ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · FALL RIVER, 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/fall-river/2022-annual-report
Yearly Traffic Safety Analysis
2,968 CRASHES IN
FALL RIVER, MA
2022
In 2022, Fall River recorded 2,968 total traffic crashes, a 16.1% increase from the 2,557 crashes reported in 2021. Despite the rise in total incidents, the number of fatalities decreased by 50%, from 6 in 2021 to 3 in 2022. A notable trend was the increase in crashes involving vulnerable road users, with pedestrian-involved crashes rising by 63.8% and bicycle-involved crashes increasing by 75% year-over-year.
2,968
▲ 16.1%was 2,557
Total Crash Events
3
▼ -50.0%was 6
Persons Killed
984
▲ 19.6%was 823
Persons Injured
191
▲ 30.8%was 146
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 151 crashes with unreported severity are 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
The overall trend in traffic crashes in Fall River shows a significant increase from 2021 to 2022. Total crashes rose by 16.1%, from 2,557 to 2,968. Similarly, the number of people injured in these incidents increased by 19.6%, from 823 in the prior year to 984 in the current year.
191
Hit-and-Run Crashes — 2022
▲ 30.8% vs prior (146)
Hit-and-run incidents in Fall River increased from 2021 to 2022. The total number of hit-and-run crashes rose by 30.8%, from 146 to 191. The hit-and-run rate, which measures these incidents as a percentage of all crashes, also trended upward, increasing from 5.7% in 2021 to 6.4% in 2022.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
0
Other Killed
66
Pedestrians Injured
18
Cyclists Injured
897
Motorists Injured
3
Other 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 temporal patterns of crashes in Fall River remained largely consistent year-over-year. Friday continued to be the peak day for crashes in both 2022 (469 incidents) and 2021 (445 incidents), and the 3 PM hour remained the peak time for collisions in both periods. While the overall pattern was stable, crashes during the 3 PM peak hour increased from 202 to 251. The distribution of crashes across weekdays also saw a shift, with Tuesday becoming the second-highest day for crashes in 2022 with 446 incidents.
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
While total crashes increased, the most severe outcomes decreased from 2021 to 2022. The number of fatal crashes was halved from 6 to 3, and the fatal crash rate dropped from 0.23% to 0.1%. The count of serious injury crashes remained unchanged at 40, though its share of all crashes slightly decreased. Conversely, crashes resulting in minor injuries increased in both volume, from 378 to 492, and as a proportion of all crashes, rising from 14.8% to 16.6%.
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 primary contributing factors cited in crashes remained consistent between 2021 and 2022, with the top five factors retaining their rank order. "Inattention" remained a leading cause, increasing in count from 322 to 343 incidents. Crashes attributed to "Failed to yield right of way" experienced a notable rise, with the count increasing by 30.2% from 252 in 2021 to 328 in 2022. Similarly, incidents involving "Failure to keep in proper lane or running off road" grew from 189 to 219.
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
Environmental conditions at the time of crashes were remarkably similar year-over-year, with no significant shifts in their distribution. The majority of incidents in both 2022 and 2021 occurred in ideal conditions: during daylight, in clear weather, and on dry road surfaces. For instance, crashes during daylight hours accounted for 69.3% of the total in 2022, compared to 67.5% in 2021. The proportion of crashes on dry roads (81.2% in 2022 vs. 82.0% in 2021) and in clear weather (64.4% in 2022 vs. 65.5% in 2021) also remained nearly unchanged.
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 composition of vehicles involved in crashes showed consistency between the two periods. The top five most frequent vehicle makes—Toyota, Honda, Ford, Nissan, and Chevrolet—maintained their exact ranking from 2021 to 2022, with the count for each increasing in line with the overall trend. Demographically, the 26-34 age group continued to be the largest cohort of persons involved in crashes, growing from 1,065 individuals in 2021 to 1,231 in 2022. The proportional representation across all age groups did not show any significant shifts.
Top Vehicle Makes (5,746 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
1,248 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (5,767 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
Crashes remained concentrated in lower speed zones, with the 30 mph zone accounting for the highest number of incidents in both years (1,690 in 2022 and 1,650 in 2021). However, there was a notable increase in crashes within the 25 mph zone, which rose from 219 incidents in 2021 to 548 in 2022. Fatal crashes also shifted; in 2022, two fatalities occurred in the 30 mph zone and one in a 65 mph zone. This compares to 2021, when four fatalities occurred in the 30 mph zone and two in a 55 mph zone.
Fatal crashes by zone: 30 mph: 2 of 1,690 (0.118%) · 65 mph: 1 of 174 (0.575%)
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: FALL RIVER, MA
- Total crash records analyzed: 2,968
- Total persons involved: 7,192
- Total vehicles involved: 5,746
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: 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/fall-river/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