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YEAR-OVER-YEAR CRASH REPORT · FALL RIVER, MA · MARCH 2023
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/march-2023-report
Monthly Traffic Safety Analysis
211 CRASHES IN
FALL RIVER, MA
MARCH 2023
Total crashes in FALL RIVER, MA, saw a slight decrease of 2.31% year-over-year, from 216 in March 2022 to 211 in March 2023. Despite this reduction in overall crash volume, the number of hit-and-run incidents more than doubled during this period, marking the most notable shift. Fatalities remained stable at one in both periods.
211
▼ -2.3%was 216
Total Crash Events
1
Persons Killed
82
▲ 36.7%was 60
Persons Injured
32
▲ 166.7%was 12
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 15 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash incidents in FALL RIVER, MA, experienced a minor decline of 2.31%, decreasing from 216 crashes in March 2022 to 211 crashes in March 2023. However, total injuries increased by 36.67%, rising from 60 to 82 persons. Fatalities remained consistent with one recorded death in both reporting periods.
32
Hit-and-Run Crashes — March 2023
▲ 166.7% vs prior (12)
Hit-and-run crashes increased significantly year-over-year, more than doubling from 12 in March 2022 to 32 in March 2023. This change also resulted in a substantial rise in the hit-and-run rate, from 5.6% of all crashes in the prior period to 15.2% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Motorists Killed
0
Other Killed
6
Pedestrians Injured
75
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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, with 40 incidents in March 2022, to Monday, with 36 incidents in March 2023. Similarly, the peak hour for crashes changed from 2 p.m. (22 crashes) in the prior period to 4 p.m. (27 crashes) in the current period. Crashes on Monday increased from 21 to 36, while crashes on Thursday decreased from 40 to 32.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Total fatalities remained stable at one in both March 2022 and March 2023. However, total injuries increased by 36.67%, from 60 to 82. Serious injury crashes (severity A) doubled from 2 (0.9% share) to 4 (1.9% share), and minor injury crashes (severity B) increased from 23 (10.6% share) to 42 (19.9% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor, "No improper driving," decreased by 5 crashes, from 61 to 56. "Other improper action" saw a significant decrease of 14 crashes, falling from 30 to 16. Conversely, "Inattention" increased by 2 crashes, from 21 to 23, and "Followed too closely" increased by 4 crashes, from 13 to 17.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in "Clear" weather conditions decreased by 16, from 133 to 117. Similarly, crashes during "Daylight" conditions decreased by 13, from 162 to 149. In contrast, crashes on "Wet" road surfaces increased by 5, from 33 to 38, and crashes during "Dawn" increased by 4, from 2 to 6.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 427 to 414 year-over-year. The 65+ age group saw an increase of 10 persons involved, rising from 41 to 51, while the 55-64 age group experienced a decrease of 13 persons involved, from 50 to 37. Toyota vehicles involved in crashes increased by 11, from 54 to 65, while Hyundai vehicles decreased by 13, from 28 to 15.
Top Vehicle Makes (414 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records
102 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (405 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 25 MPH speed zones increased by 33, from 34 to 67. Conversely, crashes in 30 MPH speed zones decreased by 28, from 122 to 94. The single fatal crash in March 2023 occurred in a 65 MPH speed zone, differing from the single fatal crash in March 2022 which occurred in a 30 MPH speed zone.
Fatal crashes by zone: 65 mph: 1 of 6 (16.667%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-03-01 through 2023-03-31 (31 days)
- Geographic scope: FALL RIVER, MA
- Total crash records analyzed: 211
- Total persons involved: 521
- Total vehicles involved: 414
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: March 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fall-river/march-2023-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: 2023-03-01 – 2023-03-31
Generated: June 21, 2026 · All rights reserved