ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · FALL RIVER, MA · FEBRUARY 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/fall-river/february-2022-report
Monthly Traffic Safety Analysis
251 CRASHES IN
FALL RIVER, MA
FEBRUARY 2022
FALL RIVER experienced a notable increase in crash activity in February 2022 compared to February 2021, with total crashes rising from 207 to 251, representing a 21.26% increase. Despite this, total injuries saw a slight decrease from 59 to 53, a reduction of 10.17%. The most significant year-over-year shift was a 600% increase in DUI-related crashes, which rose from 1 to 7.
251
▲ 21.3%was 207
Total Crash Events
0
Persons Killed
53
▼ -10.2%was 59
Persons Injured
20
▲ 33.3%was 15
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. 17 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in FALL RIVER showed an upward trend, with total crashes increasing by 21.26% from 207 in February 2021 to 251 in February 2022. Conversely, the number of total injuries decreased by 10.17%, from 59 to 53. Fatalities remained stable at zero for both periods.
20
Hit-and-Run Crashes — February 2022
▲ 33.3% vs prior (15)
Hit-and-run crashes increased by 5, from 15 in February 2021 to 20 in February 2022, marking a 33.33% rise. The hit-and-run rate also increased from 7.2% to 8% of all crashes. This indicates an upward trend in hit-and-run incidents year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
0
Other Killed
4
Pedestrians Injured
47
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · 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 (35 crashes) in February 2021 to Monday (45 crashes) in February 2022. The peak hour also changed, moving from 5 PM (19 crashes) in the prior period to 3 PM (30 crashes) in the current period. Crashes on weekdays generally increased, with Monday seeing an 18-crash rise and Wednesday experiencing a 5-crash decrease.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both periods, indicating no change in the fatal crash rate. While overall injuries decreased, the proportion of crashes resulting in serious injuries (code A) fell from 1.4% (3 crashes) to 0.4% (1 crash). Conversely, crashes with possible injuries (code C) increased from 4.3% (9 crashes) to 6% (15 crashes), and crashes with no injury (code O) rose from 71.5% (148 crashes) to 75.3% (189 crashes).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to 'No improper driving' saw a significant count increase of 35, rising from 44 to 79 crashes, while its share increased from 21.3% to 31.5%. 'Inattention' related crashes decreased by 8 in count, from 27 to 19, causing its ranking to drop from second to fourth. 'Failed to yield right of way' crashes increased by 9 in count, from 13 to 22, and 'Driving too fast for conditions' increased by 5 in count, from 10 to 15.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased by 34, from 102 to 136, while those in 'Snow' conditions decreased by 25, from 40 to 15. The number of crashes on 'Dry' road surfaces rose by 29, from 106 to 135, and crashes on 'Wet' surfaces increased by 17, from 38 to 55. Crashes during 'Daylight' hours increased by 54, from 113 to 167, while those in 'Dark - lighted roadway' conditions decreased by 11, from 69 to 58.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 380 to 492 year-over-year. The 26-34 age group saw the largest increase in persons involved, rising by 28 from 65 to 93. TOYOTA remained the most frequently involved vehicle make, with its count increasing by 29 from 56 to 85, while FORD moved from third to second, with its count rising by 15 from 35 to 50.
Top Vehicle Makes (492 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Vehicle unit records
132 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (465 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Person-level records linked to crash events
Speed Limit Zones
The 30 mph speed zone continued to account for the highest number of crashes, increasing by 50 from 122 to 172 crashes. Crashes in the 25 mph zone decreased by 5, from 18 to 13, while those in the 35 mph zone increased by 9, from 8 to 17. There were no fatal crashes recorded in any speed zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · 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: 2022-02-01 through 2022-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-02-01 through 2022-02-28 (28 days)
- Geographic scope: FALL RIVER, MA
- Total crash records analyzed: 251
- Total persons involved: 595
- Total vehicles involved: 492
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). "FALL RIVER, MA Crash Intelligence Report: February 2022." Published June 21, 2026. Reporting period: 2022-02-01 to 2022-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fall-river/february-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: 2022-02-01 – 2022-02-28
Generated: June 21, 2026 · All rights reserved