Monthly Traffic Safety Analysis

52 CRASHES IN
HINGHAM, MA
MAY 2022

All metrics benchmarked againstMay 2021

Total crashes in Hingham, MA increased by 10.64%, from 47 in May 2021 to 52 in May 2022. A significant shift was observed in crash outcomes, with fatalities rising from 0 to 1 in the current period, while total injuries decreased by 66.67%.

52

10.6%was 47

Total Crash Events

1

Persons Killed

8

-66.7%was 24

Persons Injured

3

200.0%was 1

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 3 crashes with unreported severity are not shown in the severity breakdown.

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

Overall, crashes in Hingham, MA showed an upward trend, increasing by 10.64% from 47 in May 2021 to 52 in May 2022. While total fatalities rose from 0 to 1, total injuries decreased substantially from 24 to 8, marking a 66.67% reduction year-over-year.

3

Hit-and-Run Crashes — May 2022

200.0% vs prior (1)

Hit-and-run crashes increased from 1 in May 2021 to 3 in May 2022. This change resulted in an increase in the hit-and-run rate from 2.1% of total crashes to 5.8% of total crashes.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

8

Motorists Injured

Prior: 22-63.6%

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 peak day for crashes shifted from Thursday in May 2021, with 15 incidents, to Saturday and Sunday in May 2022, each recording 10 incidents. Similarly, the peak hour for crashes moved from 12 PM (10 crashes) in the prior period to 10 AM (6 crashes) in the current period.

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

The current period recorded 1 fatal crash, resulting in 1 fatality, compared to zero fatal crashes and zero fatalities in the prior period. Total injuries saw a substantial decrease from 24 in May 2021 to 8 in May 2022. Minor injuries, specifically, decreased from 10 crashes (21.3% share) to 3 crashes (5.8% share).

Outcome by Severity (Crash Events)

Fatal1fatal crashes1.9%
Serious Injury1serious injury crashes1.9%
0.0%prior 1
Minor Injury3minor injury crashes5.8%
-70.0%prior 10
Possible Injury2possible injury crashes3.8%
-66.7%prior 6
No Injury42no injury crashes80.8%
44.8%prior 29

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

Crashes attributed to "Inattention" increased significantly, with counts rising from 9 in the prior period to 19 in the current period. Conversely, "Followed too closely" crashes decreased from 9 to 3, and "Failed to yield right of way" crashes decreased from 9 to 7. "Inattention" became the leading contributing factor in May 2022, while "Followed too closely" dropped in its ranking.

Officer-Reported Primary Contributing Cause

Inattention19 (36.5%)111.1%prior 9
Failed to yield right of way7 (13.5%)-22.2%prior 9
No improper driving5 (9.6%)-28.6%prior 7
Other improper action4 (7.7%)
Followed too closely3 (5.8%)-66.7%prior 9
Over-correcting/over-steering3 (5.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (3.8%)
Distracted2 (3.8%)
Disregarded traffic signs, signals, road markings1 (1.9%)
Failure to keep in proper lane or running off road1 (1.9%)

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 on wet road surfaces significantly decreased from 7 in May 2021 to 1 in May 2022. Crashes during daylight conditions saw a slight decrease from 44 to 42, while crashes in dark conditions (including lighted, unlighted, and unknown roadway lighting) collectively increased from 1 to 9.

Weather

Clear47 (90.4%)
17.5%prior 40
Cloudy3 (5.8%)
Clear/Unknown1 (1.9%)
Cloudy/Rain1 (1.9%)

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

Lighting

Daylight42 (80.8%)
-4.5%prior 44
Dark - lighted roadway7 (13.5%)
Dark - roadway not lighted1 (1.9%)
Dark - unknown roadway lighting1 (1.9%)
Dusk1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Lighting condition field

Road Surface

Dry51 (98.1%)
27.5%prior 40
Wet1 (1.9%)
-85.7%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Road surface condition field

Vehicles & Demographics

Toyota became the most frequently involved vehicle make, with its count rising from 9 in May 2021 to 21 in May 2022, while Nissan involvement decreased from 9 to 5. The number of persons aged 16-20 involved in crashes increased from 10 to 23, whereas persons aged 65+ decreased from 26 to 14.

Top Vehicle Makes (99 vehicles)

1
TOYOTA21 (21.2%)
133.3%prior 9
2
FORD11 (11.1%)
22.2%prior 9
3
HONDA9 (9.1%)
0.0%prior 9
4
NISSAN5 (5.1%)
-44.4%prior 9
5
JEEP4 (4%)
-50.0%prior 8
6
CHEVROLET4 (4%)
-50.0%prior 8
7
VOLVO3 (3%)
8
HYUNDAI3 (3%)
9
SUBARU3 (3%)
10
AUDI3 (3%)

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

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

Sex Distribution (100 persons with recorded sex)

Male52 (52.0%)
-5.5%prior 55
Female48 (48.0%)
-18.6%prior 59

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 occurring in 30 mph speed zones increased from 14 in May 2021 to 18 in May 2022. Conversely, crashes in 60 mph zones decreased from 10 to 7. Notably, a fatal crash was recorded in a 60 mph zone in the current period, a category that had no fatalities in the prior period.

Fatal crashes by zone: 60 mph: 1 of 7 (14.286%)

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: HINGHAM, MA
  • Total crash records analyzed: 52
  • Total persons involved: 120
  • Total vehicles involved: 99

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: 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/hingham/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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Hingham, MA Crash Report — May 2022 | ThatCarHitMe.com