Monthly Traffic Safety Analysis

42 CRASHES IN
CHELMSFORD, MA
FEBRUARY 2024

All metrics benchmarked againstFebruary 2023

CHELMSFORD experienced 42 crashes in February 2024, matching the 42 crashes recorded in February 2023. A notable shift includes a decrease from 1 fatality in the prior period to 0 fatalities in the current period, alongside an increase in hit-and-run crashes from 0 to 7.

42

Total Crash Events

0

-100.0%was 1

Persons Killed

15

7.1%was 14

Persons Injured

7

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes remained stable year-over-year at 42 incidents. However, fatalities decreased from 1 in February 2023 to 0 in February 2024, while total injuries saw a slight increase from 14 to 15.

7

Hit-and-Run Crashes — February 2024

16.7% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

15

Motorists Injured

Prior: 147.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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 12 incidents in February 2023 to Tuesday with 9 incidents in February 2024. The peak hour also changed, moving from 6 AM in the prior period to 3 PM in the current period, both recording 6 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 1 in February 2023 to 0 in February 2024, reducing the fatal crash rate from 2.38% to 0%. While minor injuries decreased from 8 to 5, possible injuries increased from 4 to 6, and crashes with no injuries rose from 29 to 30.

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes11.9%
-37.5%prior 8
Possible Injury6possible injury crashes14.3%
50.0%prior 4
No Injury30no injury crashes71.4%
3.4%prior 29

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Most severe injury per crash record

Top Contributing Factors

The factor 'Followed too closely' saw a substantial increase, rising from 4 crashes in February 2023 to 9 crashes in February 2024, a 125% increase in count. Conversely, 'Failure to keep in proper lane or running off road' decreased from 6 crashes to 4 crashes, a 33.3% reduction in count. 'Driving too fast for conditions' also decreased, from 3 crashes in the prior period to 0 in the current period.

Officer-Reported Primary Contributing Cause

Followed too closely9 (21.4%)
No improper driving9 (21.4%)12.5%prior 8
Failure to keep in proper lane or running off road4 (9.5%)-33.3%prior 6
Failed to yield right of way3 (7.1%)-40.0%prior 5
Inattention3 (7.1%)
Other improper action3 (7.1%)
Made an improper turn2 (4.8%)
Glare2 (4.8%)
Exceeded authorized speed limit1 (2.4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a significant shift in road surface conditions, with crashes on dry roads increasing from 25 in February 2023 to 39 in February 2024, while crashes on ice, snow, or slush decreased from 13 to 0. Daylight crashes also increased from 22 to 30, whereas crashes in dark-lighted conditions decreased from 11 to 4.

Weather

Clear18 (42.9%)
50.0%prior 12
Clear/Clear18 (42.9%)
50.0%prior 12
Cloudy3 (7.1%)
Clear/Rain1 (2.4%)
Rain1 (2.4%)
Snow/Snow1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Weather condition at time of crash

Lighting

Daylight30 (71.4%)
36.4%prior 22
Dark - lighted roadway4 (9.5%)
-63.6%prior 11
Dark - roadway not lighted4 (9.5%)
Dawn2 (4.8%)
-60.0%prior 5
Dusk2 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Lighting condition field

Road Surface

Dry39 (92.9%)
56.0%prior 25
Wet3 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 68 in February 2023 to 85 in February 2024. The age group 21-25 saw a notable increase in persons involved, rising from 7 to 18, while male involvement increased from 39 to 56 and female involvement decreased from 36 to 34.

Top Vehicle Makes (85 vehicles)

1
HONDA17 (20%)
30.8%prior 13
2
TOYOTA9 (10.6%)
28.6%prior 7
3
SUBARU5 (5.9%)
4
FORD5 (5.9%)
0.0%prior 5
5
CHEVROLET5 (5.9%)
6
JEEP4 (4.7%)
7
MERCEDES-BENZ4 (4.7%)
8
ACURA3 (3.5%)
9
DODGE3 (3.5%)
10
GMC3 (3.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Vehicle unit records

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

Sex Distribution (90 persons with recorded sex)

Male56 (62.2%)
43.6%prior 39
Female34 (37.8%)
-5.6%prior 36

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 65 mph speed zones increased from 4 in February 2023 to 8 in February 2024. Conversely, crashes in 30 mph zones decreased from 11 to 9, and crashes in 40 mph zones decreased from 4 to 1. The prior period recorded 1 fatal crash in a 30 mph zone, whereas no fatal crashes were reported in any speed zone in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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: 2024-02-01 through 2024-02-29
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-02-01 through 2024-02-29 (29 days)
  • Geographic scope: CHELMSFORD, MA
  • Total crash records analyzed: 42
  • Total persons involved: 102
  • Total vehicles involved: 85

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: February 2024." Published June 21, 2026. Reporting period: 2024-02-01 to 2024-02-29. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chelmsford/february-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 — February 2024 | ThatCarHitMe.com