Monthly Traffic Safety Analysis

14 CRASHES IN
WAYLAND, MA
SEPTEMBER 2024

All metrics benchmarked againstSeptember 2023

In September 2024, Wayland experienced 14 crashes, a significant decrease from the 29 crashes reported in September 2023. This represents a 51.7% reduction in total crashes year-over-year. The most notable shift was the 70.6% decrease in total injuries, falling from 17 to 5.

14

▼ -51.7%was 29

Total Crash Events

0

Persons Killed

5

▼ -70.6%was 17

Persons Injured

1

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

Trend Summary

Overall, crash data for Wayland shows a clear downward trend year-over-year. Total crashes decreased by 51.7%, from 29 in September 2023 to 14 in September 2024. Similarly, total injuries fell by 70.6%, from 17 to 5 over the same period.

1

Hit-and-Run Crashes — September 2024

7.1% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 0→%

4

Motorists Injured

Prior: 17↓-76.5%

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 peak day for crashes remained Tuesday in both periods, though the number of crashes on Tuesdays decreased from 8 in September 2023 to 3 in September 2024. The peak crash hour shifted from 4 PM with 4 crashes in the prior year to 6 PM with 2 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

Fatal crashes remained at zero in both September 2023 and September 2024. Crashes resulting in any injury (serious, minor, or possible) decreased from 8 in the prior period to 3 in the current period, representing a reduction in the proportion of injury-involved crashes from 27.6% to 21.4%. A serious injury crash was reported in the current period, which was not present in the prior period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes7.1%
Minor Injury1minor injury crashes7.1%
↓-83.3%prior 6
Possible Injury1possible injury crashes7.1%
↓-50.0%prior 2
No Injury11no injury crashes78.6%
↓-42.1%prior 19

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

Among contributing factors, 'Inattention' decreased by 4 crashes, from 7 in September 2023 to 3 in September 2024. 'No improper driving' also saw a reduction of 2 crashes, from 5 to 3. 'Followed too closely' decreased from 3 crashes to 2 crashes year-over-year.

Officer-Reported Primary Contributing Cause

Inattention3 (21.4%)↓-57.1%prior 7
No improper driving3 (21.4%)↓-40.0%prior 5
Followed too closely2 (14.3%)
Glare1 (7.1%)
Failure to keep in proper lane or running off road1 (7.1%)
Fatigued/asleep1 (7.1%)
Failed to yield right of way1 (7.1%)

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 on wet road surfaces saw a substantial decrease, falling from 11 in September 2023 to just 1 in September 2024. Crashes in clear weather also decreased from 13 to 10. The number of crashes during daylight hours decreased from 23 to 11.

Weather

Clear10 (71.4%)
↓-23.1%prior 13
Cloudy2 (14.3%)
Clear/Cloudy1 (7.1%)
↓-88.9%prior 9
Rain1 (7.1%)

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

Lighting

Daylight11 (78.6%)
↓-52.2%prior 23
Dark - lighted roadway2 (14.3%)
Dusk1 (7.1%)

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

Road Surface

Dry13 (92.9%)
↓-23.5%prior 17
Wet1 (7.1%)
↓-90.9%prior 11

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

Vehicles & Demographics

Top Vehicle Makes (28 vehicles)

1
HONDA5 (17.9%)
→0.0%prior 5
2
TOYOTA4 (14.3%)
↓-66.7%prior 12
3
HYUNDAI2 (7.1%)
4
RAM2 (7.1%)
5
FORD2 (7.1%)
6
VOLKSWAGEN2 (7.1%)
7
SUBARU2 (7.1%)
8
AUDI1 (3.6%)
9
VOLVO1 (3.6%)
10
BMW1 (3.6%)

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

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

Sex Distribution (32 persons with recorded sex)

Male18 (56.3%)
↓-43.8%prior 32
Female14 (43.8%)
↓-41.7%prior 24

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 the 25 mph speed zone decreased from 12 in September 2023 to 7 in September 2024. Similarly, crashes in the 35 mph zone decreased from 9 to 5. Notably, crashes in 40 mph and 65 mph zones, which accounted for 3 and 2 crashes respectively in the prior period, were not reported in the current period, and no fatal crashes occurred in any speed zone during either period.

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: WAYLAND, MA
  • Total crash records analyzed: 14
  • Total persons involved: 34
  • Total vehicles involved: 28

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: 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/wayland/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

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