Monthly Traffic Safety Analysis

49 CRASHES IN
DARTMOUTH, MA
APRIL 2022

All metrics benchmarked againstApril 2021

Total crashes in Dartmouth increased by 36.1% year-over-year, rising from 36 in April 2021 to 49 in April 2022. This period saw a significant 220% increase in total injuries, climbing from 5 to 16. The emergence of 2 serious injury crashes in the current period, compared to none in the prior, marks a notable shift in crash severity.

49

36.1%was 36

Total Crash Events

0

Persons Killed

16

220.0%was 5

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 · 2022-04-01 to 2022-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Dartmouth experienced an upward trend year-over-year, increasing from 36 incidents in April 2021 to 49 in April 2022. This represents a 36.1% rise in total crashes. Concurrently, total injuries saw a substantial increase of 220%, rising from 5 to 16.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

16

Motorists Injured

Prior: 5220.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Friday, though the count decreased slightly from 10 crashes in April 2021 to 9 crashes in April 2022. The peak hour shifted from 3 PM in the prior period with 7 crashes to 9 AM in the current period, also with 7 crashes. This indicates a shift in the timing of peak crash activity from afternoon to morning.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities in either April 2021 or April 2022. Total injuries increased significantly from 5 in the prior period to 16 in the current period, a 220% rise. Serious injury crashes (severity A) appeared in the current period with 2 incidents, accounting for 4.1% of all crashes, whereas no serious injury crashes were reported in the prior period.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes4.1%
Minor Injury10minor injury crashes20.4%
150.0%prior 4
Possible Injury3possible injury crashes6.1%
200.0%prior 1
No Injury34no injury crashes69.4%
9.7%prior 31

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Most severe injury per crash record

Top Contributing Factors

Inattention remained the leading contributing factor, increasing from 8 crashes to 11 crashes year-over-year. Crashes attributed to "No improper driving" saw a notable increase from 3 to 7 incidents. Conversely, "Followed too closely" crashes significantly decreased from 5 to 1, while "Failed to yield right of way" also saw a decrease from 5 to 4 incidents.

Officer-Reported Primary Contributing Cause

Inattention11 (22.4%)37.5%prior 8
No improper driving7 (14.3%)
Failed to yield right of way4 (8.2%)-20.0%prior 5
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway3 (6.1%)
Visibility obstructed3 (6.1%)
Disregarded traffic signs, signals, road markings2 (4.1%)
Distracted2 (4.1%)
Driving too fast for conditions2 (4.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (4.1%)
Made an improper turn1 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under clear weather conditions significantly increased from 25 to 42, while those in rainy conditions decreased from 4 to 1. Similarly, crashes on dry road surfaces rose from 29 to 46, contrasting with a reduction in wet road crashes from 7 to 3. The proportion of crashes occurring during daylight hours also increased, from 29 to 40.

Weather

Clear42 (85.7%)
68.0%prior 25
Cloudy5 (10.2%)
Fog, smog, smoke1 (2.0%)
Rain1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Weather condition at time of crash

Lighting

Daylight40 (81.6%)
37.9%prior 29
Dark - lighted roadway6 (12.2%)
20.0%prior 5
Dawn2 (4.1%)
Dark - roadway not lighted1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Lighting condition field

Road Surface

Dry46 (93.9%)
58.6%prior 29
Wet3 (6.1%)
-57.1%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes increased from 75 to 109 year-over-year. The 55-64 age group saw the largest increase, from 7 persons to 20 persons, while the 26-34 age group also increased significantly from 7 to 19 persons. Toyota became the most frequently involved vehicle make, increasing from 8 vehicles in the prior period to 16 in the current period, surpassing Ford which decreased from 10 to 6.

Top Vehicle Makes (92 vehicles)

1
TOYOTA16 (17.4%)
100.0%prior 8
2
NISSAN13 (14.1%)
62.5%prior 8
3
HONDA9 (9.8%)
4
FORD6 (6.5%)
-40.0%prior 10
5
JEEP6 (6.5%)
6
HYUNDAI5 (5.4%)
7
SUBARU4 (4.3%)
8
LEXUS4 (4.3%)
9
MAZDA4 (4.3%)
10
CHEVROLET3 (3.3%)
-66.7%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Vehicle unit records

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

Sex Distribution (104 persons with recorded sex)

Male59 (56.7%)
28.3%prior 46
Female45 (43.3%)
87.5%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Person-level records linked to crash events

Speed Limit Zones

No fatal crashes occurred in any speed zone in either period. Crashes in 30 mph zones increased significantly from 8 to 16 incidents year-over-year. There was also a notable increase in crashes within 35 mph zones, rising from 3 to 8, and in 65 mph zones, increasing from 3 to 6.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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: 2022-04-01 through 2022-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-04-01 through 2022-04-30 (30 days)
  • Geographic scope: DARTMOUTH, MA
  • Total crash records analyzed: 49
  • Total persons involved: 109
  • Total vehicles involved: 92

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: April 2022." Published June 21, 2026. Reporting period: 2022-04-01 to 2022-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/dartmouth/april-2022-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

ThatCarHitMe.com · An Injuria.ai Company

Dartmouth, MA Crash Report — April 2022 | ThatCarHitMe.com