Monthly Traffic Safety Analysis

18 CRASHES IN
ASHLAND, MA
APRIL 2022

All metrics benchmarked againstApril 2021

In April 2022, Ashland experienced 18 total crashes, a 10% decrease from the 20 crashes recorded in April 2021. Total injuries saw a significant reduction, falling by 50% from 4 injuries in the prior year to 2 injuries in the current period. Fatalities remained at zero in both periods.

18

-10.0%was 20

Total Crash Events

0

Persons Killed

2

-50.0%was 4

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in Ashland showed a downward trend year-over-year. Total crashes decreased by 10%, from 20 in April 2021 to 18 in April 2022. This reduction was accompanied by a 50% decrease in total injuries, falling from 4 to 2.

1

Hit-and-Run Crashes — April 2022

0.0% vs prior (1)

The number of hit-and-run crashes remained stable at 1 in both April 2021 and April 2022. However, the hit-and-run rate slightly increased from 5% of total crashes in the prior period to 5.6% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 4-50.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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 Friday with 5 crashes in April 2021 to Thursday with 6 crashes in April 2022. While the peak hour remained 4p in both periods, the number of crashes at this hour decreased from 4 in April 2021 to 2 in April 2022. Monday crashes decreased from 2 to 0, while Thursday crashes increased from 3 to 6.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both April 2021 and April 2022. Total injuries decreased from 4 to 2, with possible injuries (C) reported in 3 crashes in April 2021 but not in April 2022. The proportion of crashes resulting in no injury increased from 75% in April 2021 to 83.3% in April 2022, while minor injury crashes increased from 1 to 2.

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes11.1%
100.0%prior 1
No Injury15no injury crashes83.3%
0.0%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'Failed to yield right of way', increased from 1 crash in April 2021 to 4 crashes in April 2022. Conversely, crashes attributed to 'No improper driving' decreased significantly from 6 to 2 crashes year-over-year. 'Inattention' also saw an increase from 2 crashes to 3 crashes, and 'Followed too closely' increased from 1 crash to 2 crashes.

Officer-Reported Primary Contributing Cause

Failed to yield right of way4 (22.2%)
Inattention3 (16.7%)
Failure to keep in proper lane or running off road2 (11.1%)
No improper driving2 (11.1%)-66.7%prior 6
Followed too closely2 (11.1%)
Fatigued/asleep1 (5.6%)
Illness1 (5.6%)
Other improper action1 (5.6%)
Distracted1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Rain' conditions increased from 1 in April 2021 to 2 in April 2022. The number of crashes on 'Dry' road surfaces decreased from 19 to 16, while crashes on 'Wet' surfaces increased from 1 to 2. There was no data available for lighting conditions in April 2021.

Weather

Clear15 (83.3%)
0.0%prior 15
Rain2 (11.1%)
Clear/Other1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Weather condition at time of crash

Lighting

Daylight13 (72.2%)
Dark - lighted roadway3 (16.7%)
Dawn1 (5.6%)
Other1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Lighting condition field

Road Surface

Dry16 (88.9%)
-15.8%prior 19
Wet2 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (32 vehicles)

1
FORD8 (25%)
0.0%prior 8
2
TOYOTA5 (15.6%)
-37.5%prior 8
3
HONDA4 (12.5%)
-60.0%prior 10
4
CHEVROLET3 (9.4%)
-40.0%prior 5
5
OTH1 (3.1%)
6
SUBARU1 (3.1%)
7
VOLKSWAGEN1 (3.1%)
8
ACURA1 (3.1%)
9
VOLVO1 (3.1%)
10
CHRYSLER1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Vehicle unit records

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

Sex Distribution (33 persons with recorded sex)

Male22 (66.7%)
-12.0%prior 25
Female11 (33.3%)
-31.3%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone increased from 3 in April 2021 to 4 in April 2022, while crashes in the 30 mph zone decreased from 4 to 3. The 35 mph zone remained stable with 10 crashes in both periods. There were no fatal crashes reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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: 2022-04-01 through 2022-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-04-01 through 2022-04-30 (30 days)
  • Geographic scope: ASHLAND, MA
  • Total crash records analyzed: 18
  • Total persons involved: 34
  • Total vehicles involved: 32

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). "ASHLAND, MA Crash Intelligence Report: April 2022." Published June 21, 2026. Reporting period: 2022-04-01 to 2022-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/ashland/april-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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Ashland, MA Crash Report — April 2022 | ThatCarHitMe.com