ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BOXBOROUGH, 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/boxborough/2022-annual-report
Yearly Traffic Safety Analysis
75 CRASHES IN
BOXBOROUGH, MA
2022
In 2022, Boxborough recorded 75 total crashes, the same number as in 2021. While the overall crash volume remained stable, the number of reported injuries more than doubled, increasing from 9 in 2021 to 20 in 2022, a 122.2% rise. There were no fatalities reported in either period.
75
Total Crash Events
0
Persons Killed
20
▲ 122.2%was 9
Persons Injured
4
▼ -33.3%was 6
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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The total number of crashes in Boxborough was stable year-over-year, with 75 incidents reported in both 2022 and 2021. However, the number of people injured in these crashes increased significantly, rising by 122.2% from 9 individuals in 2021 to 20 in 2022. No fatalities occurred in either year.
4
Hit-and-Run Crashes — 2022
▼ -33.3% vs prior (6)
The number of hit-and-run incidents in Boxborough decreased from 6 in 2021 to 4 in 2022. Correspondingly, the hit-and-run rate, which measures the percentage of total crashes that were hit-and-runs, fell from 8.0% in the prior year to 5.3% in the current year, indicating a downward trend for this crash type.
Vulnerable Road User Casualties
0
Motorists Killed
20
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
Temporal crash patterns shifted between the two periods. In 2022, the most frequent day for crashes was Saturday (16 incidents), a change from 2021 when Tuesday and Friday were the peak days (18 incidents each). The peak hour for crashes also moved earlier in the day, from 8 p.m. in 2021 (7 crashes) to 4 p.m. in 2022 (11 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
There were no fatal crashes recorded in either 2022 or 2021. However, the proportion of crashes resulting in an injury increased from a 12.0% share in 2021 to an 18.6% share in 2022. This change was primarily driven by a rise in 'Minor Injury' crashes, which more than doubled from 4 incidents in 2021 to 10 in 2022.
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
The top three contributing factors remained consistent across both years, though their counts and rankings shifted. Crashes attributed to 'Followed too closely' increased in count from 9 in 2021 to 11 in 2022, moving it from the third to the second most common factor. Conversely, the count of crashes involving 'Inattention' decreased from 10 to 6, and incidents with 'No improper driving' listed fell from 27 to 23.
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
In 2022, a larger share of crashes occurred in favorable conditions compared to the prior year. Crashes on dry roads increased from a 66.7% share of the total in 2021 (50 crashes) to a 77.3% share in 2022 (58 crashes). Similarly, the proportion of crashes in daylight conditions rose from 58.7% to 61.3%, while incidents in clear weather increased from a 62.7% share to 69.3%.
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
Toyota and Honda remained the top two vehicle makes involved in crashes in both periods, with the count of Toyotas increasing from 22 vehicles in 2021 to 29 in 2022. The 26-34 age group represented the largest number of people involved in crashes in both years, growing from 28 individuals in 2021 to 33 in 2022. The number of individuals in the 16-20 age group also increased, from 15 to 20.
Top Vehicle Makes (131 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
8 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (150 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 different speed zones remained largely consistent year-over-year. The 65 mph zone accounted for the highest number of crashes in both 2022 (31 crashes) and 2021 (27 crashes). The 40 mph zone was the second most common location for crashes in both periods, with 14 incidents in 2022 and 13 in 2021. No fatal crashes were recorded in any speed zone in either year.
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: BOXBOROUGH, MA
- Total crash records analyzed: 75
- Total persons involved: 160
- Total vehicles involved: 131
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). "BOXBOROUGH, 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/boxborough/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