Monthly Traffic Safety Analysis

49 CRASHES IN
DARTMOUTH, MA
OCTOBER 2023

All metrics benchmarked againstOctober 2022

Total crashes in Dartmouth decreased by 10.9% from 55 in October 2022 to 49 in October 2023. A notable shift was the 300% increase in hit-and-run crashes, rising from 1 incident in the prior period to 4 in the current period.

49

-10.9%was 55

Total Crash Events

0

Persons Killed

28

12.0%was 25

Persons Injured

4

300.0%was 1

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.

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

Overall, total crashes in Dartmouth decreased by 10.9% from 55 crashes in October 2022 to 49 crashes in October 2023. Despite this reduction in total crashes, total injuries increased by 12.0%, from 25 to 28, while fatalities remained at zero for both periods.

4

Hit-and-Run Crashes — October 2023

300.0% vs prior (1)

Hit-and-run crashes increased significantly from 1 in October 2022 to 4 in October 2023, representing a 300% increase in count. The hit-and-run rate also rose from 1.8% of all crashes in the prior period to 8.2% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

28

Motorists Injured

Prior: 2512.0%

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 Wednesday with 11 crashes in October 2022 to Tuesday with 12 crashes in October 2023. The peak hour also changed, moving from 8a with 6 crashes in the prior period to 4p with 8 crashes in the current period.

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

There were no fatal crashes in either October 2022 or October 2023. Serious injuries (Severity A) increased from 0 in the prior period to 2 in the current period. Minor injuries (Severity B) increased from 11 to 13, while possible injuries (Severity C) decreased from 7 to 4.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes4.1%
Minor Injury13minor injury crashes26.5%
18.2%prior 11
Possible Injury4possible injury crashes8.2%
-42.9%prior 7
No Injury30no injury crashes61.2%
-16.7%prior 36

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

Among contributing factors, 'Inattention' increased by 62.5% in count, rising from 8 crashes in October 2022 to 13 crashes in October 2023. 'No improper driving' also saw a significant increase of 400% in count, from 2 to 10 crashes. Conversely, 'Failure to keep in proper lane or running off road' decreased by 83.3% in count, from 6 crashes to 1.

Officer-Reported Primary Contributing Cause

Inattention13 (26.5%)62.5%prior 8
No improper driving10 (20.4%)
Failed to yield right of way7 (14.3%)40.0%prior 5
Followed too closely5 (10.2%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway3 (6.1%)
Other improper action2 (4.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2%)
Visibility obstructed1 (2%)
Disregarded traffic signs, signals, road markings1 (2%)
Driving too fast for conditions1 (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 slightly from 33 in October 2022 to 35 in October 2023, while 'Rain' condition crashes decreased from 9 to 5. Crashes during 'Daylight' hours increased from 31 to 33, but those in 'Dark - lighted roadway' conditions decreased from 16 to 10. Crashes on 'Dry' road surfaces remained constant at 40, while 'Wet' road surface crashes decreased from 15 to 9.

Weather

Clear35 (71.4%)
6.1%prior 33
Cloudy6 (12.2%)
-14.3%prior 7
Rain5 (10.2%)
-44.4%prior 9
Clear/Cloudy1 (2.0%)
Clear/Other1 (2.0%)
Cloudy/Fog, smog, smoke1 (2.0%)

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

Lighting

Daylight33 (67.3%)
6.5%prior 31
Dark - lighted roadway10 (20.4%)
-37.5%prior 16
Dark - roadway not lighted3 (6.1%)
-50.0%prior 6
Dusk2 (4.1%)
Dawn1 (2.0%)

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

Road Surface

Dry40 (81.6%)
0.0%prior 40
Wet9 (18.4%)
-40.0%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 92 in October 2022 to 98 in October 2023. Toyota vehicles involved in crashes increased from 11 to 18, while Ford vehicles decreased from 17 to 10. In terms of age distribution, persons aged 0-15 involved in crashes increased significantly from 2 to 18, and those aged 26-34 increased from 7 to 17.

Top Vehicle Makes (98 vehicles)

1
TOYOTA18 (18.4%)
63.6%prior 11
2
NISSAN11 (11.2%)
120.0%prior 5
3
FORD10 (10.2%)
-41.2%prior 17
4
HONDA8 (8.2%)
-38.5%prior 13
5
GMC7 (7.1%)
40.0%prior 5
6
CHEVROLET6 (6.1%)
0.0%prior 6
7
VOLKSWAGEN4 (4.1%)
8
HYUNDAI4 (4.1%)
9
JEEP3 (3.1%)
10
KIA3 (3.1%)

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

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

Sex Distribution (119 persons with recorded sex)

Male62 (52.1%)
19.2%prior 52
Female57 (47.9%)
16.3%prior 49

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 30 MPH speed zones decreased slightly from 13 in October 2022 to 12 in October 2023. Crashes in 35 MPH zones saw a decrease from 17 to 9, while those in 40 MPH zones increased from 12 to 13. Crashes in 65 MPH speed zones increased from 5 to 7. There were no fatal crashes reported in any speed 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: DARTMOUTH, MA
  • Total crash records analyzed: 49
  • Total persons involved: 129
  • Total vehicles involved: 98

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). "DARTMOUTH, 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/dartmouth/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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Dartmouth, MA Crash Report — October 2023 | ThatCarHitMe.com