Monthly Traffic Safety Analysis

44 CRASHES IN
ABINGTON, MA
JULY 2022

All metrics benchmarked againstJuly 2021

Total crashes in ABINGTON decreased by 8.33% from 48 in July 2021 to 44 in July 2022. The most significant year-over-year shift was a 162.5% increase in total injuries, rising from 8 to 21.

44

-8.3%was 48

Total Crash Events

0

-100.0%was 1

Persons Killed

21

162.5%was 8

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. 2 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in ABINGTON decreased by 8.33% year-over-year, from 48 crashes in July 2021 to 44 crashes in July 2022. Fatalities decreased from 1 to 0, while total injuries significantly increased by 162.5%, from 8 to 21.

2

Hit-and-Run Crashes — July 2022

100.0% vs prior (1)

The number of hit-and-run crashes increased from 1 in July 2021 to 2 in July 2022. This resulted in the hit-and-run rate rising from 2.1% to 4.5% of all crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 1-100.0%

1

Pedestrians Injured

Prior: 0%

20

Motorists Injured

Prior: 8150.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Friday in both periods, though the count decreased from 14 in July 2021 to 9 in July 2022. The peak hour shifted from 3 PM with 7 crashes in July 2021 to 2 PM with 8 crashes in July 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total fatalities decreased from 1 in July 2021 to 0 in July 2022. Concurrently, total injuries increased significantly from 8 to 21. Specifically, serious injuries (severity A) rose from 0 to 2, and minor injuries (severity B) increased from 1 to 12, while possible injuries (severity C) remained stable at 7.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.3%
Minor Injury8minor injury crashes18.2%
700.0%prior 1
Possible Injury5possible injury crashes11.4%
-16.7%prior 6
No Injury28no injury crashes63.6%
-22.2%prior 36

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Most severe injury per crash record

Top Contributing Factors

The count of crashes where 'Failed to yield right of way' was a factor increased from 13 in July 2021 to 18 in July 2022, a 38.5% increase. Conversely, crashes attributed to 'Followed too closely' decreased by 66.7% in count, from 6 to 2. 'No improper driving' crashes increased by 25% from 4 to 5, while 'Inattention' remained steady at 4 crashes in both periods. 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' saw a 300% increase in count, from 1 to 4 crashes.

Officer-Reported Primary Contributing Cause

Failed to yield right of way18 (40.9%)38.5%prior 13
No improper driving5 (11.4%)
Inattention4 (9.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (9.1%)
Distracted3 (6.8%)
Followed too closely2 (4.5%)-66.7%prior 6
Glare1 (2.3%)
Fatigued/asleep1 (2.3%)
Other improper action1 (2.3%)
Failure to keep in proper lane or running off road1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 34 in July 2021 to 37 in July 2022. Notably, crashes occurring in 'Rain' or 'Rain/Cloudy' conditions, which totaled 9 in July 2021, were not observed in July 2022. The number of crashes in 'Daylight' conditions decreased slightly from 40 to 38, while 'Dark - lighted roadway' crashes decreased from 6 to 5.

Weather

Clear37 (84.1%)
8.8%prior 34
Clear/Other6 (13.6%)
Cloudy1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Weather condition at time of crash

Lighting

Daylight38 (86.4%)
-5.0%prior 40
Dark - lighted roadway5 (11.4%)
-16.7%prior 6
Dark - roadway not lighted1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Lighting condition field

Vehicles & Demographics

Toyota became the most frequently involved make in crashes, increasing from 13 in July 2021 to 16 in July 2022, while Ford's involvement decreased slightly from 14 to 13. The age group 0-15 saw an increase in person involvement from 3 to 9, and the 16-20 age group also increased from 9 to 10. Conversely, the 21-25 age group experienced a decrease in involvement from 16 to 4 persons.

Top Vehicle Makes (78 vehicles)

1
TOYOTA16 (20.5%)
23.1%prior 13
2
FORD13 (16.7%)
-7.1%prior 14
3
HONDA8 (10.3%)
4
CHEVROLET6 (7.7%)
-33.3%prior 9
5
NISSAN5 (6.4%)
-50.0%prior 10
6
JEEP4 (5.1%)
-20.0%prior 5
7
GMC3 (3.8%)
8
CHRYSLER3 (3.8%)
9
MERCEDES-BENZ2 (2.6%)
10
HYUNDAI2 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Vehicle unit records

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

Sex Distribution (86 persons with recorded sex)

Male46 (53.5%)
-8.0%prior 50
Female40 (46.5%)
-11.1%prior 45

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone increased from 15 in July 2021 to 16 in July 2022. Crashes in the 35 mph zone decreased from 15 to 10, and in the 40 mph zone from 10 to 5. The 30 mph zone recorded 1 fatal crash in July 2021, while no fatal crashes were reported in any speed zone in July 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · 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: 2022-07-01 through 2022-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-07-01 through 2022-07-31 (31 days)
  • Geographic scope: ABINGTON, MA
  • Total crash records analyzed: 44
  • Total persons involved: 97
  • Total vehicles involved: 78

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). "ABINGTON, MA Crash Intelligence Report: July 2022." Published June 21, 2026. Reporting period: 2022-07-01 to 2022-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/abington/july-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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Abington, MA Crash Report — July 2022 | ThatCarHitMe.com