Monthly Traffic Safety Analysis

32 CRASHES IN
DEDHAM, MA
APRIL 2024

All metrics benchmarked againstApril 2023

Total crashes in DEDHAM, MA decreased by 18.0% from 39 crashes in April 2023 to 32 crashes in April 2024. Total injuries also saw a substantial reduction, falling from 17 to 5 year-over-year. The most notable shift was a significant 85.7% decrease in hit-and-run crashes, from 7 to 1.

32

-17.9%was 39

Total Crash Events

0

Persons Killed

5

-70.6%was 17

Persons Injured

1

-85.7%was 7

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend for crashes in DEDHAM, MA for April indicates a decrease year-over-year. Total crashes fell from 39 in April 2023 to 32 in April 2024, representing a reduction of 7 crashes or 18.0%. Total injuries also decreased from 17 to 5, a 70.6% reduction.

1

Hit-and-Run Crashes — April 2024

-85.7% vs prior (7)

Hit-and-run crashes decreased substantially from 7 incidents in April 2023 to 1 incident in April 2024. This change resulted in the hit-and-run rate falling from 17.9% of all crashes in April 2023 to 3.1% in April 2024, indicating a downward trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 17-70.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Saturday with 10 crashes in April 2023 to Thursday with 9 crashes in April 2024. The peak hour also changed, moving from 5 PM with 6 crashes in April 2023 to 3 PM with 5 crashes in April 2024. These changes indicate a shift in the busiest times for crash incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes reported in either April 2023 or April 2024. The proportion of injury crashes decreased from 35.9% (14 out of 39 crashes) in April 2023 to 12.5% (4 out of 32 crashes) in April 2024. Specifically, minor injury crashes decreased from 5 to 2, and possible injury crashes decreased from 8 to 1.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes3.1%
0.0%prior 1
Minor Injury2minor injury crashes6.3%
-60.0%prior 5
Possible Injury1possible injury crashes3.1%
-87.5%prior 8
No Injury27no injury crashes84.4%
12.5%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'No improper driving' increased in count from 7 in April 2023 to 11 in April 2024. 'Followed too closely' also increased from 4 to 8 crashes year-over-year. Conversely, 'Failed to yield right of way' saw a significant decrease from 8 crashes in April 2023 to 1 crash in April 2024, while 'Inattention' decreased from 4 to 3 crashes.

Officer-Reported Primary Contributing Cause

No improper driving11 (34.4%)57.1%prior 7
Followed too closely8 (25%)
Inattention3 (9.4%)
Fatigued/asleep2 (6.3%)
Over-correcting/over-steering1 (3.1%)
Illness1 (3.1%)
Exceeded authorized speed limit1 (3.1%)
Failed to yield right of way1 (3.1%)-87.5%prior 8
Distracted1 (3.1%)
Other improper action1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear/Clear' weather conditions decreased from 21 in April 2023 to 12 in April 2024. The number of crashes on dry road surfaces decreased from 34 to 26 year-over-year, while crashes on wet surfaces decreased from 5 to 4. Crashes occurring during daylight hours decreased from 25 to 21, with non-daylight crashes decreasing from 14 to 11.

Weather

Clear/Clear12 (37.5%)
-42.9%prior 21
Clear11 (34.4%)
22.2%prior 9
Cloudy/Cloudy3 (9.4%)
Rain/Cloudy1 (3.1%)
Rain/Rain1 (3.1%)
Sleet, hail (freezing rain or drizzle)1 (3.1%)
Sleet, hail (freezing rain or drizzle)/Sleet, hail (freezing rain or drizzle)1 (3.1%)
Cloudy/Rain1 (3.1%)
Rain1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Weather condition at time of crash

Lighting

Daylight21 (65.6%)
-16.0%prior 25
Dark - lighted roadway5 (15.6%)
-16.7%prior 6
Dark - roadway not lighted3 (9.4%)
Dusk3 (9.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Lighting condition field

Road Surface

Dry26 (81.3%)
-23.5%prior 34
Wet4 (12.5%)
-20.0%prior 5
Other1 (3.1%)
Slush1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Road surface condition field

Vehicles & Demographics

The top vehicle make involved in crashes, Toyota, decreased from 19 vehicles in April 2023 to 10 vehicles in April 2024. Honda vehicles involved decreased from 9 to 7. The age group 45-54 saw a decrease in persons involved from 20 to 15, while the 21-25 age group increased from 6 to 10 persons involved.

Top Vehicle Makes (59 vehicles)

1
TOYOTA10 (16.9%)
-47.4%prior 19
2
HONDA7 (11.9%)
-22.2%prior 9
3
FORD5 (8.5%)
-28.6%prior 7
4
NISSAN4 (6.8%)
5
ACURA3 (5.1%)
6
INFI3 (5.1%)
7
SUBARU3 (5.1%)
8
LEXUS2 (3.4%)
9
BMW2 (3.4%)
10
GMC2 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Vehicle unit records

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

Sex Distribution (70 persons with recorded sex)

Male42 (60.0%)
7.7%prior 39
Female28 (40.0%)
-22.2%prior 36

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Person-level records linked to crash events

Speed Limit Zones

There were no fatal crashes recorded in any speed limit zone for either period. Crashes in 30 mph zones decreased from 7 in April 2023 to 3 in April 2024. Similarly, crashes in 35 mph zones decreased from 3 to 1, and 45 mph zones decreased from 2 to 1. The number of crashes in 55 mph zones remained stable at 10 for both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · 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: 2024-04-01 through 2024-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-04-01 through 2024-04-30 (30 days)
  • Geographic scope: DEDHAM, MA
  • Total crash records analyzed: 32
  • Total persons involved: 71
  • Total vehicles involved: 59

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). "DEDHAM, MA Crash Intelligence Report: April 2024." Published June 21, 2026. Reporting period: 2024-04-01 to 2024-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/dedham/april-2024-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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Dedham, MA Crash Report — April 2024 | ThatCarHitMe.com