Monthly Traffic Safety Analysis

85 CRASHES IN
BOURNE, MA
OCTOBER 2023

All metrics benchmarked againstOctober 2022

Total crashes in BOURNE, MA increased significantly from 55 in October 2022 to 85 in October 2023, representing a 54.5% rise year-over-year. The most notable shift was the substantial increase in total crashes, accompanied by a change in the peak day and hour for crash occurrences.

85

54.5%was 55

Total Crash Events

0

Persons Killed

18

38.5%was 13

Persons Injured

13

62.5%was 8

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a considerable increase in crash activity year-over-year. Total crashes rose from 55 in October 2022 to 85 in October 2023, marking a 54.5% increase. Concurrently, total injuries increased from 13 to 18, while fatalities remained at 0 in both periods.

13

Hit-and-Run Crashes — October 2023

62.5% vs prior (8)

Hit-and-run crashes increased from 8 in October 2022 to 13 in October 2023. The hit-and-run rate also saw a slight increase year-over-year, rising from 14.5% to 15.3% of total crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 0%

15

Motorists Injured

Prior: 1315.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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 Saturday, with 11 crashes in October 2022, to Tuesday, with 16 crashes in October 2023. The peak hour also changed, moving from 8 AM with 7 crashes in the prior period to 4 PM with 9 crashes in the current period, indicating a shift in the busiest crash times.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total injuries increased from 13 in October 2022 to 18 in October 2023. Serious injuries (severity A) increased from 1 to 2, while possible injuries (severity C) rose from 1 to 3. Fatalities remained at 0 in both periods, indicating no change in the fatal crash rate.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes2.4%
100.0%prior 1
Minor Injury9minor injury crashes10.6%
0.0%prior 9
Possible Injury3possible injury crashes3.5%
200.0%prior 1
No Injury66no injury crashes77.6%
78.4%prior 37

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw notable increases in crash counts year-over-year. 'No improper driving' increased from 11 crashes in the prior period to 20 crashes in the current period. 'Followed too closely' rose from 6 crashes to 15 crashes, and 'Failed to yield right of way' increased from 2 crashes to 13 crashes, showing a significant rise in this specific factor.

Officer-Reported Primary Contributing Cause

No improper driving20 (23.5%)81.8%prior 11
Followed too closely15 (17.6%)150.0%prior 6
Failed to yield right of way13 (15.3%)
Inattention9 (10.6%)
Failure to keep in proper lane or running off road6 (7.1%)0.0%prior 6
Disregarded traffic signs, signals, road markings2 (2.4%)
Made an improper turn2 (2.4%)
Driving too fast for conditions2 (2.4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (2.4%)
Illness1 (1.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 38 to 61 year-over-year, while those during 'Daylight' conditions rose from 31 to 56. Conversely, crashes in 'Dark - lighted roadway' conditions decreased from 14 in the prior period to 6 in the current period. The count of crashes on 'Wet' road surfaces remained stable at 15 in both periods.

Weather

Clear61 (77.2%)
60.5%prior 38
Cloudy6 (7.6%)
Rain6 (7.6%)
Cloudy/Rain5 (6.3%)
Fog, smog, smoke1 (1.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash

Lighting

Daylight56 (67.5%)
80.6%prior 31
Dark - roadway not lighted15 (18.1%)
87.5%prior 8
Dark - lighted roadway6 (7.2%)
-57.1%prior 14
Dusk4 (4.8%)
Dawn2 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field

Road Surface

Dry68 (81.9%)
74.4%prior 39
Wet15 (18.1%)
0.0%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 91 to 155 year-over-year. TOYOTA vehicles involved increased from 12 to 28, and CHEVROLET vehicles increased from 8 to 15. The 55-64 age group saw a substantial increase in representation, from 13 persons in the prior period to 37 persons in the current period.

Top Vehicle Makes (155 vehicles)

1
TOYOTA28 (18.1%)
133.3%prior 12
2
CHEVROLET15 (9.7%)
87.5%prior 8
3
HONDA14 (9%)
55.6%prior 9
4
NISSAN11 (7.1%)
83.3%prior 6
5
GMC9 (5.8%)
80.0%prior 5
6
FORD8 (5.2%)
0.0%prior 8
7
BMW7 (4.5%)
8
JEEP5 (3.2%)
9
AUDI5 (3.2%)
10
KIA4 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records

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

Sex Distribution (163 persons with recorded sex)

Male85 (52.1%)
51.8%prior 56
Female78 (47.9%)
105.3%prior 38

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones increased from 13 to 16, and those in 55 mph zones saw a notable rise from 5 to 14. In contrast, crashes in 40 mph zones decreased from 12 to 9. No fatal crashes were reported in any speed limit zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-10-01 through 2023-10-31 (31 days)
  • Geographic scope: BOURNE, MA
  • Total crash records analyzed: 85
  • Total persons involved: 187
  • Total vehicles involved: 155

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: October 2023." Published June 21, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/bourne/october-2023-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 — October 2023 | ThatCarHitMe.com