Yearly Traffic Safety Analysis

427 CRASHES IN
DANVERS, MA
2024

All metrics benchmarked against2023

In Danvers, total traffic crashes remained nearly stable year-over-year, with 427 incidents in 2024 compared to 426 in 2023, an increase of less than one percent. The most significant change was the occurrence of two fatal crashes resulting in two fatalities in 2024, whereas no fatalities were recorded in the prior year. The total number of persons injured also increased by 7.3%, from 164 to 176.

427

0.2%was 426

Total Crash Events

2

Persons Killed

176

7.3%was 164

Persons Injured

20

-25.9%was 27

Hit-and-Run Crashes

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 7 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

The overall trend in crash volume in Danvers was stable, with total incidents increasing by just one crash from 426 in 2023 to 427 in 2024. However, the severity of these crashes increased, as evidenced by a 7.3% rise in total injuries from 164 to 176 and the appearance of two fatalities in 2024 after none in the previous year.

20

Hit-and-Run Crashes — 2024

-25.9% vs prior (27)

The number of hit-and-run incidents in Danvers decreased from 27 in 2023 to 20 in 2024, a reduction of 25.9%. This downward trend is also reflected in the hit-and-run rate, which fell from 6.3% of all crashes in the prior year to 4.7% in the current year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

2

Motorists Killed

Prior: 0%

0

Other Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 5-40.0%

7

Cyclists Injured

Prior: 1600.0%

165

Motorists Injured

Prior: 1565.8%

1

Other Injured

Prior: 2-50.0%

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 patterns of crashes showed some shifts between the two periods. The peak day for crashes moved from Wednesday (72 crashes) in 2023 to Friday (75 crashes) in 2024. The peak hour for collisions also shifted slightly earlier, from 4 p.m. in 2023 (42 crashes) to a two-hour window between 2 p.m. and 3 p.m. in 2024, which each recorded 42 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

Crash severity increased in 2024 with the recording of two fatal incidents, which accounted for 0.5% of all crashes, compared to zero fatal crashes in 2023. The number of serious injury crashes was stable at nine in both years. Despite the new fatalities, the overall proportion of crashes involving any injury (from possible to fatal) saw a slight decrease from 31.9% of crashes in 2023 (136 incidents) to 31.6% in 2024 (135 incidents).

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.5%
Serious Injury9serious injury crashes2.1%
0.0%prior 9
Minor Injury90minor injury crashes21.1%
-9.1%prior 99
Possible Injury34possible injury crashes8%
21.4%prior 28
No Injury285no injury crashes66.7%
-0.3%prior 286

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

The leading contributing factors for crashes shifted year-over-year. 'Inattention' became the top factor in 2024, with the count of related crashes rising by 45.8% from 59 to 86. Conversely, crashes with 'No improper driving' cited as a factor decreased by 21.6%, from 88 incidents in 2023 to 69 in 2024, moving it from the top position to second. The count of crashes involving 'Failed to yield right of way' also saw a substantial increase of 53.1%, growing from 32 to 49 incidents.

Officer-Reported Primary Contributing Cause

Inattention86 (20.1%)45.8%prior 59
No improper driving69 (16.2%)-21.6%prior 88
Failed to yield right of way49 (11.5%)53.1%prior 32
Followed too closely31 (7.3%)10.7%prior 28
Other improper action20 (4.7%)33.3%prior 15
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner18 (4.2%)12.5%prior 16
Driving too fast for conditions16 (3.7%)33.3%prior 12
Disregarded traffic signs, signals, road markings15 (3.5%)150.0%prior 6
Distracted14 (3.3%)133.3%prior 6
Failure to keep in proper lane or running off road12 (2.8%)-20.0%prior 15

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

Crashes were more likely to occur on dry roads in 2024 compared to the prior year. The number of crashes on dry surfaces increased from 323 to 348, while crashes on wet surfaces decreased from 83 to 61. Consequently, the share of crashes happening on non-dry road surfaces (wet, snow, ice, or slush) dropped from 24.2% in 2023 to 18.3% in 2024. Lighting conditions remained broadly similar, with daylight crashes accounting for 72.6% of incidents in 2024, up from 69.5% in 2023.

Weather

Clear264 (62.0%)
0.4%prior 263
Clear/Clear47 (11.0%)
56.7%prior 30
Cloudy46 (10.8%)
0.0%prior 46
Rain18 (4.2%)
-53.8%prior 39
Cloudy/Rain11 (2.6%)
0.0%prior 11
Snow9 (2.1%)
0.0%prior 9
Rain/Rain5 (1.2%)
Rain/Cloudy5 (1.2%)
Clear/Cloudy4 (0.9%)
Rain/Fog, smog, smoke2 (0.5%)

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

Lighting

Daylight310 (72.8%)
4.7%prior 296
Dark - lighted roadway84 (19.7%)
-3.4%prior 87
Dark - roadway not lighted18 (4.2%)
-30.8%prior 26
Dawn8 (1.9%)
Dusk6 (1.4%)
-50.0%prior 12

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

Road Surface

Dry348 (81.7%)
7.7%prior 323
Wet61 (14.3%)
-26.5%prior 83
Snow9 (2.1%)
-35.7%prior 14
Ice4 (0.9%)
Slush3 (0.7%)
Other1 (0.2%)

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 remained consistent, with Toyota, Honda, and Ford being the top three in both 2024 and 2023. While vehicle makes were stable, there was a significant demographic shift among persons involved in crashes. The number of individuals in the 0-15 age group more than doubled, increasing from 36 in 2023 to 91 in 2024. This occurred even as the total number of people involved in all crashes decreased slightly from 1105 to 1073.

Top Vehicle Makes (802 vehicles)

1
TOYOTA128 (16%)
6.7%prior 120
2
HONDA123 (15.3%)
21.8%prior 101
3
FORD84 (10.5%)
6.3%prior 79
4
NISSAN53 (6.6%)
15.2%prior 46
5
CHEVROLET50 (6.2%)
-15.3%prior 59
6
JEEP44 (5.5%)
-4.3%prior 46
7
SUBARU43 (5.4%)
16.2%prior 37
8
HYUNDAI25 (3.1%)
-7.4%prior 27
9
VOLKSWAGEN22 (2.7%)
0.0%prior 22
10
LEXUS16 (2%)
-11.1%prior 18

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

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

Sex Distribution (971 persons with recorded sex)

Male539 (55.5%)
24.8%prior 432
Female432 (44.5%)
-2.3%prior 442

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

In 2024, two fatal crashes occurred, one in a 30 mph zone and another in a 50 mph zone; no fatal crashes were recorded in 2023. There was a noticeable shift in where crashes occurred, with incidents in 30 mph zones increasing from 132 to 152 year-over-year. Conversely, crashes in higher speed zones, such as 35 mph and 55 mph, saw decreases from 75 to 59 and 51 to 37, respectively.

Fatal crashes by zone: 30 mph: 1 of 152 (0.658%) · 50 mph: 1 of 32 (3.125%)

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: DANVERS, MA
  • Total crash records analyzed: 427
  • Total persons involved: 1,073
  • Total vehicles involved: 802

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). "DANVERS, 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/danvers/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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Danvers, MA Crash Report — 2024 | ThatCarHitMe.com