ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHARLTON, MA · MARCH 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/charlton/march-2022-report
Monthly Traffic Safety Analysis
39 CRASHES IN
CHARLTON, MA
MARCH 2022
Total crashes in Charlton increased from 32 in March 2021 to 39 in March 2022, marking a 21.9% rise year-over-year. A notable shift was the emergence of hit-and-run crashes, increasing from 0 in the prior period to 4 in the current period. Additionally, crashes where "No improper driving" was a factor more than doubled, from 6 to 14.
39
▲ 21.9%was 32
Total Crash Events
0
Persons Killed
11
▼ -8.3%was 12
Persons Injured
4
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, Charlton experienced an increase in crashes year-over-year, with total crashes rising by 21.9% from 32 in March 2021 to 39 in March 2022. Despite this increase in crash volume, total fatalities remained at 0 in both periods. Total injuries saw a slight decrease of 8.3%, from 12 in March 2021 to 11 in March 2022.
4
Hit-and-Run Crashes — March 2022
10.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.
Vulnerable Road User Casualties
0
Motorists Killed
11
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The distribution of crashes by day of the week shifted, with the peak days moving from Friday and Monday (7 crashes each) in March 2021 to Wednesday and Thursday (10 crashes each) in March 2022. The peak crash hour also changed, with March 2022 seeing 5 crashes at 3 PM, compared to March 2021's peak of 5 crashes at both 1 PM and 4 PM.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Charlton recorded 0 fatalities in both March 2021 and March 2022. Total injuries decreased slightly by 8.3%, from 12 in the prior period to 11 in the current period. The number of serious injuries remained constant at 1 in both periods, while minor injuries decreased from 8 to 5. Notably, "Possible Injury" crashes, which were not reported in March 2021, accounted for 4 crashes in March 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Most severe injury per crash record
Top Contributing Factors
The most frequent contributing factor in March 2022 was "No improper driving" with 14 crashes, a 133.3% increase from 6 crashes in March 2021. This factor's share of crashes rose from 18.8% to 35.9%. Conversely, "Inattention" decreased significantly by 54.5%, from 11 crashes in March 2021 to 5 crashes in March 2022, with its share dropping from 34.4% to 12.8%. "Followed too closely" emerged as a top factor in March 2022 with 4 crashes, while "Exceeded authorized speed limit" and "Distracted," which each accounted for 2 crashes in March 2021, were not among the listed top factors in March 2022.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Weather conditions during crashes shifted year-over-year, with "Clear" condition crashes decreasing from 25 to 23, while "Cloudy" crashes increased from 3 to 8. A notable change was the appearance of "Snow" (3 crashes) and "Cloudy/Snow" (1 crash) conditions in March 2022, which were not reported in March 2021. Correspondingly, crashes on "Snow" (6 crashes) and "Ice" (3 crashes) road surfaces were reported in March 2022 but not in March 2021, indicating a shift towards more adverse road conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 18.9%, from 53 in March 2021 to 63 in March 2022. Ford vehicles saw the largest increase in involvement among top makes, rising from 5 in March 2021 to 9 in March 2022. Conversely, Chevrolet and Honda vehicles saw slight decreases in involvement, from 7 to 6 and 7 to 5 respectively.
Top Vehicle Makes (63 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Vehicle unit records
6 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (64 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 mph zones saw a substantial increase, rising from 2 in March 2021 to 7 in March 2022. Crashes in 65 mph zones also doubled, increasing from 4 to 8. Conversely, crashes in 50 mph zones decreased from 9 to 7. The 40 mph speed zone remained constant with 8 crashes in both periods, and no fatalities were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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: 2022-03-01 through 2022-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-03-01 through 2022-03-31 (31 days)
- Geographic scope: CHARLTON, MA
- Total crash records analyzed: 39
- Total persons involved: 73
- Total vehicles involved: 63
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). "CHARLTON, MA Crash Intelligence Report: March 2022." Published June 21, 2026. Reporting period: 2022-03-01 to 2022-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/charlton/march-2022-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: 2022-03-01 – 2022-03-31
Generated: June 21, 2026 · All rights reserved