Monthly Traffic Safety Analysis

23 CRASHES IN
NORTH ADAMS, MA
JANUARY 2023

All metrics benchmarked againstJanuary 2022

In January 2023, North Adams experienced a notable decrease in total crashes compared to January 2022. Total crashes fell by 36.1%, from 36 crashes in January 2022 to 23 crashes in January 2023. Despite this reduction, total injuries remained stable at 5 in both periods.

23

▼ -36.1%was 36

Total Crash Events

0

Persons Killed

5

Persons Injured

0

▼ -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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend shows a significant decline in crash incidents year-over-year in North Adams. Total crashes decreased from 36 in January 2022 to 23 in January 2023, representing a 36.1% reduction.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 0→0.0%

1

Cyclists Injured

Prior: 0→%

4

Motorists Injured

Prior: 5↓-20.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes shifted between the two periods. In January 2022, the peak day for crashes was Monday with 9 incidents, while in January 2023, it shifted to Tuesday with 5 incidents. Similarly, the peak hour for crashes moved from 8p with 4 incidents in January 2022 to 6p with 3 incidents in January 2023.

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

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

Crash Severity Breakdown

Total fatalities remained at 0 in both January 2022 and January 2023, indicating no change in fatal crash outcomes. Total injuries also remained stable at 5 in both periods. The number of serious injury crashes (code 'A') stayed consistent at 1 in both years, while minor injury crashes (code 'B') decreased from 3 in January 2022 to 2 in January 2023.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4.3%
→0.0%prior 1
Minor Injury2minor injury crashes8.7%
↓-33.3%prior 3
No Injury20no injury crashes87%
↓-28.6%prior 28

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

The top contributing factor, "No improper driving," saw a decrease of 10 crashes, from 16 in January 2022 to 6 in January 2023. Crashes attributed to "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" decreased by 5, from 5 in January 2022 to 0 in January 2023. "Inattention" remained consistent with 4 crashes in both periods, while "Visibility obstructed" crashes increased from 1 in January 2022 to 2 in January 2023.

Officer-Reported Primary Contributing Cause

No improper driving6 (26.1%)↓-62.5%prior 16
Inattention4 (17.4%)
Other improper action2 (8.7%)
Failed to yield right of way2 (8.7%)
Visibility obstructed2 (8.7%)
Physical impairment1 (4.3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (4.3%)
Failure to keep in proper lane or running off road1 (4.3%)
Disregarded traffic signs, signals, road markings1 (4.3%)

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

Road & Environmental Conditions

Daylight crashes decreased from 23 in January 2022 to 14 in January 2023, while crashes occurring in 'Dark - lighted roadway' remained at 7 in both periods. Regarding road surface conditions, dry road crashes remained at 15 in both periods, and wet road crashes remained at 5. Snow-related crashes decreased from 10 in January 2022 to 3 in January 2023, and ice-related crashes decreased from 5 to 0.

Weather

Clear12 (52.2%)
↓-20.0%prior 15
Cloudy4 (17.4%)
Snow4 (17.4%)
Clear/Cloudy1 (4.3%)
↓-80.0%prior 5
Cloudy/Snow1 (4.3%)
Sleet, hail (freezing rain or drizzle)1 (4.3%)

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

Lighting

Daylight14 (60.9%)
↓-39.1%prior 23
Dark - lighted roadway7 (30.4%)
→0.0%prior 7
Dark - roadway not lighted1 (4.3%)
Dusk1 (4.3%)

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

Road Surface

Dry15 (65.2%)
→0.0%prior 15
Wet5 (21.7%)
→0.0%prior 5
Snow3 (13.0%)
↓-70.0%prior 10

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

Vehicles & Demographics

Top Vehicle Makes (38 vehicles)

1
BUIC6 (15.8%)
2
HONDA4 (10.5%)
↓-60.0%prior 10
3
TOYOTA4 (10.5%)
4
GMC3 (7.9%)
5
FORD3 (7.9%)
↓-62.5%prior 8
6
DODGE3 (7.9%)
7
JEEP2 (5.3%)
↓-60.0%prior 5
8
CHEVROLET2 (5.3%)
9
OTHR1 (2.6%)
10
VOLKSWAGEN1 (2.6%)

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

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

Sex Distribution (45 persons with recorded sex)

Female25 (55.6%)
↓-3.8%prior 26
Male20 (44.4%)
↓-48.7%prior 39

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

Speed Limit Zones

Crashes in 30 mph zones decreased from 14 in January 2022 to 8 in January 2023, representing a decrease of 6 crashes. There were 6 crashes in 50 mph zones in January 2022, but none in January 2023. Conversely, crashes in 20 mph zones appeared with 2 incidents in January 2023, while there were none in January 2022. No fatal crashes were recorded in any speed zone in either period.

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

Data Coverage

  • Reporting period: 2023-01-01 through 2023-01-31 (31 days)
  • Geographic scope: NORTH ADAMS, MA
  • Total crash records analyzed: 23
  • Total persons involved: 49
  • Total vehicles involved: 38

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). "NORTH ADAMS, MA Crash Intelligence Report: January 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/north-adams/january-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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North Adams, MA Crash Report — January 2023 | ThatCarHitMe.com