Monthly Traffic Safety Analysis

59 CRASHES IN
BOURNE, MA
MAY 2025

All metrics benchmarked againstMay 2024

Total crashes in Bourne for May 2025 were 59, a decrease of 19.2% from 73 crashes in May 2024. Total injuries also decreased by 21.7%, from 23 to 18. The most significant year-over-year shift was a 75% decrease in DUI-related crashes, falling from 4 in May 2024 to 1 in May 2025.

59

▼ -19.2%was 73

Total Crash Events

0

Persons Killed

18

▼ -21.7%was 23

Persons Injured

6

▼ -45.5%was 11

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. 2 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for Bourne shows a downward trend in May 2025 compared to May 2024. Total crashes decreased by 19.2%, from 73 to 59, and total injuries decreased by 21.7%, from 23 to 18. Fatalities remained stable at zero in both periods.

6

Hit-and-Run Crashes — May 2025

▼ -45.5% vs prior (11)

Hit-and-run crashes decreased by 45.5%, from 11 in May 2024 to 6 in May 2025. The hit-and-run rate also decreased from 15.1% of all crashes in May 2024 to 10.2% in May 2025. This indicates a positive trend in reducing hit-and-run incidents.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

18

Motorists Injured

Prior: 23↓-21.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Thursday with 16 crashes in May 2024 to Tuesday with 14 crashes in May 2025. The peak hour also shifted from 3 PM with 9 crashes in May 2024 to 2 PM with 11 crashes in May 2025. Notably, Saturday crashes saw a decrease from 10 in May 2024 to 3 in May 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While both periods reported zero fatalities, May 2025 saw 2 crashes resulting in serious injuries (3.4% of crashes), which were not present in May 2024 data. Minor injury crashes decreased from 12 (16.4%) in May 2024 to 9 (15.3%) in May 2025. Possible injury crashes also decreased from 6 (8.2%) to 4 (6.8%).

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes3.4%
Minor Injury9minor injury crashes15.3%
↓-25.0%prior 12
Possible Injury4possible injury crashes6.8%
↓-33.3%prior 6
No Injury42no injury crashes71.2%
↓-16.0%prior 50

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'Failed to yield right of way' decreased from 12 in May 2024 to 6 in May 2025. Similarly, 'Followed too closely' crashes decreased from 11 to 8, and 'Failure to keep in proper lane or running off road' decreased from 9 to 4. Conversely, crashes attributed to 'No improper driving' increased from 8 in May 2024 to 12 in May 2025.

Officer-Reported Primary Contributing Cause

No improper driving12 (20.3%)↑50.0%prior 8
Followed too closely8 (13.6%)↓-27.3%prior 11
Failed to yield right of way6 (10.2%)↓-50.0%prior 12
Inattention5 (8.5%)→0.0%prior 5
Disregarded traffic signs, signals, road markings4 (6.8%)↓-20.0%prior 5
Failure to keep in proper lane or running off road4 (6.8%)↓-55.6%prior 9
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (5.1%)
Exceeded authorized speed limit3 (5.1%)
Other improper action2 (3.4%)
Driving too fast for conditions1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather decreased from 46 in May 2024 to 37 in May 2025, and those in 'Rain' decreased from 10 to 2. Crashes on 'Wet' road surfaces also saw a substantial reduction from 16 to 6. 'Daylight' crashes decreased from 59 to 50 year-over-year.

Weather

Clear37 (63.8%)
↓-19.6%prior 46
Clear/Clear7 (12.1%)
Cloudy5 (8.6%)
↓-58.3%prior 12
Cloudy/Cloudy2 (3.4%)
Rain2 (3.4%)
↓-80.0%prior 10
Rain/Cloudy2 (3.4%)
Cloudy/Rain1 (1.7%)
Clear/Unknown1 (1.7%)
Clear/Sleet, hail (freezing rain or drizzle)1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash

Lighting

Daylight50 (86.2%)
↓-15.3%prior 59
Dark - lighted roadway4 (6.9%)
↓-42.9%prior 7
Dark - roadway not lighted2 (3.4%)
↓-60.0%prior 5
Dark - unknown roadway lighting1 (1.7%)
Dusk1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field

Road Surface

Dry50 (87.7%)
↓-12.3%prior 57
Wet6 (10.5%)
↓-62.5%prior 16
Sand, mud, dirt, oil, gravel1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field

Vehicles & Demographics

The age group 35-44 experienced the largest decrease in persons involved in crashes, falling from 24 in May 2024 to 12 in May 2025. Conversely, the 55-64 age group saw an increase from 15 to 24 persons. Among top vehicle makes, TOYOTA involvement decreased from 28 to 19, while SUBARU involvement increased from 5 to 9.

Top Vehicle Makes (109 vehicles)

1
TOYOTA19 (17.4%)
↓-32.1%prior 28
2
HONDA13 (11.9%)
↑18.2%prior 11
3
FORD9 (8.3%)
↓-43.8%prior 16
4
SUBARU9 (8.3%)
↑80.0%prior 5
5
JEEP7 (6.4%)
↑40.0%prior 5
6
VOLKSWAGEN5 (4.6%)
→0.0%prior 5
7
VOLVO4 (3.7%)
8
NISSAN4 (3.7%)
↓-20.0%prior 5
9
HYUNDAI3 (2.8%)
10
GMC3 (2.8%)
↓-40.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records

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

Sex Distribution (127 persons with recorded sex)

Male69 (54.3%)
↓-21.6%prior 88
Female58 (45.7%)
↓-13.4%prior 67

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 40 mph speed zones decreased from 16 in May 2024 to 10 in May 2025. Conversely, crashes in 35 mph speed zones increased from 8 to 10. The number of crashes in 25 mph speed zones remained stable at 14 in both periods. No fatal crashes were reported in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-05-01 through 2025-05-31 (31 days)
  • Geographic scope: BOURNE, MA
  • Total crash records analyzed: 59
  • Total persons involved: 136
  • Total vehicles involved: 109

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). "BOURNE, MA Crash Intelligence Report: May 2025." Published June 21, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/bourne/may-2025-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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Bourne, MA Crash Report — May 2025 | ThatCarHitMe.com