Monthly Traffic Safety Analysis

52 CRASHES IN
CHELMSFORD, MA
SEPTEMBER 2024

All metrics benchmarked againstSeptember 2023

Total crashes in Chelmsford decreased from 75 in September 2023 to 52 in September 2024, representing a 30.7% reduction year-over-year. This period saw a notable decrease in crashes attributed to "Driving too fast for conditions," which dropped from 11 crashes to 2 crashes.

52

-30.7%was 75

Total Crash Events

0

Persons Killed

19

-32.1%was 28

Persons Injured

4

33.3%was 3

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 · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for Chelmsford shows a significant downward trend in September 2024 compared to September 2023. Total crashes decreased by 30.7%, from 75 to 52, while total injuries also saw a 32.1% reduction, falling from 28 to 19. Fatalities remained at zero for both periods.

4

Hit-and-Run Crashes — September 2024

33.3% vs prior (3)

Hit-and-run crashes increased from 3 in September 2023 to 4 in September 2024. This change resulted in the hit-and-run crash rate rising from 4% of total crashes in the prior period to 7.7% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

19

Motorists Injured

Prior: 27-29.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The distribution of crashes across the week shifted, with Wednesday becoming the peak day in September 2024 with 11 crashes, compared to Tuesday being the peak day in September 2023 with 19 crashes. The peak crash hour also changed from 8 p.m. (8 crashes) in the prior year to 5 p.m. (7 crashes) in the current year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total injuries decreased from 28 in September 2023 to 19 in September 2024, a 32.1% reduction. In the current period, there were 3 serious injuries, 7 minor injuries, and 9 possible injuries. In the prior period, there were 18 minor injuries and 9 possible injuries, with no serious injuries reported.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.9%
Minor Injury2minor injury crashes3.8%
-88.2%prior 17
Possible Injury6possible injury crashes11.5%
0.0%prior 6
No Injury42no injury crashes80.8%
-19.2%prior 52

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw significant year-over-year changes in crash counts. Crashes attributed to "Driving too fast for conditions" decreased by 9, from 11 to 2, and "Failure to keep in proper lane or running off road" also decreased by 9 crashes, from 11 to 2. Conversely, "Inattention" increased by 6 crashes, rising from 4 to 10, and "Failed to yield right of way" increased by 2 crashes, from 7 to 9.

Officer-Reported Primary Contributing Cause

Followed too closely12 (23.1%)0.0%prior 12
Inattention10 (19.2%)
Failed to yield right of way9 (17.3%)28.6%prior 7
No improper driving7 (13.5%)0.0%prior 7
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (3.8%)
Driving too fast for conditions2 (3.8%)-81.8%prior 11
Failure to keep in proper lane or running off road2 (3.8%)-81.8%prior 11
Physical impairment1 (1.9%)
Wrong side or wrong way1 (1.9%)
Disregarded traffic signs, signals, road markings1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in adverse weather conditions notably decreased, with crashes during "Rain" dropping from 12 in September 2023 to 0 in September 2024, and "Wet" road surface crashes decreasing from 26 to 5. Conversely, crashes on "Dry" road surfaces saw a slight increase from 46 to 47. There was also a significant reduction in crashes occurring in "Dark - roadway not lighted" conditions, dropping from 14 to 0.

Weather

Clear/Clear30 (57.7%)
20.0%prior 25
Clear12 (23.1%)
-29.4%prior 17
Cloudy/Rain3 (5.8%)
-50.0%prior 6
Rain/Cloudy2 (3.8%)
Clear/Cloudy2 (3.8%)
Cloudy/Cloudy2 (3.8%)
Cloudy1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash

Lighting

Daylight42 (80.8%)
-8.7%prior 46
Dark - lighted roadway6 (11.5%)
-25.0%prior 8
Dusk3 (5.8%)
Dawn1 (1.9%)
-83.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field

Road Surface

Dry47 (90.4%)
2.2%prior 46
Wet5 (9.6%)
-80.8%prior 26

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 139 to 114 year-over-year. While Toyota remained the top make, its involvement decreased from 27 vehicles to 17, and Honda's involvement decreased from 23 to 12. Notably, the 0-15 age group saw an increase in persons involved from 2 to 7, while the 26-34 age group saw a decrease from 43 to 32.

Top Vehicle Makes (114 vehicles)

1
TOYOTA17 (14.9%)
-37.0%prior 27
2
HONDA12 (10.5%)
-47.8%prior 23
3
FORD11 (9.6%)
-15.4%prior 13
4
NISSAN8 (7%)
5
SUBARU6 (5.3%)
6
CHEVROLET5 (4.4%)
-16.7%prior 6
7
KIA5 (4.4%)
8
HYUNDAI5 (4.4%)
-28.6%prior 7
9
JEEP4 (3.5%)
10
VOLKSWAGEN3 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records

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

Sex Distribution (132 persons with recorded sex)

Male73 (55.3%)
-11.0%prior 82
Female59 (44.7%)
-6.3%prior 63

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 65 mph speed zones decreased from 24 to 18 year-over-year, and crashes in 55 mph zones dropped from 11 to 0. Conversely, crashes in 25 mph zones increased from 4 to 5. All reported speed zones continued to have a 0% fatal crash rate in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-09-01 through 2024-09-30 (30 days)
  • Geographic scope: CHELMSFORD, MA
  • Total crash records analyzed: 52
  • Total persons involved: 149
  • Total vehicles involved: 114

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: September 2024." Published June 21, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chelmsford/september-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

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