Monthly Traffic Safety Analysis

23 CRASHES IN
ASHLAND, MA
DECEMBER 2023

All metrics benchmarked againstDecember 2022

In December 2023, Ashland recorded 23 total crashes, a decrease of 8% compared to the 25 crashes reported in December 2022. A notable shift was the 36.4% reduction in total injuries, falling from 11 to 7 year-over-year.

23

-8.0%was 25

Total Crash Events

0

Persons Killed

7

-36.4%was 11

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 · 2023-12-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, Ashland experienced a falling trend in crash data year-over-year, with total crashes decreasing by 8% from 25 in December 2022 to 23 in December 2023. Concurrently, total injuries saw a more significant decline of 36.4%, dropping from 11 to 7 during the same period.

1

Hit-and-Run Crashes — December 2023

4.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

7

Motorists Injured

Prior: 11-36.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · 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 Friday in December 2022 (4 crashes) to Sunday in December 2023 (7 crashes). While the peak hour remained 6 p.m. in both periods, the number of crashes at this hour was 3 in December 2022 and also 3 in December 2023. Additionally, December 2023 saw 7 crashes on Sunday, compared to 4 on Sunday in December 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no traffic fatalities in either December 2023 or December 2022. Total injuries decreased from 11 in December 2022 to 7 in December 2023. In December 2023, 4 crashes resulted in injury (1 serious, 2 minor, 1 possible), representing 17.4% of total crashes, a decrease from December 2022 where 6 crashes resulted in possible injuries, accounting for 24% of total crashes.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4.3%
Minor Injury2minor injury crashes8.7%
Possible Injury1possible injury crashes4.3%
-83.3%prior 6
No Injury19no injury crashes82.6%
0.0%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The most significant change in contributing factors was the emergence of 'No improper driving,' which accounted for 11 crashes in December 2023, up from 0 in December 2022. Conversely, 'Inattention' crashes decreased by 5, from 7 in December 2022 to 2 in December 2023. 'Failed to yield right of way' crashes also saw a reduction of 2, falling from 5 to 3 year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving11 (47.8%)
Failed to yield right of way3 (13%)-40.0%prior 5
Followed too closely2 (8.7%)
Inattention2 (8.7%)-71.4%prior 7
Distracted1 (4.3%)
Physical impairment1 (4.3%)
Driving too fast for conditions1 (4.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (4.3%)
Over-correcting/over-steering1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather decreased from 18 in December 2022 to 13 in December 2023, while 'Rain' condition crashes increased from 1 to 9 during the same period. Correspondingly, crashes on 'Dry' road surfaces decreased from 18 to 13, and 'Wet' road surface crashes increased from 4 to 9. The distribution of crashes by lighting conditions remained relatively stable, with 'Dark - lighted roadway' remaining the most frequent condition at 11 crashes in both periods.

Weather

Clear13 (56.5%)
-27.8%prior 18
Rain9 (39.1%)
Other1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Dark - lighted roadway11 (47.8%)
0.0%prior 11
Daylight9 (39.1%)
-10.0%prior 10
Dark - roadway not lighted2 (8.7%)
Dusk1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry13 (56.5%)
-27.8%prior 18
Wet9 (39.1%)
Ice1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (35 vehicles)

1
TOYOTA8 (22.9%)
0.0%prior 8
2
KIA4 (11.4%)
3
HONDA4 (11.4%)
-50.0%prior 8
4
ACURA2 (5.7%)
5
CHEVROLET2 (5.7%)
6
FORD2 (5.7%)
-60.0%prior 5
7
MAZDA2 (5.7%)
8
NISSAN2 (5.7%)
9
FL1 (2.9%)
10
LEXUS1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (38 persons with recorded sex)

Male20 (52.6%)
-28.6%prior 28
Female18 (47.4%)
-37.9%prior 29

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 35 mph zones decreased from 12 in December 2022 to 8 in December 2023, and crashes in 25 mph zones decreased from 8 to 5. Conversely, crashes in 30 mph zones increased from 4 to 8 year-over-year. Additionally, December 2023 saw crashes reported in 20 mph (1 crash) and 65 mph (1 crash) zones, which were not present in December 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · 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: 2023-12-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-12-01 through 2023-12-31 (31 days)
  • Geographic scope: ASHLAND, MA
  • Total crash records analyzed: 23
  • Total persons involved: 43
  • Total vehicles involved: 35

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: December 2023." Published June 21, 2026. Reporting period: 2023-12-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/ashland/december-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 — December 2023 | ThatCarHitMe.com