Monthly Traffic Safety Analysis

33 CRASHES IN
DARTMOUTH, MA
JULY 2023

All metrics benchmarked againstJuly 2022

Total crashes in Dartmouth decreased by 45.9%, from 61 crashes in July 2022 to 33 crashes in July 2023. The most notable shift was the occurrence of one fatality in July 2023, compared to zero fatalities in July 2022.

33

-45.9%was 61

Total Crash Events

1

Persons Killed

16

-38.5%was 26

Persons Injured

2

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Dartmouth showed a significant downward trend year-over-year, decreasing from 61 crashes in July 2022 to 33 crashes in July 2023. This represents a reduction of 28 crashes, or 45.9%.

2

Hit-and-Run Crashes — July 2023

6.1% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

16

Motorists Injured

Prior: 26-38.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes shifted between the two periods. In July 2023, the peak day for crashes was Wednesday with 8 incidents, and the peak hour was 3p with 4 incidents. This contrasts with July 2022, when the peak day was Friday with 12 crashes and the peak hour was 9a with 7 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution of crashes changed year-over-year, with the fatal crash rate increasing from 0% in July 2022 to 3.03% in July 2023, corresponding to one fatal crash. The proportion of minor injury crashes increased from 23% in July 2022 to 30.3% in July 2023, while serious injury crash proportions remained similar at 3.3% and 3% respectively.

Outcome by Severity (Crash Events)

Fatal1fatal crashes3%
Serious Injury1serious injury crashes3%
-50.0%prior 2
Minor Injury10minor injury crashes30.3%
-28.6%prior 14
Possible Injury2possible injury crashes6.1%
-60.0%prior 5
No Injury18no injury crashes54.5%
-55.0%prior 40

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Most severe injury per crash record

Top Contributing Factors

Several top contributing factors saw reductions in crash counts year-over-year. Crashes attributed to 'Inattention' decreased from 14 in July 2022 to 5 in July 2023, a 64.3% reduction. 'Failed to yield right of way' crashes decreased by 50%, from 8 to 4, and 'No improper driving' crashes decreased by 42.9%, from 7 to 4. Conversely, crashes involving 'Exceeded authorized speed limit' increased from 1 in July 2022 to 2 in July 2023.

Officer-Reported Primary Contributing Cause

Inattention5 (15.2%)-64.3%prior 14
No improper driving4 (12.1%)-42.9%prior 7
Failed to yield right of way4 (12.1%)-50.0%prior 8
Failure to keep in proper lane or running off road4 (12.1%)
Followed too closely3 (9.1%)
Exceeded authorized speed limit2 (6.1%)
Distracted2 (6.1%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (6.1%)
Over-correcting/over-steering2 (6.1%)
Glare1 (3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in 'Clear' weather conditions decreased from 95.1% (58 of 61 crashes) in July 2022 to 84.8% (28 of 33 crashes) in July 2023. The proportion of crashes occurring in 'Daylight' conditions remained relatively stable, accounting for 75.4% in July 2022 and 75.8% in July 2023. Similarly, the proportion of crashes on 'Dry' road surfaces saw a slight decrease from 96.7% (59 of 61 crashes) to 93.9% (31 of 33 crashes).

Weather

Clear28 (84.8%)
-51.7%prior 58
Cloudy3 (9.1%)
Clear/Other1 (3.0%)
Cloudy/Rain1 (3.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Weather condition at time of crash

Lighting

Daylight25 (75.8%)
-45.7%prior 46
Dark - lighted roadway6 (18.2%)
20.0%prior 5
Dark - roadway not lighted1 (3.0%)
Dusk1 (3.0%)
-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Lighting condition field

Road Surface

Dry31 (93.9%)
-47.5%prior 59
Wet2 (6.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 113 in July 2022 to 53 in July 2023. Toyota remained the top vehicle make involved, though its count decreased from 16 to 9. The age group 26-34 saw a significant reduction in persons involved, from 29 in July 2022 to 8 in July 2023, while the 45-54 age group also decreased from 27 to 10 persons involved.

Top Vehicle Makes (53 vehicles)

1
TOYOTA9 (17%)
-43.8%prior 16
2
NISSAN6 (11.3%)
0.0%prior 6
3
HONDA5 (9.4%)
-58.3%prior 12
4
JEEP4 (7.5%)
-33.3%prior 6
5
FORD4 (7.5%)
-66.7%prior 12
6
DODGE3 (5.7%)
7
GMC3 (5.7%)
8
CHEVROLET2 (3.8%)
-77.8%prior 9
9
KIA2 (3.8%)
-75.0%prior 8
10
MERCEDES-BENZ2 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Vehicle unit records

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

Sex Distribution (65 persons with recorded sex)

Male34 (52.3%)
-55.3%prior 76
Female31 (47.7%)
-53.7%prior 67

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Person-level records linked to crash events

Speed Limit Zones

The total number of crashes with recorded speed limits decreased from 61 in July 2022 to 33 in July 2023. Crashes in 30 mph zones decreased from 25 to 11, and in 40 mph zones from 13 to 11. Notably, the single fatal crash in July 2023 occurred in a 40 mph zone, whereas no fatal crashes were recorded in any speed zone during July 2022.

Fatal crashes by zone: 40 mph: 1 of 11 (9.091%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · 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: 2023-07-01 through 2023-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-07-01 through 2023-07-31 (31 days)
  • Geographic scope: DARTMOUTH, MA
  • Total crash records analyzed: 33
  • Total persons involved: 76
  • Total vehicles involved: 53

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: July 2023." Published June 21, 2026. Reporting period: 2023-07-01 to 2023-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/dartmouth/july-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 — July 2023 | ThatCarHitMe.com