Monthly Traffic Safety Analysis

41 CRASHES IN
CHELMSFORD, MA
NOVEMBER 2024

All metrics benchmarked againstNovember 2023

In Chelmsford, MA, total crashes decreased significantly from 72 in November 2023 to 41 in November 2024, representing a 43.1% reduction year-over-year. This substantial decrease in overall crash incidents is the most notable shift observed between the two periods. There were no fatal crashes reported in either period.

41

▼ -43.1%was 72

Total Crash Events

0

Persons Killed

16

▼ -46.7%was 30

Persons Injured

2

▼ -50.0%was 4

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 · 2024-11-01 to 2024-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash incidents in Chelmsford show a declining trend, with a decrease from 72 crashes in November 2023 to 41 crashes in November 2024. This constitutes a reduction of 31 crashes, or 43.1%, year-over-year.

2

Hit-and-Run Crashes — November 2024

▼ -50.0% vs prior (4)

The number of hit-and-run crashes decreased from 4 in November 2023 to 2 in November 2024. The hit-and-run crash rate also decreased from 5.6% in November 2023 to 4.9% in November 2024, indicating a downward trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

16

Motorists Injured

Prior: 30↓-46.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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 Thursday, with 17 incidents in November 2023, to Friday, with 8 incidents in November 2024. Similarly, the peak hour for crashes moved from 2 PM (8 crashes) in the prior period to 5 PM (6 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either November 2023 or November 2024. Total injuries decreased from 30 in November 2023 to 16 in November 2024. Serious injury crashes, categorized as 'A', increased from 1 (1.4% of total crashes) in November 2023 to 2 (4.9% of total crashes) in November 2024, while minor injury crashes decreased from 11 (15.3%) to 4 (9.8%).

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes4.9%
↑100.0%prior 1
Minor Injury4minor injury crashes9.8%
↓-63.6%prior 11
Possible Injury8possible injury crashes19.5%
↑33.3%prior 6
No Injury27no injury crashes65.9%
↓-50.0%prior 54

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'Followed too closely,' decreased from 15 crashes in November 2023 to 11 crashes in November 2024. Crashes attributed to 'No improper driving' also saw a slight reduction from 11 to 10 incidents. Notably, 'Exceeded authorized speed limit' increased from 0 crashes in November 2023 to 3 crashes in November 2024.

Officer-Reported Primary Contributing Cause

Followed too closely11 (26.8%)↓-26.7%prior 15
No improper driving10 (24.4%)↓-9.1%prior 11
Failed to yield right of way4 (9.8%)↓-42.9%prior 7
Driving too fast for conditions3 (7.3%)
Exceeded authorized speed limit3 (7.3%)
Disregarded traffic signs, signals, road markings2 (4.9%)↓-60.0%prior 5
Distracted1 (2.4%)
Over-correcting/over-steering1 (2.4%)
Physical impairment1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 47 in November 2023 to 35 in November 2024. Incidents on dry road surfaces also saw a reduction from 55 to 36 year-over-year. While crashes during daylight hours decreased from 47 to 17, those occurring in 'Dark - lighted roadway' conditions slightly increased from 11 to 14.

Weather

Clear/Clear30 (73.2%)
↓-3.2%prior 31
Clear5 (12.2%)
↓-68.8%prior 16
Clear/Cloudy2 (4.9%)
Rain/Cloudy2 (4.9%)
Cloudy1 (2.4%)
↓-80.0%prior 5
Fog, smog, smoke/Rain1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Weather condition at time of crash

Lighting

Daylight17 (41.5%)
↓-63.8%prior 47
Dark - lighted roadway14 (34.1%)
↑27.3%prior 11
Dark - roadway not lighted8 (19.5%)
→0.0%prior 8
Dusk2 (4.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Lighting condition field

Road Surface

Dry36 (87.8%)
↓-34.5%prior 55
Wet4 (9.8%)
↓-73.3%prior 15
Ice1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Road surface condition field

Vehicles & Demographics

The number of Toyota vehicles involved in crashes decreased from 29 in November 2023 to 10 in November 2024, and Honda vehicles decreased from 18 to 9. In terms of persons involved, the '65+' age group saw a slight increase from 21 persons in November 2023 to 22 persons in November 2024, while the '26-34' age group experienced a substantial decrease from 36 to 9 persons.

Top Vehicle Makes (71 vehicles)

1
TOYOTA10 (14.1%)
↓-65.5%prior 29
2
HONDA9 (12.7%)
↓-50.0%prior 18
3
CHEVROLET9 (12.7%)
↓-10.0%prior 10
4
FORD6 (8.5%)
↓-45.5%prior 11
5
NISSAN6 (8.5%)
↓-40.0%prior 10
6
SUBARU6 (8.5%)
7
HYUNDAI4 (5.6%)
8
CADI3 (4.2%)
9
KIA2 (2.8%)
↓-75.0%prior 8
10
VOLKSWAGEN2 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Vehicle unit records

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

Sex Distribution (114 persons with recorded sex)

Male65 (57.0%)
↓-22.6%prior 84
Female49 (43.0%)
↓-38.8%prior 80

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in the 30 mph speed zone decreased from 24 in November 2023 to 8 in November 2024. Crashes in the 65 mph speed zone also saw a decrease from 14 to 11. Conversely, crashes in the 25 mph speed zone increased from 7 to 8, and the 40 mph speed zone increased from 1 to 2.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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: 2024-11-01 through 2024-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-11-01 through 2024-11-30 (30 days)
  • Geographic scope: CHELMSFORD, MA
  • Total crash records analyzed: 41
  • Total persons involved: 124
  • Total vehicles involved: 71

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). "CHELMSFORD, MA Crash Intelligence Report: November 2024." Published June 21, 2026. Reporting period: 2024-11-01 to 2024-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chelmsford/november-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

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Chelmsford, MA Crash Report — November 2024 | ThatCarHitMe.com