Yearly Traffic Safety Analysis

357 CRASHES IN
DENNIS, MA
2024

All metrics benchmarked against2023

In 2024, Dennis recorded 357 total traffic crashes, representing a 2.7% decrease from the 367 crashes documented in 2023. Despite this overall reduction in collisions, the total number of injuries increased significantly. The most notable year-over-year shift was a 38.2% rise in persons injured, which grew from 76 in 2023 to 105 in 2024.

357

-2.7%was 367

Total Crash Events

0

Persons Killed

105

38.2%was 76

Persons Injured

30

36.4%was 22

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash totals in Dennis showed a slight year-over-year decline of 2.7%, down from 367 incidents in 2023 to 357 in 2024. In contrast, the number of reported injuries rose by 38.2% during the same period. The number of fatalities remained stable, with zero recorded in both years.

30

Hit-and-Run Crashes — 2024

36.4% vs prior (22)

The number of hit-and-run crashes increased by 36.4% year-over-year, rising from 22 incidents in 2023 to 30 in 2024. This corresponds to an increase in the hit-and-run rate as a percentage of all crashes, which grew from 6.0% in the prior year to 8.4% in the current year. The data indicates an upward trend for hit-and-run incidents in both absolute count and rate.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

5

Pedestrians Injured

Prior: 2150.0%

5

Cyclists Injured

Prior: 366.7%

95

Motorists Injured

Prior: 7133.8%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes showed a notable shift in the peak time of day. While Friday remained the busiest day for crashes in both 2023 and 2024 with 61 incidents, the peak hour changed significantly. In 2023, the highest number of crashes occurred at 5 PM (36 crashes), whereas in 2024, the peak shifted to the late morning at 11 AM (31 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The proportion of crashes resulting in an injury increased from 15.8% in 2023 to 21.3% in 2024. There were no fatal crashes recorded in either period. While the count of serious injury crashes decreased from 10 to 4, crashes involving minor injuries rose from 30 to 46, and possible injury crashes increased from 18 to 26.

Outcome by Severity (Crash Events)

Serious Injury4serious injury crashes1.1%
-60.0%prior 10
Minor Injury46minor injury crashes12.9%
53.3%prior 30
Possible Injury26possible injury crashes7.3%
44.4%prior 18
No Injury263no injury crashes73.7%
-10.5%prior 294

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Inattention was the top contributing factor in both periods, though its count decreased by 7.8% from 116 crashes in 2023 to 107 in 2024. The count of crashes where a driver 'Failed to yield right of way' increased by 28.1%, from 32 to 41 incidents. Conversely, crashes attributed to 'Followed too closely' decreased by 16.7% (from 24 to 20). The top three cited factors remained consistent across both years.

Officer-Reported Primary Contributing Cause

Inattention107 (30%)-7.8%prior 116
No improper driving80 (22.4%)25.0%prior 64
Failed to yield right of way41 (11.5%)28.1%prior 32
Followed too closely20 (5.6%)-16.7%prior 24
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner13 (3.6%)-38.1%prior 21
Distracted8 (2.2%)-50.0%prior 16
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway8 (2.2%)
Failure to keep in proper lane or running off road8 (2.2%)60.0%prior 5
Other improper action8 (2.2%)-42.9%prior 14
Disregarded traffic signs, signals, road markings5 (1.4%)-37.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Driving conditions for crashes remained broadly similar year-over-year. Crashes on dry roads accounted for approximately 83% of all incidents in both 2023 and 2024, and collisions in wet conditions made up about 13% in both periods. Daylight was the dominant lighting condition, present in 72.0% of crashes in 2024 compared to 74.1% in 2023.

Weather

Clear279 (78.6%)
3.7%prior 269
Rain28 (7.9%)
3.7%prior 27
Cloudy25 (7.0%)
-41.9%prior 43
Rain/Cloudy6 (1.7%)
Cloudy/Rain4 (1.1%)
-66.7%prior 12
Snow/Sleet, hail (freezing rain or drizzle)2 (0.6%)
Snow/Blowing sand, snow2 (0.6%)
Rain/Severe crosswinds2 (0.6%)
Snow2 (0.6%)
Cloudy/Clear1 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight257 (72.2%)
-5.5%prior 272
Dark - lighted roadway54 (15.2%)
10.2%prior 49
Dark - roadway not lighted29 (8.1%)
7.4%prior 27
Dusk12 (3.4%)
20.0%prior 10
Dawn3 (0.8%)
-40.0%prior 5
Dark - unknown roadway lighting1 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry299 (84.0%)
-2.3%prior 306
Wet48 (13.5%)
-2.0%prior 49
Snow5 (1.4%)
Ice3 (0.8%)
Sand, mud, dirt, oil, gravel1 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The most common vehicle makes involved in crashes were largely unchanged, with Toyota, Ford, and Honda leading in 2024. The count of Toyotas involved decreased from 117 to 101, while Ford remained stable at 68. A demographic shift was observed among persons involved in crashes; the share of individuals aged 65 and older decreased from 24.2% in 2023 to 19.8% in 2024, while the 45-54 age group's share increased from 8.7% to 13.8%.

Top Vehicle Makes (627 vehicles)

1
TOYOTA101 (16.1%)
-13.7%prior 117
2
FORD68 (10.8%)
0.0%prior 68
3
HONDA64 (10.2%)
3.2%prior 62
4
CHEVROLET58 (9.3%)
-9.4%prior 64
5
JEEP37 (5.9%)
76.2%prior 21
6
NISSAN36 (5.7%)
20.0%prior 30
7
SUBARU25 (4%)
-19.4%prior 31
8
GMC23 (3.7%)
4.5%prior 22
9
HYUNDAI17 (2.7%)
-19.0%prior 21
10
DODGE15 (2.4%)
87.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (704 persons with recorded sex)

Male398 (56.5%)
-5.0%prior 419
Female306 (43.5%)
-13.1%prior 352

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

The 35 mph speed zone was the site of the most crashes in both years, although the count in this zone fell from 122 in 2023 to 101 in 2024. A notable shift occurred in lower speed zones, where crashes in 10 mph zones increased from 7 to 23. Incidents also decreased in the 30 mph (from 82 to 69) and 40 mph (from 37 to 26) zones. No fatal crashes were recorded in any speed zone in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: DENNIS, MA
  • Total crash records analyzed: 357
  • Total persons involved: 788
  • Total vehicles involved: 627

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). "DENNIS, MA Crash Intelligence Report: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/dennis/2024-annual-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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Dennis, MA Crash Report — 2024 | ThatCarHitMe.com