Monthly Traffic Safety Analysis

41 CRASHES IN
WESTFORD, MA
MAY 2024

All metrics benchmarked againstMay 2023

In May 2024, WESTFORD, MA experienced 41 crashes, marking a 17.1% increase compared to the 35 crashes recorded in May 2023. Total injuries also saw a slight rise from 10 to 11, while fatal crashes remained at zero for both periods. A notable shift is the emergence of 2 hit-and-run crashes in May 2024, compared to zero in the prior year.

41

17.1%was 35

Total Crash Events

0

Persons Killed

11

10.0%was 10

Persons Injured

2

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 · 2024-05-01 to 2024-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in WESTFORD, MA showed an upward trend year-over-year, increasing by 17.1% from 35 crashes in May 2023 to 41 crashes in May 2024. Total injuries also increased by 10%, from 10 to 11, while the number of fatalities remained at zero in both periods.

2

Hit-and-Run Crashes — May 2024

4.9% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 10.0%

10

Motorists Injured

Prior: 911.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year, with the peak day moving from Monday in May 2023 (7 crashes) to Wednesday in May 2024 (9 crashes). The peak crash hour also changed from 11 AM (5 crashes) in May 2023 to 5 PM (6 crashes) in May 2024. Wednesday crashes increased from 4 to 9, while Monday crashes decreased from 7 to 4.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While both periods reported zero fatal crashes, the distribution of injury severities changed. Serious injury crashes increased from 1 in May 2023 to 2 in May 2024, representing a 100% rise, and their share of total crashes grew from 2.9% to 4.9%. Minor injury crashes also increased from 4 to 7, while possible injury crashes decreased from 3 to 1, with their share falling from 8.6% to 2.4%.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes4.9%
100.0%prior 1
Minor Injury7minor injury crashes17.1%
75.0%prior 4
Possible Injury1possible injury crashes2.4%
-66.7%prior 3
No Injury30no injury crashes73.2%
11.1%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Most severe injury per crash record

Top Contributing Factors

Several shifts were observed in contributing factors year-over-year. Crashes attributed to 'Inattention' decreased from 11 to 8, while 'Followed too closely' crashes increased from 5 to 8. 'No improper driving' incidents decreased from 8 to 4 crashes, and 'Failed to yield right of way' crashes, not prominent in May 2023, accounted for 6 crashes in May 2024.

Officer-Reported Primary Contributing Cause

Followed too closely8 (19.5%)60.0%prior 5
Inattention8 (19.5%)-27.3%prior 11
Failure to keep in proper lane or running off road7 (17.1%)
Failed to yield right of way6 (14.6%)
No improper driving4 (9.8%)-50.0%prior 8
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (4.9%)
Made an improper turn1 (2.4%)
Other improper action1 (2.4%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained predominantly clear and dry across both periods, with a slight increase in the proportion of crashes occurring in clear weather from 88.6% to 90.2%. Crashes on wet road surfaces decreased from 3 to 2, and the proportion of crashes occurring during daylight hours slightly decreased from 85.7% in May 2023 to 80.5% in May 2024. There were 2 crashes at dusk in May 2024, compared to none in May 2023.

Weather

Clear37 (90.2%)
19.4%prior 31
Cloudy2 (4.9%)
Rain/Cloudy2 (4.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Weather condition at time of crash

Lighting

Daylight33 (80.5%)
10.0%prior 30
Dark - lighted roadway4 (9.8%)
Dark - roadway not lighted2 (4.9%)
Dusk2 (4.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Lighting condition field

Road Surface

Dry39 (95.1%)
21.9%prior 32
Wet2 (4.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 24.6%, from 57 in May 2023 to 71 in May 2024. Toyota vehicles involved in crashes increased from 8 to 14, and Honda vehicles doubled from 4 to 8. Conversely, Subaru and Ford vehicles involved in crashes each decreased from 5 to 3.

Top Vehicle Makes (71 vehicles)

1
TOYOTA14 (19.7%)
75.0%prior 8
2
CHEVROLET8 (11.3%)
60.0%prior 5
3
HONDA8 (11.3%)
4
NISSAN5 (7%)
5
MAZDA4 (5.6%)
6
SUBARU3 (4.2%)
-40.0%prior 5
7
FORD3 (4.2%)
-40.0%prior 5
8
JEEP3 (4.2%)
9
MERCEDES-BENZ3 (4.2%)
10
KIA2 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Vehicle unit records

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

Sex Distribution (80 persons with recorded sex)

Male45 (56.3%)
21.6%prior 37
Female35 (43.8%)
25.0%prior 28

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph and 65 mph speed zones remained constant at 22 and 5 crashes, respectively, across both periods. Crashes in the 40 mph zone doubled from 4 to 8, and the 25 mph zone also saw a 100% increase from 1 to 2 crashes. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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: 2024-05-01 through 2024-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-05-01 through 2024-05-31 (31 days)
  • Geographic scope: WESTFORD, MA
  • Total crash records analyzed: 41
  • Total persons involved: 86
  • 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). "WESTFORD, MA Crash Intelligence Report: May 2024." Published June 21, 2026. Reporting period: 2024-05-01 to 2024-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/westford/may-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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Westford, MA Crash Report — May 2024 | ThatCarHitMe.com