Monthly Traffic Safety Analysis

26 CRASHES IN
SUDBURY, MA
JANUARY 2024

All metrics benchmarked againstJanuary 2023

In January 2024, SUDBURY, MA experienced 26 total crashes, an increase of 23.8% compared to the 21 crashes recorded in January 2023. The most notable year-over-year shift was the 133.3% increase in total injuries, rising from 3 to 7.

26

23.8%was 21

Total Crash Events

0

Persons Killed

7

133.3%was 3

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 · 2024-01-01 to 2024-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for January 2024 in SUDBURY, MA indicates an upward trend compared to January 2023. Total crashes increased by 23.8%, from 21 to 26, while total injuries saw a substantial rise of 133.3%, increasing from 3 to 7.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

7

Motorists Injured

Prior: 3133.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal patterns show shifts in peak crash times year-over-year. The peak day for crashes moved from Monday in January 2023, with 6 crashes, to Thursday in January 2024, with 5 crashes. Similarly, the peak crash hour shifted from 5 PM in January 2023 to 8 PM in January 2024, both periods recording 3 crashes during their respective peak hours.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both January 2023 and January 2024. However, the proportion of crashes resulting in injuries increased substantially, from 9.5% (2 crashes) in January 2023 to 26.9% (7 crashes) in January 2024. Specifically, serious injury crashes, which were absent in the prior period, accounted for 1 crash (3.8%) in January 2024.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes3.8%
Minor Injury3minor injury crashes11.5%
200.0%prior 1
Possible Injury3possible injury crashes11.5%
200.0%prior 1
No Injury18no injury crashes69.2%
-5.3%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'No improper driving,' increased by 3 crashes, rising from 10 in January 2023 to 13 in January 2024. Conversely, 'Failed to yield right of way' decreased from 2 crashes to 1 crash year-over-year. New factors observed in January 2024 include 'Made an improper turn' with 2 crashes and 'Swerving or avoiding' with 2 crashes, which were not reported in January 2023.

Officer-Reported Primary Contributing Cause

No improper driving13 (50%)30.0%prior 10
Made an improper turn2 (7.7%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (7.7%)
Failed to yield right of way1 (3.8%)
Distracted1 (3.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under adverse conditions significantly increased in January 2024 compared to January 2023. Crashes during non-clear weather rose from 7 to 16, representing 33.3% and 61.5% of total crashes respectively. Similarly, crashes on non-dry road surfaces increased from 9 to 17, accounting for 42.9% to 65.4% of crashes, while crashes in dark conditions saw a slight increase from 9 to 12.

Weather

Clear9 (34.6%)
-25.0%prior 12
Snow6 (23.1%)
Cloudy3 (11.5%)
Sleet, hail (freezing rain or drizzle)2 (7.7%)
Rain/Sleet, hail (freezing rain or drizzle)1 (3.8%)
Rain1 (3.8%)
Sleet, hail (freezing rain or drizzle)/Snow1 (3.8%)
Clear/Cloudy1 (3.8%)
Snow/Cloudy1 (3.8%)
Snow/Sleet, hail (freezing rain or drizzle)1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Weather condition at time of crash

Lighting

Daylight14 (53.8%)
40.0%prior 10
Dark - lighted roadway7 (26.9%)
-12.5%prior 8
Dark - roadway not lighted3 (11.5%)
Dark - unknown roadway lighting2 (7.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Lighting condition field

Road Surface

Dry9 (34.6%)
-25.0%prior 12
Snow9 (34.6%)
80.0%prior 5
Wet5 (19.2%)
Ice3 (11.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (44 vehicles)

1
TOYOTA8 (18.2%)
-27.3%prior 11
2
HONDA5 (11.4%)
3
FORD4 (9.1%)
4
CHEVROLET3 (6.8%)
5
NISSAN3 (6.8%)
6
ACURA2 (4.5%)
7
MERCEDES-BENZ2 (4.5%)
8
HYUNDAI2 (4.5%)
9
KIA1 (2.3%)
10
KVCH1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Vehicle unit records

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

Sex Distribution (47 persons with recorded sex)

Male27 (57.4%)
50.0%prior 18
Female20 (42.6%)
25.0%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones shifted year-over-year, with no fatal crashes reported in any speed zone during either period. Crashes in 35 MPH zones decreased from 12 in January 2023 to 6 in January 2024, while crashes in 25 MPH zones increased from 2 to 6, and 30 MPH zones increased from 5 to 8. Additionally, 5 MPH and 15 MPH zones, each with 1 crash, appeared in January 2024 but were not present in the prior period's data.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · 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: 2024-01-01 through 2024-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-01-31 (31 days)
  • Geographic scope: SUDBURY, MA
  • Total crash records analyzed: 26
  • Total persons involved: 53
  • Total vehicles involved: 44

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). "SUDBURY, MA Crash Intelligence Report: January 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/sudbury/january-2024-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

ThatCarHitMe.com · An Injuria.ai Company

Sudbury, MA Crash Report — January 2024 | ThatCarHitMe.com