ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BILLERICA, MA · 2022
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/2022-annual-report
Yearly Traffic Safety Analysis
544 CRASHES IN
BILLERICA, MA
2022
In 2022, Billerica recorded 544 total vehicle crashes, a 22.3% increase from the 445 crashes reported in 2021. This year-over-year analysis shows a rise in most key metrics, including a 26.5% increase in persons injured and a doubling of fatalities from one to two. The most notable shift was a 100% increase in hit-and-run incidents, which rose from 12 in 2021 to 24 in 2022.
544
▲ 22.2%was 445
Total Crash Events
2
▲ 100.0%was 1
Persons Killed
191
▲ 26.5%was 151
Persons Injured
24
▲ 100.0%was 12
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 6 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety metrics in Billerica show a worsening trend from 2021 to 2022. The total number of crashes increased by 22.3%, rising from 445 to 544. In parallel, the number of individuals injured in these incidents grew by 26.5% to 191, and total fatalities increased from one to two.
24
Hit-and-Run Crashes — 2022
▲ 100.0% vs prior (12)
Hit-and-run incidents showed a significant upward trend. The absolute number of hit-and-run crashes doubled, increasing from 12 in 2021 to 24 in 2022. As a result, the hit-and-run rate, which measures the proportion of all crashes that are hit-and-runs, increased from 2.7% to 4.4%.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
1
Pedestrians Injured
3
Cyclists Injured
187
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. In 2022, the peak day for crashes was Friday with 94 incidents, a change from Tuesday (77 incidents) in 2021. The peak hour for collisions also moved earlier in the day, from the 4 p.m. hour in 2021 (45 crashes) to the 2 p.m. hour in 2022 (50 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes increased from 2021 to 2022, with the fatal crash rate rising from 0.22% to 0.37%. While the overall share of crashes involving any type of injury remained stable at around 27%, the composition of those injuries changed. The proportion of crashes resulting in 'Possible Injury' increased from 10.6% to 14.2% of all incidents, while the shares of 'Serious Injury' and 'Minor Injury' crashes decreased slightly.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
While 'Failed to yield right of way' remained the top contributing factor in both years with a nearly unchanged count (78 in 2021 vs. 77 in 2022), other driver behaviors saw notable increases. Crashes attributed to 'Followed too closely' grew by 32.6% from 46 to 61 incidents. The count for 'Inattention' as a factor rose by 63.3% from 30 to 49 crashes, making it the third most-cited factor in 2022.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
While most crashes in both years occurred in daylight on dry roads, there was a significant increase in incidents on adverse road surfaces. The number of crashes on icy roads doubled, rising from 13 in 2021 to 26 in 2022. Collisions on wet roads also increased from 70 to 83, and those on snowy roads grew from 11 to 18.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained consistent, with Toyota vehicle involvements increasing from 126 to 197. Analysis of persons involved reveals significant growth in specific age groups, with the number of individuals aged 65 and older increasing by 69.0% (from 87 to 147) and those in the 0-15 age group increasing by 88.2% (from 51 to 96).
Top Vehicle Makes (1,016 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
54 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,201 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones shifted year-over-year. Incidents in 55 mph zones increased from 62 to 78, while crashes in 30 mph zones decreased from 193 to 171. The single fatality in 2021 occurred in a 35 mph zone, whereas the two fatalities in 2022 were recorded in 30 mph and 55 mph zones.
Fatal crashes by zone: 30 mph: 1 of 171 (0.585%) · 55 mph: 1 of 78 (1.282%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: BILLERICA, MA
- Total crash records analyzed: 544
- Total persons involved: 1,286
- Total vehicles involved: 1,016
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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/billerica/2022-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved