Monthly Traffic Safety Analysis

27 CRASHES IN
PEMBROKE, MA
JANUARY 2024

All metrics benchmarked againstJanuary 2023

In January 2024, PEMBROKE recorded 27 total crashes, a slight decrease from the 28 crashes reported in January 2023, representing a 3.6% reduction. Despite the decrease in total crashes, the number of total injuries rose significantly by 60%, from 5 injuries in the prior period to 8 injuries in the current period. Additionally, hit-and-run crashes doubled from 1 to 2 year-over-year.

27

-3.6%was 28

Total Crash Events

0

Persons Killed

8

60.0%was 5

Persons Injured

2

100.0%was 1

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. 3 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 2024-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a stable number of total crashes, with a minor decrease of 1 crash year-over-year from 28 to 27. However, total injuries increased by 60%, from 5 in January 2023 to 8 in January 2024, suggesting an increase in the severity of crash outcomes. Fatalities remained at 0 in both periods.

2

Hit-and-Run Crashes — January 2024

100.0% vs prior (1)

Hit-and-run crashes increased from 1 in January 2023 to 2 in January 2024, representing a 100% increase in count. The hit-and-run rate also trended upward, rising from 3.6% of total crashes in the prior period to 7.4% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

8

Motorists Injured

Prior: 560.0%

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

When Crashes Happen

Mondays continued to be the peak day for crashes in both periods, though the count decreased slightly from 11 crashes in January 2023 to 10 crashes in January 2024. The peak hour for crashes remained 5 PM in both periods, with a minor reduction from 5 crashes in the prior period to 4 crashes in the current period. Overall, temporal patterns for peak crash times remained consistent year-over-year.

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

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

Crash Severity Breakdown

Fatal crashes remained at 0 in both January 2023 and January 2024. While serious injuries (Severity A) decreased from 1 to 0, minor injuries (Severity B) saw a substantial increase from 1 crash to 6 crashes, and possible injuries (Severity C) remained stable at 2 crashes. The proportion of crashes resulting in any injury (Severity B or C) increased from 10.7% (3 crashes) in January 2023 to 29.6% (8 crashes) in January 2024.

Outcome by Severity (Crash Events)

Minor Injury6minor injury crashes22.2%
500.0%prior 1
Possible Injury2possible injury crashes7.4%
0.0%prior 2
No Injury16no injury crashes59.3%
-27.3%prior 22

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

Crashes attributed to 'Inattention' increased by 100% in count, rising from 3 in January 2023 to 6 in January 2024. Similarly, 'Followed too closely' crashes also increased by 100% in count, from 2 to 4. Conversely, crashes due to 'Failed to yield right of way' decreased by 66.7% in count, from 3 to 1, and 'Failure to keep in proper lane or running off road' crashes decreased by 50% in count, from 2 to 1.

Officer-Reported Primary Contributing Cause

No improper driving9 (33.3%)0.0%prior 9
Inattention6 (22.2%)
Followed too closely4 (14.8%)
Failure to keep in proper lane or running off road1 (3.7%)
Failed to yield right of way1 (3.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.7%)
Driving too fast for conditions1 (3.7%)

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

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 11 in January 2023 to 15 in January 2024. Crashes on 'Dry' road surfaces also increased from 13 to 16, while crashes on 'Wet' road surfaces decreased from 10 to 8, and 'Snow' road crashes decreased from 5 to 3. Crashes occurring in 'Dark - roadway not lighted' conditions decreased from 6 to 2, indicating a shift towards crashes occurring in daylight or lighted conditions.

Weather

Clear15 (55.6%)
36.4%prior 11
Cloudy5 (18.5%)
Snow4 (14.8%)
Rain/Snow1 (3.7%)
Sleet, hail (freezing rain or drizzle)1 (3.7%)
Snow/Cloudy1 (3.7%)

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

Lighting

Daylight16 (59.3%)
23.1%prior 13
Dark - lighted roadway6 (22.2%)
0.0%prior 6
Dark - roadway not lighted2 (7.4%)
-66.7%prior 6
Dusk2 (7.4%)
Dark - unknown roadway lighting1 (3.7%)

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

Road Surface

Dry16 (59.3%)
23.1%prior 13
Wet8 (29.6%)
-20.0%prior 10
Snow3 (11.1%)
-40.0%prior 5

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

Vehicles & Demographics

Top Vehicle Makes (48 vehicles)

1
FORD6 (12.5%)
0.0%prior 6
2
JEEP6 (12.5%)
3
TOYOTA6 (12.5%)
-25.0%prior 8
4
CHEVROLET4 (8.3%)
-42.9%prior 7
5
HONDA3 (6.3%)
-40.0%prior 5
6
MAZDA3 (6.3%)
7
NISSAN2 (4.2%)
8
GMC2 (4.2%)
9
HYUNDAI2 (4.2%)
10
SUBARU2 (4.2%)

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

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

Sex Distribution (50 persons with recorded sex)

Male27 (54.0%)
-22.9%prior 35
Female23 (46.0%)
-4.2%prior 24

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

Speed Limit Zones

There was a notable shift in crashes across different speed zones. Crashes in the 40 mph zone decreased from 7 to 4, and in the 35 mph zone from 11 to 10. Conversely, crashes in the 45 mph zone increased from 2 to 5, and 3 crashes occurred in the 10 mph zone in January 2024 where none were reported in the prior period. No fatal crashes were reported in any speed zone for either period.

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

Data Coverage

  • Reporting period: 2024-01-01 through 2024-01-31 (31 days)
  • Geographic scope: PEMBROKE, MA
  • Total crash records analyzed: 27
  • Total persons involved: 55
  • Total vehicles involved: 48

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