Yearly Traffic Safety Analysis

12 CRASHES IN
CONWAY, MA
2025

All metrics benchmarked against2024

In 2025, Conway recorded 12 total traffic crashes, a 14.3% decrease from the 14 crashes documented in 2024. While overall crashes declined, the number of individuals injured increased from 3 to 4. The most significant year-over-year change was the appearance of serious injury crashes; two such incidents were reported in 2025, whereas none were recorded in the prior year.

12

-14.3%was 14

Total Crash Events

0

Persons Killed

4

33.3%was 3

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 · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in traffic crashes in Conway shows a modest decline year-over-year, with total incidents falling by 14.3% from 14 in 2024 to 12 in 2025. Despite the drop in total crashes, the number of people injured increased from 3 to 4. Fatalities remained at zero for both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

4

Motorists Injured

Prior: 333.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted significantly between the two periods. In 2025, collisions were most frequent on weekends, with Saturday and Sunday each recording 3 crashes, compared to 2024 when the peak days were Monday and Thursday with 4 crashes each. The peak hour for crashes also moved earlier, from 10 p.m. in 2024 (2 crashes) to 7 p.m. in 2025 (3 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened in 2025 despite a lower total number of incidents. While no fatal crashes occurred in either year, two crashes (16.7% of the total) resulted in serious injuries in 2025, a category not present in 2024's data. Consequently, the proportion of crashes involving any injury increased from 21.4% in 2024 (3 crashes) to 33.3% in 2025 (4 crashes).

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes16.7%
Minor Injury2minor injury crashes16.7%
-33.3%prior 3
No Injury8no injury crashes66.7%
-27.3%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes shifted notably year-over-year. In 2025, 'Failure to keep in proper lane or running off road' became a top factor, accounting for 4 incidents, a 300% increase in count from the single crash attributed to this factor in 2024. Conversely, crashes with 'No improper driving' listed as a factor decreased by 50%, from 8 incidents in 2024 to 4 in 2025, dropping its share of total crashes from 57.1% to 33.3%.

Officer-Reported Primary Contributing Cause

Failure to keep in proper lane or running off road4 (33.3%)
No improper driving4 (33.3%)-50.0%prior 8
Driving too fast for conditions1 (8.3%)
Exceeded authorized speed limit1 (8.3%)
Followed too closely1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in 2025 occurred under generally better conditions compared to 2024. The proportion of collisions happening in darkness on unlighted roadways decreased from 71.4% (10 crashes) in 2024 to 41.7% (5 crashes) in 2025. Similarly, incidents during adverse weather like snow or sleet dropped from 9 crashes in 2024 to 5 in 2025. The share of crashes on non-dry road surfaces also saw a slight decrease, from 57.1% in the prior year to 50% in the current year.

Weather

Clear/Clear4 (33.3%)
Clear2 (16.7%)
-60.0%prior 5
Cloudy/Cloudy1 (8.3%)
Rain/Rain1 (8.3%)
Snow/Sleet, hail (freezing rain or drizzle)1 (8.3%)
Blowing sand, snow/Snow1 (8.3%)
Snow/Snow1 (8.3%)
Clear/Severe crosswinds1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Dark - roadway not lighted5 (41.7%)
-50.0%prior 10
Daylight5 (41.7%)
Dusk2 (16.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry6 (50.0%)
0.0%prior 6
Ice2 (16.7%)
Snow2 (16.7%)
-60.0%prior 5
Wet2 (16.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (13 vehicles)

1
TOYOTA4 (30.8%)
2
HONDA2 (15.4%)
3
VOLKSWAGEN2 (15.4%)
4
ACURA1 (7.7%)
5
KIA1 (7.7%)
6
HYUNDAI1 (7.7%)
7
BMW1 (7.7%)
8
DODGE1 (7.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

Sex Distribution (13 persons with recorded sex)

Male8 (61.5%)
-50.0%prior 16
Female5 (38.5%)
-16.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

There was a noticeable shift in crashes toward lower speed zones in 2025 compared to the previous year. Crashes in 25 mph and 30 mph zones increased from a combined 3 incidents in 2024 to 9 incidents in 2025. Conversely, the 4 crashes that occurred in 40 mph or 45 mph zones in 2024 had no equivalent in 2025. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: CONWAY, MA
  • Total crash records analyzed: 12
  • Total persons involved: 14
  • Total vehicles involved: 13

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). "CONWAY, MA Crash Intelligence Report: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/conway/2025-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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Conway, MA Crash Report — 2025 | ThatCarHitMe.com