Monthly Traffic Safety Analysis

66 CRASHES IN
BILLERICA, MA
JANUARY 2024

All metrics benchmarked againstJanuary 2023

In January 2024, Billerica experienced 66 crashes, a 24.5% increase from the 53 crashes reported in January 2023. The most significant shift was the rise in total fatalities from 0 to 1.

66

24.5%was 53

Total Crash Events

1

Persons Killed

14

-17.6%was 17

Persons Injured

7

250.0%was 2

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 2024-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Billerica showed an upward trend, increasing by 24.5% from 53 crashes in January 2023 to 66 crashes in January 2024. This period also saw an increase in total fatalities from 0 to 1, while total injuries decreased from 17 to 14.

7

Hit-and-Run Crashes — January 2024

250.0% vs prior (2)

Hit-and-run crashes saw a significant increase, rising from 2 in January 2023 to 7 in January 2024, a 250% increase in count. Consequently, the hit-and-run rate also increased from 3.8% to 10.6% of all crashes.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

14

Motorists Injured

Prior: 17-17.6%

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

The peak day for crashes shifted from Monday with 15 crashes in January 2023 to Tuesday with 20 crashes in January 2024. The peak hour also changed, moving from 2 PM with 10 crashes in the prior year to 6 PM with 7 crashes in the current 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

The severity of crashes saw a notable increase, with total fatalities rising from 0 in January 2023 to 1 in January 2024. Serious injury crashes also increased from 0 to 1, and minor injury crashes increased from 4 to 7. Conversely, possible injury crashes decreased significantly from 10 to 2.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1.5%
Serious Injury1serious injury crashes1.5%
Minor Injury7minor injury crashes10.6%
75.0%prior 4
Possible Injury2possible injury crashes3%
-80.0%prior 10
No Injury55no injury crashes83.3%
41.0%prior 39

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

Among contributing factors, 'No improper driving' saw a substantial increase in count, rising from 9 crashes in January 2023 to 19 crashes in January 2024. Crashes attributed to 'Followed too closely' increased from 6 to 7, while 'Driving too fast for conditions' remained constant at 7 crashes in both periods. 'Inattention' decreased from 6 to 4 crashes, and 'Failure to keep in proper lane or running off road' decreased from 6 to 5 crashes.

Officer-Reported Primary Contributing Cause

No improper driving19 (28.8%)111.1%prior 9
Followed too closely7 (10.6%)16.7%prior 6
Driving too fast for conditions7 (10.6%)0.0%prior 7
Failure to keep in proper lane or running off road5 (7.6%)-16.7%prior 6
Inattention4 (6.1%)-33.3%prior 6
Failed to yield right of way4 (6.1%)
Disregarded traffic signs, signals, road markings3 (4.5%)
Physical impairment2 (3%)
History heart/epilepsy/fainting2 (3%)
Other improper action2 (3%)

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 19 to 31, and those during snow increased from 6 to 15. For road surface conditions, crashes on snowy roads increased from 9 to 17, and on icy roads from 3 to 12, while wet road crashes decreased from 17 to 12. Daylight crashes rose from 27 to 33, and crashes in dark-lighted roadway conditions increased from 14 to 21, but crashes in dark-roadway not lighted conditions decreased from 8 to 3.

Weather

Clear31 (47.7%)
63.2%prior 19
Snow15 (23.1%)
150.0%prior 6
Rain6 (9.2%)
Cloudy6 (9.2%)
-25.0%prior 8
Snow/Cloudy2 (3.1%)
Sleet, hail (freezing rain or drizzle)/Snow1 (1.5%)
Snow/Snow1 (1.5%)
Clear/Clear1 (1.5%)
Rain/Rain1 (1.5%)
Sleet, hail (freezing rain or drizzle)1 (1.5%)

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

Lighting

Daylight33 (50.0%)
22.2%prior 27
Dark - lighted roadway21 (31.8%)
50.0%prior 14
Dawn5 (7.6%)
Dusk4 (6.1%)
Dark - roadway not lighted3 (4.5%)
-62.5%prior 8

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

Road Surface

Dry24 (36.4%)
4.3%prior 23
Snow17 (25.8%)
88.9%prior 9
Ice12 (18.2%)
Wet12 (18.2%)
-29.4%prior 17
Slush1 (1.5%)

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

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 100 in January 2023 to 112 in January 2024. Toyota remained the most frequently involved make, increasing from 17 to 21 vehicles, while Honda remained at 15 vehicles. Ford vehicles involved in crashes also increased from 14 to 17.

Top Vehicle Makes (112 vehicles)

1
TOYOTA21 (18.8%)
23.5%prior 17
2
FORD17 (15.2%)
21.4%prior 14
3
HONDA15 (13.4%)
0.0%prior 15
4
CHEVROLET10 (8.9%)
100.0%prior 5
5
KIA6 (5.4%)
6
MERCEDES-BENZ5 (4.5%)
7
JEEP5 (4.5%)
-37.5%prior 8
8
VOLKSWAGEN4 (3.6%)
9
MAZDA3 (2.7%)
10
LEXUS2 (1.8%)

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

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

Sex Distribution (126 persons with recorded sex)

Male75 (59.5%)
13.6%prior 66
Female50 (39.7%)
16.3%prior 43
X / Unspecified1 (0.8%)

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

Crashes in 30 mph zones increased from 18 in January 2023 to 25 in January 2024, and crashes in 35 mph zones increased from 10 to 24. Conversely, crashes in 55 mph zones decreased from 11 to 6. A fatal crash occurred in a 30 mph zone in January 2024, whereas no fatal crashes were recorded in any speed zone in January 2023.

Fatal crashes by zone: 30 mph: 1 of 25 (4%)

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: BILLERICA, MA
  • Total crash records analyzed: 66
  • Total persons involved: 138
  • Total vehicles involved: 112

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). "BILLERICA, 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/billerica/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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Billerica, MA Crash Report — January 2024 | ThatCarHitMe.com