidents in March 2023 to Saturday with 6 incidents in March 2024. The peak hour for crashes also shifted from 7 AM with 4 incidents in March 2023 to 2 PM with 4 incidents in March 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either March 2023 or March 2024. Total injuries increased by 50%, from 2 in the prior period to 3 in the current period. While March 2023 recorded 2 minor injury crashes (11.8% of total), March 2024 reported 2 possible injury crashes (11.1% of total crashes).

Outcome by Severity (Crash Events)

Possible Injury2possible injury crashes11.1%
No Injury15no injury crashes83.3%
0.0%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'No improper driving' saw a substantial increase, rising from 1 incident in March 2023 to 5 incidents in March 2024, a 400% increase. 'Inattention' crashes increased by 33.3%, from 3 in the prior period to 4 in the current period, while 'Followed too closely' crashes increased by 50%, from 2 to 3. Conversely, 'Failed to yield right of way' crashes decreased by 50%, from 2 to 1.

Officer-Reported Primary Contributing Cause

No improper driving5 (27.8%)
Inattention4 (22.2%)
Followed too closely3 (16.7%)
Failed to yield right of way1 (5.6%)
Failure to keep in proper lane or running off road1 (5.6%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Daylight conditions remained the most common for crashes, with 13 incidents in both March 2023 and March 2024. Wet road surface crashes increased from 3 in March 2023 to 5 in March 2024. Rain-related weather conditions (including 'Rain', 'Cloudy/Rain', 'Rain/Cloudy') increased from 1 crash in March 2023 to 5 crashes in March 2024.

Weather

Clear11 (61.1%)
-8.3%prior 12
Rain3 (16.7%)
Clear/Unknown1 (5.6%)
Cloudy1 (5.6%)
Cloudy/Rain1 (5.6%)
Rain/Cloudy1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Weather condition at time of crash

Lighting

Daylight13 (72.2%)
0.0%prior 13
Dark - lighted roadway3 (16.7%)
Dusk2 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Lighting condition field

Road Surface

Dry13 (72.2%)
0.0%prior 13
Wet5 (27.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (33 vehicles)

1
CHEVROLET6 (18.2%)
0.0%prior 6
2
NISSAN4 (12.1%)
3
FORD4 (12.1%)
4
TOYOTA3 (9.1%)
-57.1%prior 7
5
CHRYSLER3 (9.1%)
6
GMC2 (6.1%)
7
MERCEDES-BENZ2 (6.1%)
8
HYUNDAI1 (3%)
9
DODGE1 (3%)
10
HONDA1 (3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Vehicle unit records

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

Sex Distribution (45 persons with recorded sex)

Female26 (57.8%)
85.7%prior 14
Male19 (42.2%)
-17.4%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 35 mph speed zones saw a significant increase, rising by 200% from 2 incidents in March 2023 to 6 incidents in March 2024. Conversely, crashes in 30 mph speed zones decreased by 50%, from 4 to 2 incidents. There were no fatalities recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · 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: 2024-03-01 through 2024-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-03-01 through 2024-03-31 (31 days)
  • Geographic scope: WHITMAN, MA
  • Total crash records analyzed: 18
  • Total persons involved: 47
  • Total vehicles involved: 33

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: March 2024." Published June 21, 2026. Reporting period: 2024-03-01 to 2024-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/whitman/march-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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Whitman, MA Crash Report — March 2024 | ThatCarHitMe.com