Monthly Traffic Safety Analysis

30 CRASHES IN
HINGHAM, MA
MARCH 2024

All metrics benchmarked againstMarch 2023

In March 2024, HINGHAM experienced 30 total crashes, marking a 36.4% increase from the 22 crashes reported in March 2023. The most significant year-over-year shift was in total injuries, which saw a substantial increase from 3 in the prior period to 17 in the current period. Fatalities remained at zero for both periods, indicating no change in the number of fatal crashes.

30

36.4%was 22

Total Crash Events

0

Persons Killed

17

466.7%was 3

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

Trend Summary

Overall, crash activity in HINGHAM trended upwards year-over-year, with total crashes increasing by 36.4% from 22 to 30. This rise was accompanied by a significant 466.7% increase in total injuries, climbing from 3 to 17. The number of fatal crashes remained stable at zero in both periods.

1

Hit-and-Run Crashes — March 2024

0.0% vs prior (1)

The number of hit-and-run crashes remained constant at 1 in both March 2023 and March 2024. Consequently, the hit-and-run rate decreased from 4.5% of total crashes in the prior period to 3.3% in the current period, reflecting a downward trend in the proportion of such incidents.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

17

Motorists Injured

Prior: 2750.0%

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 between the two periods. The peak day for crashes moved from Wednesday with 7 crashes in March 2023 to Monday with 9 crashes in March 2024. Similarly, the peak hour for crashes changed from 2 PM with 4 crashes in the prior period to 10 PM with 3 crashes in the current period.

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 fatal crashes in either March 2023 or March 2024. However, total injuries increased significantly from 3 in the prior period to 17 in the current period. The proportion of crashes resulting in minor injuries rose from 13.6% (3 crashes) to 26.7% (8 crashes), and possible injuries, not present in the prior period, accounted for 10% (3 crashes) of current period crashes.

Outcome by Severity (Crash Events)

Minor Injury8minor injury crashes26.7%
166.7%prior 3
Possible Injury3possible injury crashes10%
No Injury19no injury crashes63.3%
5.6%prior 18

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

Contributing factors saw notable changes year-over-year, with 'Inattention' increasing from 1 crash in March 2023 to 10 crashes in March 2024. 'Followed too closely,' the leading factor in the prior period with 7 crashes, was not among the listed factors for the current period. Other factors like 'No improper driving,' 'Failed to yield right of way,' 'Failure to keep in proper lane or running off road,' and 'Driving too fast for conditions' all saw increases in crash counts.

Officer-Reported Primary Contributing Cause

Inattention10 (33.3%)
No improper driving4 (13.3%)
Failed to yield right of way4 (13.3%)
Failure to keep in proper lane or running off road3 (10%)
Driving too fast for conditions2 (6.7%)
Exceeded authorized speed limit1 (3.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.3%)
Other improper action1 (3.3%)
Physical impairment1 (3.3%)
Disregarded traffic signs, signals, road markings1 (3.3%)

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

Crashes occurring in 'Clear' weather conditions remained consistent at 18 in both periods. However, crashes in 'Rain' conditions increased from 1 to 3, and 'Cloudy/Rain' conditions saw an increase from 1 to 4 crashes. For lighting, crashes in 'Dark - lighted roadway' increased from 2 to 6, and crashes on 'Wet' road surfaces increased from 2 to 10, while 'Slush' conditions were present in the prior period but not the current.

Weather

Clear18 (64.3%)
0.0%prior 18
Cloudy/Rain4 (14.3%)
Rain3 (10.7%)
Cloudy1 (3.6%)
Rain/Cloudy1 (3.6%)
Rain/Severe crosswinds1 (3.6%)

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

Lighting

Daylight19 (63.3%)
5.6%prior 18
Dark - lighted roadway6 (20.0%)
Dark - roadway not lighted4 (13.3%)
Dusk1 (3.3%)

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

Road Surface

Dry20 (66.7%)
11.1%prior 18
Wet10 (33.3%)

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 (57 vehicles)

1
TOYOTA10 (17.5%)
100.0%prior 5
2
CHEVROLET7 (12.3%)
16.7%prior 6
3
HONDA6 (10.5%)
4
JEEP5 (8.8%)
5
SUBARU4 (7%)
6
VOLKSWAGEN3 (5.3%)
7
GMC2 (3.5%)
8
HYUNDAI2 (3.5%)
9
KIA2 (3.5%)
10
LEXUS2 (3.5%)

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

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

Sex Distribution (59 persons with recorded sex)

Male32 (54.2%)
33.3%prior 24
Female27 (45.8%)
50.0%prior 18

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

The distribution of crashes across speed zones shifted, with crashes in the 30 mph zone increasing from 7 to 9 and in the 35 mph zone from 4 to 7. Additionally, crashes were reported in the 15 mph (3 crashes) and 20 mph (1 crash) zones in the current period, which were not present in the prior period. Conversely, crashes in the 60 mph zone decreased from 6 to 5.

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: HINGHAM, MA
  • Total crash records analyzed: 30
  • Total persons involved: 65
  • Total vehicles involved: 57

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). "HINGHAM, 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/hingham/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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Hingham, MA Crash Report — March 2024 | ThatCarHitMe.com