Yearly Traffic Safety Analysis

14 CRASHES IN
CONWAY, MA
2024

All metrics benchmarked against2023

In 2024, Conway recorded 14 vehicle crashes, a 250% increase from the 4 crashes reported in 2023. While fatalities remained at zero in both years, the number of injuries rose from 2 to 3. The most significant year-over-year change was the sharp rise in total collisions, particularly single-vehicle incidents, which accounted for 11 of the 14 crashes in the current period.

14

250.0%was 4

Total Crash Events

0

Persons Killed

3

50.0%was 2

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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash trends in Conway show a significant upward trajectory year-over-year. Total crashes increased by 250%, rising from 4 in 2023 to 14 in 2024. This increase was accompanied by a slight rise in total injuries from 2 to 3, while fatalities remained at zero for both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

3

Motorists Injured

Prior: 250.0%

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 shifted significantly between the two periods. In 2023, crashes were most common on Sunday, which saw 3 of the 4 total incidents. In 2024, the peak days for collisions moved to Monday and Thursday, each recording 4 crashes. The single peak hour also shifted from 9 p.m. in the prior year to 10 p.m. in the current year, which saw 2 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

While the absolute number of injuries increased from 2 to 3, the overall severity of crashes decreased proportionally year-over-year. The rate of crashes involving minor injuries fell from 50% of all incidents in 2023 to 21.4% in 2024. Consequently, the share of crashes with no reported injuries increased from 50% to 78.6%. There were no fatal crashes recorded in either period.

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes21.4%
50.0%prior 2
No Injury11no injury crashes78.6%
450.0%prior 2

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

The leading contributing factors shifted between periods. In 2024, 'No improper driving' was the most cited factor, accounting for 8 of the 14 crashes, a significant increase from just 1 crash in 2023. Crashes attributed to 'Driving too fast for conditions' also increased in count from 1 to 2. Conversely, 'Exceeded authorized speed limit,' which was a factor in one crash in 2023, was not listed among the primary factors in 2024.

Officer-Reported Primary Contributing Cause

No improper driving8 (57.1%)
Driving too fast for conditions2 (14.3%)
Failure to keep in proper lane or running off road1 (7.1%)
Fatigued/asleep1 (7.1%)
Inattention1 (7.1%)

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

Adverse weather and road conditions played a much larger role in crashes during 2024 compared to the prior year. Crashes occurring in snow conditions rose from zero in 2023 to 6 in 2024, and incidents on snowy road surfaces increased from zero to 5. Similarly, the number of crashes in dark, unlit roadway conditions increased from 2 to 10. In contrast, crashes in clear weather only increased from 2 to 5.

Weather

Snow6 (42.9%)
Clear5 (35.7%)
Cloudy1 (7.1%)
Sleet, hail (freezing rain or drizzle)1 (7.1%)
Snow/Sleet, hail (freezing rain or drizzle)1 (7.1%)

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

Lighting

Dark - roadway not lighted10 (71.4%)
Daylight3 (21.4%)
Dawn1 (7.1%)

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

Road Surface

Dry6 (42.9%)
Snow5 (35.7%)
Ice2 (14.3%)
Wet1 (7.1%)

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

Vehicles & Demographics

Top Vehicle Makes (18 vehicles)

1
FORD3 (16.7%)
2
TOYOTA3 (16.7%)
3
GMC1 (5.6%)
4
HYUNDAI1 (5.6%)
5
MAZDA1 (5.6%)
6
RAM1 (5.6%)
7
SUBARU1 (5.6%)
8
VOLKSWAGEN1 (5.6%)
9
CHEVROLET1 (5.6%)
10
VOLVO1 (5.6%)

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

Sex Distribution (22 persons with recorded sex)

Male16 (72.7%)
700.0%prior 2
Female6 (27.3%)
200.0%prior 2

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

The distribution of crashes across different speed zones expanded in 2024. In 2023, all recorded crashes occurred in 30 mph (3 crashes) and 35 mph (1 crash) zones. In the current period, crashes were more dispersed, with incidents occurring in 25 mph (2 crashes), 40 mph (3 crashes), and 45 mph (1 crash) zones. Crashes in 30 mph zones decreased from 3 to 1, while those in 35 mph zones increased from 1 to 3. No fatal crashes were reported in any speed zone for either year.

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: CONWAY, MA
  • Total crash records analyzed: 14
  • Total persons involved: 24
  • Total vehicles involved: 18

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: 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/conway/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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Conway, MA Crash Report — 2024 | ThatCarHitMe.com