Monthly Traffic Safety Analysis

46 CRASHES IN
CHELMSFORD, MA
APRIL 2024

All metrics benchmarked againstApril 2023

In April 2024, CHELMSFORD experienced 46 total crashes, a decrease from 51 crashes in April 2023, representing a 9.8% reduction. The most notable year-over-year shift was a 50% decrease in total injuries, falling from 16 to 8.

46

-9.8%was 51

Total Crash Events

0

Persons Killed

8

-50.0%was 16

Persons Injured

2

-60.0%was 5

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 · 2024-04-01 to 2024-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for CHELMSFORD indicates a downward trend year-over-year. Total crashes decreased by 9.8%, from 51 in April 2023 to 46 in April 2024. Similarly, total injuries saw a significant 50% reduction, dropping from 16 to 8.

2

Hit-and-Run Crashes — April 2024

-60.0% vs prior (5)

Hit-and-run crashes decreased by 60%, falling from 5 incidents in April 2023 to 2 in April 2024. Consequently, the hit-and-run crash rate also decreased from 9.8% to 4.3% year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

8

Motorists Injured

Prior: 15-46.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted year-over-year. The peak day for crashes moved from Sunday, with 11 crashes in April 2023, to Friday, with 10 crashes in April 2024. The peak hour also shifted from 4 PM in April 2023 to 5 PM in April 2024, both periods recording 5 crashes during their respective peak hours.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at 0 in both periods. The total number of injuries decreased by 50%, from 16 in April 2023 to 8 in April 2024. Specifically, minor injury crashes decreased substantially from 10 to 1, while possible injury crashes increased from 1 to 5.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.2%
0.0%prior 1
Minor Injury1minor injury crashes2.2%
-90.0%prior 10
Possible Injury5possible injury crashes10.9%
400.0%prior 1
No Injury39no injury crashes84.8%
2.6%prior 38

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'Followed too closely,' saw a slight increase in count from 9 crashes in April 2023 to 10 crashes in April 2024. 'No improper driving' increased from 6 crashes to 8 crashes, while 'Failed to yield right of way' decreased from 7 crashes to 6 crashes. 'Failure to keep in proper lane or running off road' experienced a notable decrease from 6 crashes to 2 crashes.

Officer-Reported Primary Contributing Cause

Followed too closely10 (21.7%)11.1%prior 9
No improper driving8 (17.4%)33.3%prior 6
Failed to yield right of way6 (13%)-14.3%prior 7
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (6.5%)
Driving too fast for conditions3 (6.5%)
Inattention2 (4.3%)
Failure to keep in proper lane or running off road2 (4.3%)-66.7%prior 6
Over-correcting/over-steering2 (4.3%)
Disregarded traffic signs, signals, road markings1 (2.2%)
Illness1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes on dry road surfaces decreased from 41 in April 2023 to 31 in April 2024, while crashes on wet road surfaces increased from 9 to 14. Crashes occurring during daylight hours decreased from 41 to 34, whereas those in 'Dark - lighted roadway' conditions increased from 4 to 6.

Weather

Clear/Clear22 (47.8%)
46.7%prior 15
Clear6 (13.0%)
-62.5%prior 16
Rain4 (8.7%)
-33.3%prior 6
Cloudy/Cloudy4 (8.7%)
Rain/Cloudy3 (6.5%)
Snow2 (4.3%)
Cloudy2 (4.3%)
Cloudy/Snow1 (2.2%)
Sleet, hail (freezing rain or drizzle)/Sleet, hail (freezing rain or drizzle)1 (2.2%)
Cloudy/Rain1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Weather condition at time of crash

Lighting

Daylight34 (73.9%)
-17.1%prior 41
Dark - lighted roadway6 (13.0%)
Dark - roadway not lighted2 (4.3%)
Dark - unknown roadway lighting2 (4.3%)
Dawn2 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Lighting condition field

Road Surface

Dry31 (67.4%)
-24.4%prior 41
Wet14 (30.4%)
55.6%prior 9
Ice1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Road surface condition field

Vehicles & Demographics

Toyota remained the most frequently involved vehicle make, with its crash count increasing from 18 to 20. Honda's involvement significantly decreased from 17 to 7, while Ford's increased from 6 to 10. In terms of persons involved, the 16-20 age group saw a decrease from 18 to 13, and the 26-34 age group decreased from 21 to 15, while the 21-25 age group increased from 13 to 18.

Top Vehicle Makes (86 vehicles)

1
TOYOTA20 (23.3%)
11.1%prior 18
2
FORD10 (11.6%)
66.7%prior 6
3
HONDA7 (8.1%)
-58.8%prior 17
4
NISSAN5 (5.8%)
0.0%prior 5
5
JEEP4 (4.7%)
6
BMW4 (4.7%)
7
VOLVO3 (3.5%)
8
CHEVROLET3 (3.5%)
9
HYUNDAI3 (3.5%)
-40.0%prior 5
10
SUBARU3 (3.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Vehicle unit records

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

Sex Distribution (86 persons with recorded sex)

Male46 (53.5%)
-22.0%prior 59
Female40 (46.5%)
-11.1%prior 45

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 65 mph speed zone decreased from 16 in April 2023 to 10 in April 2024. Conversely, crashes in the 35 mph speed zone increased from 5 to 11. Crashes in the 55 mph zone also decreased from 8 to 3, and the 25 mph zone saw a reduction from 8 crashes to 6 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · 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: 2024-04-01 through 2024-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-04-01 through 2024-04-30 (30 days)
  • Geographic scope: CHELMSFORD, MA
  • Total crash records analyzed: 46
  • Total persons involved: 96
  • Total vehicles involved: 86

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: April 2024." Published June 21, 2026. Reporting period: 2024-04-01 to 2024-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chelmsford/april-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 — April 2024 | ThatCarHitMe.com