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YEAR-OVER-YEAR CRASH REPORT · FALL RIVER, MA · JANUARY 2024
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/january-2024-report
Monthly Traffic Safety Analysis
269 CRASHES IN
FALL RIVER, MA
JANUARY 2024
Total crashes in Fall River, MA increased from 229 in January 2023 to 269 in January 2024, representing a 17.47% rise year-over-year. The most significant shift observed was a 111.76% increase in hit-and-run crashes, rising from 17 to 36 incidents.
269
▲ 17.5%was 229
Total Crash Events
0
Persons Killed
82
▲ 20.6%was 68
Persons Injured
36
▲ 111.8%was 17
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. 12 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in Fall River, MA showed an upward trend year-over-year, increasing by 17.47% from 229 crashes in January 2023 to 269 crashes in January 2024. This indicates a notable rise in crash frequency for the specified period.
36
Hit-and-Run Crashes — January 2024
▲ 111.8% vs prior (17)
Hit-and-run crashes increased significantly year-over-year, rising by 19 incidents from 17 in January 2023 to 36 in January 2024. This represents a 111.76% increase in the number of hit-and-run incidents. Consequently, the hit-and-run rate also rose from 7.4% to 13.4% of all crashes.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
5
Pedestrians Injured
2
Cyclists Injured
75
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · 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 Thursday in January 2023 (42 crashes) to Wednesday in January 2024 (45 crashes). Similarly, the peak crash hour moved from 3 PM (21 crashes) in the prior period to 6 PM (22 crashes) in the current period, indicating a shift in the busiest time for incidents.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both January 2023 and January 2024. The number of serious injury crashes remained constant at 1 in both periods, representing 0.4% of total crashes in January 2024 and 0.4% in January 2023. Minor injury crashes saw a slight increase in proportion, rising from 16.6% to 16.7% of total crashes, while possible injury crashes increased from 5.2% to 6.3%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to "No improper driving" increased by 41 incidents (75.9%) from 54 to 95 year-over-year, and "Driving too fast for conditions" saw a significant count increase of 12 incidents (1200%), rising from 1 to 13. Conversely, "Followed too closely" decreased by 16 incidents (-57.1%) from 28 to 12, and "Failed to yield right of way" decreased by 10 incidents (-34.5%) from 29 to 19.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The number of crashes occurring in "Clear" weather conditions increased from 99 to 162, while those in "Rain" decreased from 29 to 18. Crashes on "Dry" road surfaces rose from 144 to 182, but crashes on "Wet" surfaces decreased from 80 to 54. The proportion of crashes occurring during "Daylight" increased from 52.4% (120 of 229) to 60.2% (162 of 269) of total crashes.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Road surface condition field
Vehicles & Demographics
The age group with the highest number of persons involved in crashes remained 26-34, increasing from 97 persons in January 2023 to 106 persons in January 2024. Toyota remained the most frequently involved vehicle make, though its count decreased from 75 to 68, while Ford moved up to the third position from fourth, with its count increasing from 41 to 57.
Top Vehicle Makes (504 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Vehicle unit records
102 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (470 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 25 mph speed zone slightly increased from 75 to 77, and those in the 30 mph zone rose from 112 to 114. Notably, crashes in the 65 mph zone saw a substantial increase, more than doubling from 14 incidents in January 2023 to 25 incidents in January 2024. No fatal crashes were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · 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: 2024-01-01 through 2024-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-01-31 (31 days)
- Geographic scope: FALL RIVER, MA
- Total crash records analyzed: 269
- Total persons involved: 600
- Total vehicles involved: 504
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: January 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fall-river/january-2024-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: 2024-01-01 – 2024-01-31
Generated: June 21, 2026 · All rights reserved