Monthly Traffic Safety Analysis

12 CRASHES IN
ASHLAND, MA
JUNE 2023

All metrics benchmarked againstJune 2022

ASHLAND experienced a stable number of total crashes in June 2023 compared to June 2022, with 12 crashes recorded in both periods, representing a 0% change. Total fatalities and injuries also remained unchanged year-over-year. A notable shift includes the appearance of one DUI-related crash in the current period, where none were reported in the prior period.

12

Total Crash Events

0

Persons Killed

2

Persons Injured

0

Fatal Crash Events

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 · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend for crashes in ASHLAND remained stable, with total crashes holding at 12 for both June 2023 and June 2022. Total fatalities and total injuries also showed no change, remaining at 0 and 2 respectively for both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 1100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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. In June 2023, the peak day for crashes was Friday with 3 incidents, while in June 2022, Tuesday was the peak day with 4 crashes. The peak hour also shifted from 5 PM with 2 crashes in the prior period to 6 PM with 4 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution of crashes saw minor changes, with no fatal crashes reported in either period. In June 2023, there was 1 minor injury and 1 possible injury crash, while June 2022 recorded 2 minor injury crashes. The proportion of crashes resulting in no injury remained stable at 75% for both periods.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes8.3%
-50.0%prior 2
Possible Injury1possible injury crashes8.3%
No Injury9no injury crashes75%
0.0%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors observed a shift year-over-year. 'Followed too closely' emerged as the top factor in June 2023 with 3 crashes, a factor not present in the prior period's top list. Conversely, 'Inattention' decreased from 3 crashes in June 2022 to 1 crash in June 2023, representing a 66.7% decrease in count, and 'No improper driving' decreased from 2 crashes to 1 crash, a 50% decrease in count.

Officer-Reported Primary Contributing Cause

Followed too closely3 (25%)
Failed to yield right of way1 (8.3%)
No improper driving1 (8.3%)
Physical impairment1 (8.3%)
Inattention1 (8.3%)
Failure to keep in proper lane or running off road1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Weather conditions for crashes showed a shift, with 'Clear' conditions decreasing from 9 crashes in June 2022 to 7 crashes in June 2023, while 'Cloudy' conditions increased from 1 to 4 crashes. Regarding lighting, 'Daylight' crashes decreased from 11 to 8, and 'Dusk' conditions, which were not present in June 2022, accounted for 2 crashes in June 2023. Road surface conditions saw 'Wet' conditions appear in June 2023 with 1 crash, replacing 'Sand, mud, dirt, oil, gravel' from the prior period.

Weather

Clear7 (58.3%)
-22.2%prior 9
Cloudy4 (33.3%)
Cloudy/Rain1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash

Lighting

Daylight8 (66.7%)
-27.3%prior 11
Dark - lighted roadway2 (16.7%)
Dusk2 (16.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field

Road Surface

Dry11 (91.7%)
0.0%prior 11
Wet1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (24 vehicles)

1
TOYOTA5 (20.8%)
2
HONDA4 (16.7%)
3
HYUNDAI3 (12.5%)
4
FORD3 (12.5%)
5
LEXUS2 (8.3%)
6
NISSAN2 (8.3%)
7
DODGE1 (4.2%)
8
JEEP1 (4.2%)
9
SUBARU1 (4.2%)
10
BMW1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Vehicle unit records

Sex Distribution (23 persons with recorded sex)

Male13 (56.5%)
44.4%prior 9
Female10 (43.5%)
-16.7%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones changed, with crashes at 5 mph (1 crash) and 30 mph (3 crashes) appearing in June 2023, which were not present in June 2022. Crashes at 10 mph (1 crash) and 65 mph (1 crash) observed in June 2022 were not recorded in June 2023. The number of crashes in 25 mph zones decreased from 5 to 4, and in 35 mph zones from 5 to 4. No fatal crashes were recorded in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-06-01 through 2023-06-30 (30 days)
  • Geographic scope: ASHLAND, MA
  • Total crash records analyzed: 12
  • Total persons involved: 24
  • Total vehicles involved: 24

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: June 2023." Published June 21, 2026. Reporting period: 2023-06-01 to 2023-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/ashland/june-2023-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 — June 2023 | ThatCarHitMe.com