Yearly Traffic Safety Analysis

264 CRASHES IN
WAYLAND, MA
2024

All metrics benchmarked against2023

In Wayland, total traffic crashes increased slightly from 258 in 2023 to 264 in 2024, a change of approximately 2.3%. While the overall crash count remained relatively stable, the most significant year-over-year change was the registration of one fatality in 2024, whereas there were no fatalities in the prior year. Despite this, the total number of injuries recorded decreased from 88 to 75.

264

2.3%was 258

Total Crash Events

1

Persons Killed

75

-14.8%was 88

Persons Injured

10

11.1%was 9

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends show a slight increase in the total number of incidents, rising from 258 in 2023 to 264 in 2024. In contrast, the number of people injured in these crashes decreased by 14.8%, from 88 individuals in 2023 to 75 in 2024. The data indicates a minor rise in crash frequency accompanied by a larger drop in resulting injuries.

10

Hit-and-Run Crashes — 2024

11.1% vs prior (9)

The number of hit-and-run crashes increased from 9 in 2023 to 10 in 2024. As a percentage of total crashes, the hit-and-run rate also trended slightly upward, rising from 3.5% in the prior year to 3.8% in the current year. This reflects a small increase in both the absolute count and the proportional rate of hit-and-run incidents.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

0

Other Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 1100.0%

1

Cyclists Injured

Prior: 4-75.0%

71

Motorists Injured

Prior: 83-14.5%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed a shift between the two years. In 2023, the peak day for crashes was Tuesday with 52 incidents, which shifted to Friday in 2024, also with 52 incidents. The peak hour for crashes moved earlier in the day, from 4 p.m. in 2023 (28 crashes) to 3 p.m. in 2024 (40 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes shifted year-over-year, most notably with one fatal crash occurring in 2024 compared to zero in 2023. The proportion of crashes resulting in no injuries increased, accounting for 79.2% of incidents in 2024, up from 71.7% in 2023. Correspondingly, the share of crashes involving any injury (Serious, Minor, or Possible) decreased from 24.0% of all crashes in 2023 to 20.1% in 2024.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
Serious Injury6serious injury crashes2.3%
50.0%prior 4
Minor Injury35minor injury crashes13.3%
-20.5%prior 44
Possible Injury12possible injury crashes4.5%
-14.3%prior 14
No Injury209no injury crashes79.2%
13.0%prior 185

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Comparing contributing factors, "Inattention" saw a notable increase, cited in 57 crashes in 2024 compared to 43 in 2023, a 32.6% rise in count. Conversely, crashes involving "Failed to yield right of way" decreased by 35.3% in count, from 34 incidents in 2023 to 22 in 2024. The count of crashes where "Driving too fast for conditions" was a factor more than doubled, increasing from 4 to 11.

Officer-Reported Primary Contributing Cause

No improper driving67 (25.4%)19.6%prior 56
Inattention57 (21.6%)32.6%prior 43
Followed too closely24 (9.1%)4.3%prior 23
Failed to yield right of way22 (8.3%)-35.3%prior 34
Driving too fast for conditions11 (4.2%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner7 (2.7%)0.0%prior 7
Fatigued/asleep7 (2.7%)-30.0%prior 10
Disregarded traffic signs, signals, road markings6 (2.3%)20.0%prior 5
Failure to keep in proper lane or running off road6 (2.3%)0.0%prior 6
Other improper action6 (2.3%)-45.5%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather and on dry roads constituted a larger share of incidents in 2024 than in 2023. In 2024, 61.7% of crashes happened in clear weather, up from 55.0% the previous year. Similarly, incidents on dry road surfaces rose from 73.6% of the total in 2023 to 77.7% in 2024. Crashes during daylight hours remained proportionally stable, accounting for approximately 72% of all incidents in both years.

Weather

Clear163 (62.2%)
14.8%prior 142
Clear/Cloudy39 (14.9%)
8.3%prior 36
Cloudy14 (5.3%)
-6.7%prior 15
Cloudy/Rain10 (3.8%)
66.7%prior 6
Rain8 (3.1%)
-42.9%prior 14
Snow7 (2.7%)
Rain/Cloudy4 (1.5%)
-42.9%prior 7
Clear/Clear3 (1.1%)
-72.7%prior 11
Other2 (0.8%)
Cloudy/Snow2 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight191 (72.3%)
2.1%prior 187
Dark - lighted roadway38 (14.4%)
40.7%prior 27
Dark - roadway not lighted16 (6.1%)
-27.3%prior 22
Dusk15 (5.7%)
36.4%prior 11
Dawn3 (1.1%)
Dark - unknown roadway lighting1 (0.4%)
-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry205 (78.2%)
7.9%prior 190
Wet38 (14.5%)
-20.8%prior 48
Snow11 (4.2%)
-21.4%prior 14
Ice6 (2.3%)
Slush2 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The top two vehicle makes involved in crashes, Toyota and Honda, maintained their rankings in both 2024 and 2023. Regarding the age of persons involved, there was a significant decrease in the 16-20 age group, which fell from 75 individuals in 2023 to 50 in 2024. In contrast, the 21-25 age group saw its involvement increase from 39 persons in 2023 to 67 in 2024.

Top Vehicle Makes (482 vehicles)

1
TOYOTA85 (17.6%)
-4.5%prior 89
2
HONDA52 (10.8%)
0.0%prior 52
3
FORD43 (8.9%)
4.9%prior 41
4
CHEVROLET28 (5.8%)
21.7%prior 23
5
NISSAN28 (5.8%)
16.7%prior 24
6
JEEP25 (5.2%)
19.0%prior 21
7
SUBARU24 (5%)
0.0%prior 24
8
LEXUS19 (3.9%)
58.3%prior 12
9
HYUNDAI15 (3.1%)
-6.3%prior 16
10
BMW13 (2.7%)
-51.9%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (538 persons with recorded sex)

Male282 (52.4%)
5.2%prior 268
Female256 (47.6%)
9.4%prior 234

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones remained the most common in both periods, increasing slightly from 103 incidents in 2023 to 107 in 2024. The single fatal crash recorded in 2024 occurred within a 25 mph zone. The number of crashes in 35 mph zones saw a slight decrease from 68 in 2023 to 63 in 2024, while incidents in 65 mph zones were nearly unchanged, with 17 in 2023 and 16 in 2024.

Fatal crashes by zone: 25 mph: 1 of 107 (0.935%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: WAYLAND, MA
  • Total crash records analyzed: 264
  • Total persons involved: 571
  • Total vehicles involved: 482

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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wayland/2024-annual-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 — 2024 | ThatCarHitMe.com