Yearly Traffic Safety Analysis

35 CRASHES IN
ESSEX, MA
2024

All metrics benchmarked against2023

In Essex, the total number of traffic crashes was unchanged year-over-year, with 35 incidents recorded in both the current and prior periods. There were no fatalities in either year. The most notable change was a 25% increase in the number of people injured, which rose from 8 in the prior year to 10 in the current year.

35

Total Crash Events

0

Persons Killed

10

25.0%was 8

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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Essex remained stable, with the total count holding steady at 35 incidents year-over-year. While the volume of crashes did not change, the number of resulting injuries increased by 25%, from 8 to 10 persons. Fatalities remained at zero for both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

10

Motorists Injured

Prior: 825.0%

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 pattern of crashes shifted between the two periods. The peak day for collisions moved from Friday (9 crashes) in the prior year to Saturday (10 crashes) in the current year, with Saturday crashes more than doubling from 4 to 10 incidents. The peak hour for crashes, however, remained consistent at 4 p.m. in both years, accounting for 4 crashes in each period.

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

While total crashes were stable, injury outcomes changed year-over-year. The total number of people injured increased from 8 to 10, and the current period saw one serious injury crash, a category with zero incidents in the prior year. Conversely, crashes resulting in minor injuries decreased from 4 to 2. The proportion of non-injury crashes increased from 80% to 85.7% of all incidents.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.9%
Minor Injury2minor injury crashes5.7%
-50.0%prior 4
Possible Injury2possible injury crashes5.7%
-33.3%prior 3
No Injury30no injury crashes85.7%
7.1%prior 28

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 factor cited in both periods was "No improper driving," with counts of 16 in the current year and 15 in the prior year. Crashes where distraction was a factor decreased in count from 4 to 3. "Failed to yield right of way" and "Failure to keep in proper lane" each accounted for 3 crashes in the current year, replacing "Followed too closely" which dropped from 3 incidents to zero.

Officer-Reported Primary Contributing Cause

No improper driving16 (45.7%)6.7%prior 15
Failed to yield right of way3 (8.6%)
Failure to keep in proper lane or running off road3 (8.6%)
Distracted3 (8.6%)
Inattention2 (5.7%)
Physical impairment2 (5.7%)
Other improper action1 (2.9%)
Over-correcting/over-steering1 (2.9%)
Fatigued/asleep1 (2.9%)
Glare1 (2.9%)

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

Crash conditions on dry and wet roads were identical year-over-year, with 29 and 5 incidents respectively. Daylight crashes were also consistent, with 21 in the current period versus 20 in the prior. A notable shift occurred in nighttime conditions, as crashes on dark, unlighted roadways increased from 3 to 7, while crashes on dark, lighted roadways fell from 11 to 6.

Weather

Clear28 (80.0%)
12.0%prior 25
Rain3 (8.6%)
Clear/Unknown1 (2.9%)
Rain/Cloudy1 (2.9%)
Rain/Unknown1 (2.9%)
Sleet, hail (freezing rain or drizzle)/Snow1 (2.9%)

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

Lighting

Daylight21 (60.0%)
5.0%prior 20
Dark - roadway not lighted7 (20.0%)
Dark - lighted roadway6 (17.1%)
-45.5%prior 11
Dusk1 (2.9%)

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

Road Surface

Dry29 (82.9%)
0.0%prior 29
Wet5 (14.3%)
0.0%prior 5
Ice1 (2.9%)

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

Vehicles & Demographics

Toyota and Honda remained the top two vehicle makes involved in crashes across both years, with Toyota's count increasing from 6 to 9 vehicles. Demographically, the 65+ age group represented the largest number of persons involved in crashes in both periods, with their count increasing from 13 to 15 individuals. The 26-34 and 55-64 age groups also saw their involvement increase from 8 to 12 persons each.

Top Vehicle Makes (51 vehicles)

1
TOYOTA9 (17.6%)
50.0%prior 6
2
HONDA7 (13.7%)
16.7%prior 6
3
FORD6 (11.8%)
4
CHEVROLET5 (9.8%)
5
JEEP3 (5.9%)
6
MAZDA3 (5.9%)
7
VOLKSWAGEN2 (3.9%)
8
GMC2 (3.9%)
-66.7%prior 6
9
HYUNDAI2 (3.9%)
10
KIA2 (3.9%)

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

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

Sex Distribution (61 persons with recorded sex)

Male34 (55.7%)
-12.8%prior 39
Female27 (44.3%)
-6.9%prior 29

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 distribution of crashes across speed zones changed significantly. Crashes in 20 mph zones dropped from 8 incidents in the prior year to 2 in the current year. In contrast, crashes in 40 mph zones increased from 3 to 5, and incidents in 25 mph zones rose from 6 to 7. There were no fatal crashes reported in any speed zone during 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: ESSEX, MA
  • Total crash records analyzed: 35
  • Total persons involved: 62
  • Total vehicles involved: 51

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). "ESSEX, 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/essex/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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Essex, MA Crash Report — 2024 | ThatCarHitMe.com