Monthly Traffic Safety Analysis

3 CRASHES IN
ESSEX, MA
NOVEMBER 2023

All metrics benchmarked againstNovember 2022

Total crashes in ESSEX decreased by 62.5% from 8 crashes in November 2022 to 3 crashes in November 2023. Despite this overall decrease in crash events, the number of reported injuries increased from 0 to 2 during the same period.

3

-62.5%was 8

Total Crash Events

0

Persons Killed

2

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 · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the number of crashes in ESSEX significantly decreased year-over-year, falling by 62.5% from 8 crashes in November 2022 to 3 crashes in November 2023. Concurrently, total injuries increased from 0 to 2, indicating a shift in crash severity despite fewer incidents.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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 for both periods, though the count on Fridays decreased from 3 crashes in November 2022 to 1 crash in November 2023. The peak hour for crashes was 10p in both periods, with 1 crash reported at that hour each year. The distribution of crashes across other days and hours shifted, with crashes occurring on Monday, Tuesday, Wednesday, and Thursday in November 2022 not being present in November 2023, while Sunday and Thursday crashes appeared in November 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Outcome by Severity (Crash Events)

Possible Injury1possible injury crashes33.3%
No Injury2no injury crashes66.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "No improper driving" decreased from 7 in November 2022 to 2 in November 2023, representing a 71.4% decrease in count. "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" was cited in 1 crash in November 2023, while it was not a factor in November 2022. Conversely, "Failure to keep in proper lane or running off road" was a factor in 1 crash in November 2022 but not in November 2023.

Officer-Reported Primary Contributing Cause

No improper driving2 (66.7%)-71.4%prior 7
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (33.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Weather and road surface conditions data were not available for comparison. In terms of lighting, crashes occurring in "Daylight" decreased from 3 in November 2022 to 1 in November 2023, and "Dark - lighted roadway" crashes decreased from 2 to 1. "Dusk" conditions accounted for 2 crashes in November 2022 but none in November 2023, while "Dark - roadway not lighted" crashes remained at 1 for both periods.

Lighting

Dark - lighted roadway1 (33.3%)
Dark - roadway not lighted1 (33.3%)
Daylight1 (33.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field

Vehicles & Demographics

Top Vehicle Makes (3 vehicles)

1
FORD1 (33.3%)
2
HONDA1 (33.3%)
3
NISSAN1 (33.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Vehicle unit records

Sex Distribution (4 persons with recorded sex)

Male3 (75.0%)
-40.0%prior 5
Female1 (25.0%)
-75.0%prior 4

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Person-level records linked to crash events

Speed Limit Zones

The number of crashes occurring in the 50 mph speed limit zone decreased from 3 in November 2022 to 2 in November 2023. A crash in the 30 mph zone was reported in November 2023, which was not present in the prior year. Crashes in the 25 mph, 35 mph, 40 mph, and 45 mph zones, which accounted for a total of 5 crashes in November 2022, did not occur in November 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-11-01 through 2023-11-30 (30 days)
  • Geographic scope: ESSEX, MA
  • Total crash records analyzed: 3
  • Total persons involved: 4
  • Total vehicles involved: 3

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: November 2023." Published June 21, 2026. Reporting period: 2023-11-01 to 2023-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/essex/november-2023-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 — November 2023 | ThatCarHitMe.com