ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BOYLSTON, 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/boylston/2022-annual-report
Yearly Traffic Safety Analysis
66 CRASHES IN
BOYLSTON, MA
2022
In Boylston, total vehicle crashes increased by 17.9% from 56 in 2021 to 66 in 2022. While total injuries remained nearly stable, decreasing from 16 to 15, the most notable year-over-year change was the emergence of fatal crashes. The area recorded two fatal crashes resulting in two deaths in 2022, compared to zero in the prior year.
66
▲ 17.9%was 56
Total Crash Events
2
Persons Killed
15
▼ -6.3%was 16
Persons Injured
1
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. 1 crash with unreported severity is 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
Crash trends in Boylston show an overall increase in collision frequency year-over-year. The total number of crashes rose from 56 in 2021 to 66 in 2022, an increase of 10 incidents. This rise in total crashes was accompanied by a significant increase in crash severity, with fatalities rising from zero to two, even as the total number of non-fatal injuries slightly declined from 16 to 15.
1
Hit-and-Run Crashes — 2022
▼ 0.0% vs prior (1)
The number of hit-and-run crashes remained stable, with one incident reported in both 2021 and 2022. Due to the overall increase in total crashes in 2022, the hit-and-run rate saw a slight decrease from 1.8% to 1.5% of all crashes. This indicates a stable trend in the absolute count of these incidents year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
2
Motorists Killed
1
Pedestrians Injured
14
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 13 incidents, a shift from Wednesday (11 crashes) in 2021. The daily peak hour also moved later into the evening commute, from 3 p.m. (9 crashes) in the prior year to 5 p.m. (8 crashes) in the current year. Notably, crashes on Wednesdays fell from 11 to 2, while Friday crashes more than doubled from 5 to 13.
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
Crash severity significantly worsened year-over-year. In 2022, two fatal crashes occurred, accounting for 3% of all incidents, whereas there were no fatal crashes in 2021. Consequently, the number of fatalities rose from zero to two. While the total number of people injured was nearly unchanged (15 in 2022 vs. 16 in 2021), 2022 saw one serious injury, a category not present in the prior year's data. The proportion of crashes with no injuries increased from 71.4% to 78.8%.
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 leading contributing factors showed some shifts in volume between 2021 and 2022. The count of crashes attributed to 'Inattention' doubled from 5 to 10. The number of crashes where 'No improper driving' was cited increased from 8 to 25, a 212.5% increase in count. Conversely, crashes involving an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased from 4 incidents to 3. 'Failed to yield right of way' also saw an increase, rising from 3 crashes in 2021 to 5 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
Crashes occurred more frequently in adverse conditions in 2022 compared to 2021. The number of crashes on wet road surfaces more than doubled from 4 to 9, and crashes on snow-covered roads increased from 3 to 7. While 'Daylight' remained the most common lighting condition, its share of crashes fell from 71.4% (40 crashes) in 2021 to 60.6% (40 crashes) in 2022, as the total number of crashes increased. Similarly, the share of crashes in clear weather decreased from 71.4% to 65.2%.
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 makes of vehicles involved in crashes showed a notable shift. In 2021, Toyota was the most frequent make with 19 vehicles, but this number fell to 11 in 2022. Chevrolet became the most common make in 2022 with 12 vehicles, up from 7 in the prior year. Regarding driver and passenger demographics, the 45-54 age group saw increased involvement, growing from 14 persons in 2021 to 22 in 2022, making it the largest group in the current period.
Top Vehicle Makes (103 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
2 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (122 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 changed between periods. Crashes in 35 mph zones increased from 10 in 2021 to 15 in 2022. In contrast, collisions in 65 mph zones decreased from 7 to 4. The two fatal crashes recorded in 2022 occurred in a 35 mph zone and a 65 mph zone, whereas no fatal crashes were recorded in any speed zone in 2021.
Fatal crashes by zone: 35 mph: 1 of 15 (6.667%) · 65 mph: 1 of 4 (25%)
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: BOYLSTON, MA
- Total crash records analyzed: 66
- Total persons involved: 125
- Total vehicles involved: 103
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). "BOYLSTON, 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/boylston/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