ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BILLERICA, MA · FEBRUARY 2024
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/billerica/february-2024-report
Monthly Traffic Safety Analysis
44 CRASHES IN
BILLERICA, MA
FEBRUARY 2024
Total crashes in Billerica increased by 41.9% year-over-year, rising from 31 in February 2023 to 44 in February 2024. The most notable shift was a 250% increase in total injuries, which climbed from 4 in the prior period to 14 in the current period. This surge in injuries occurred despite no fatalities being reported in either period.
44
▲ 41.9%was 31
Total Crash Events
0
Persons Killed
14
▲ 250.0%was 4
Persons Injured
2
▼ -60.0%was 5
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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for Billerica shows an upward trend in February, with total crashes increasing by 41.9% from 31 in 2023 to 44 in 2024. This rise was accompanied by a significant 250% increase in total injuries, from 4 to 14 year-over-year.
2
Hit-and-Run Crashes — February 2024
▼ -60.0% vs prior (5)
Hit-and-run crashes decreased from 5 in February 2023 to 2 in February 2024, representing a 60% reduction. Consequently, the hit-and-run rate significantly decreased from 16.1% of all crashes in the prior period to 4.5% in the current period, indicating a downward trend.
Vulnerable Road User Casualties
0
Motorists Killed
14
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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 Wednesday, with 6 crashes in the prior period, to Thursday, with 10 crashes in the current period. The peak crash hour remained 2 PM in both periods, however, the number of crashes at this hour increased from 4 in the prior period to 9 in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The total number of injuries increased substantially from 4 in February 2023 to 14 in February 2024, representing a 250% rise. The current period recorded one serious injury crash, where none were reported in the prior period, and minor injury crashes increased from 1 to 6 year-over-year. No fatal crashes or fatalities occurred in either period.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to 'Failed to yield right of way' decreased by 4 (from 9 to 5), and 'No improper driving' decreased by 4 (from 8 to 4) year-over-year. Conversely, crashes due to 'Followed too closely' increased by 4 (from 3 to 7), becoming the most frequent factor in the current period. Additionally, 'Distracted' and 'Disregarded traffic signs, signals, road markings' each contributed to 4 crashes in the current period, not being as prominent in the prior period's top factors.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
There was a notable shift in road surface conditions, with crashes on dry roads increasing from 21 (67.7% of total) in the prior period to 37 (84.1% of total) in the current period. Conversely, crashes on icy roads significantly decreased from 5 (16.1%) to 1 (2.3%) year-over-year. The proportion of crashes occurring in daylight conditions slightly decreased from 64.5% to 59.1%, while crashes in dark conditions increased from 32.3% to 36.4%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Road surface condition field
Vehicles & Demographics
Honda vehicles involved in crashes doubled from 7 in the prior period to 14 in the current period, making them the most frequently involved make. Toyota vehicles also saw a slight increase from 10 to 11, while Chevrolet involvement decreased from 8 to 5. The 26-34 age group became the most represented in the current period with 18 persons involved, an increase from 10 in the prior period, while the 16-20 age group's representation decreased from 14 to 9.
Top Vehicle Makes (80 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Vehicle unit records
3 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (90 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 35 mph speed zone increased from 10 in the prior period to 16 in the current period. Crashes in the 25 mph and 30 mph zones each saw a minor increase of 1 crash. There were no fatal crashes reported in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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: 2024-02-01 through 2024-02-29
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-02-01 through 2024-02-29 (29 days)
- Geographic scope: BILLERICA, MA
- Total crash records analyzed: 44
- Total persons involved: 94
- Total vehicles involved: 80
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: February 2024." Published June 21, 2026. Reporting period: 2024-02-01 to 2024-02-29. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/billerica/february-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-02-01 – 2024-02-29
Generated: June 21, 2026 · All rights reserved