Monthly Traffic Safety Analysis

14 CRASHES IN
WAYLAND, MA
FEBRUARY 2024

All metrics benchmarked againstFebruary 2023

In February 2024, Wayland experienced 14 total crashes, a decrease of 6.7% compared to the 15 crashes recorded in February 2023. The most significant year-over-year change was an 80% reduction in total injuries, falling from 5 in the prior period to 1 in the current period. Fatalities remained at zero for both periods.

14

-6.7%was 15

Total Crash Events

0

Persons Killed

1

-80.0%was 5

Persons Injured

0

Fatal Crash Events

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 · 2024-02-01 to 2024-02-29 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a slight decrease in total crashes, with 14 crashes in the current period compared to 15 in the prior period, representing a 6.7% reduction. More notably, total injuries saw a substantial decline, dropping from 5 to 1, indicating an 80% decrease year-over-year. Fatal crashes remained stable at zero for both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 3-66.7%

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 hour for crashes shifted from 9 PM with 2 crashes in the prior period to 3 PM with 4 crashes in the current period. While Thursday remained the peak day for crashes, the count decreased from 4 crashes in the prior period to 3 crashes in the current period. Crashes on Sunday and Saturday each increased from 0 to 1, while Monday, Thursday, and Friday each saw a decrease of one crash.

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

Both periods reported zero fatal crashes. Total injuries decreased significantly from 5 in the prior period to 1 in the current period, an 80% reduction. Specifically, serious injuries (code A) and minor injuries (code B) each decreased from 1 and 4 respectively to 0, while possible injuries (code C) increased from 0 to 1.

Outcome by Severity (Crash Events)

Possible Injury1possible injury crashes7.1%
No Injury13no injury crashes92.9%
44.4%prior 9

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 contributing factor 'Inattention' increased significantly, rising from 2 crashes in the prior period to 5 crashes in the current period, a 150% increase in count, and its share of crashes rose from 13.3% to 35.7%. Conversely, 'No improper driving' decreased from 6 crashes to 2 crashes, a 66.7% reduction in count, with its share dropping from 40% to 14.3%. Factors like 'Driving too fast for conditions' and 'Failed to yield right of way', each accounting for 2 crashes in the prior period, were not reported in the current period.

Officer-Reported Primary Contributing Cause

Inattention5 (35.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (14.3%)
No improper driving2 (14.3%)-66.7%prior 6
Over-correcting/over-steering1 (7.1%)
Failure to keep in proper lane or running off road1 (7.1%)
Fatigued/asleep1 (7.1%)
Followed too closely1 (7.1%)

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

Daylight crashes increased from 6 in the prior period to 12 in the current period, while crashes occurring in 'Dark - roadway not lighted' remained stable at 2 for both periods. The prior period recorded a wider variety of adverse weather conditions, including rain, sleet, and snow in 6 crashes, whereas the current period only reported 'Clear' or 'Clear/Cloudy' conditions. Road surface data was not available for comparison in the current period.

Weather

Clear8 (57.1%)
60.0%prior 5
Clear/Cloudy6 (42.9%)

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

Lighting

Daylight12 (85.7%)
100.0%prior 6
Dark - roadway not lighted2 (14.3%)

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

Vehicles & Demographics

Top Vehicle Makes (26 vehicles)

1
TOYOTA6 (23.1%)
0.0%prior 6
2
FORD4 (15.4%)
3
NISSAN3 (11.5%)
4
HONDA2 (7.7%)
5
KIA1 (3.8%)
6
AUDI1 (3.8%)
7
LNDR1 (3.8%)
8
MAZDA1 (3.8%)
9
MERCEDES-BENZ1 (3.8%)
10
RAM1 (3.8%)

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

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

Sex Distribution (26 persons with recorded sex)

Male14 (53.8%)
-22.2%prior 18
Female12 (46.2%)
20.0%prior 10

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 30 mph speed zones saw a notable increase, rising from 1 crash in the prior period to 5 crashes in the current period. Conversely, crashes in 35 mph zones decreased from 4 to 2 year-over-year. The number of crashes in 25 mph and 40 mph zones remained stable, with 5 crashes and 1 crash respectively in both periods.

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: WAYLAND, MA
  • Total crash records analyzed: 14
  • Total persons involved: 28
  • Total vehicles involved: 26

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). "WAYLAND, 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/wayland/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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Wayland, MA Crash Report — February 2024 | ThatCarHitMe.com