Monthly Traffic Safety Analysis

287 CRASHES IN
FALL RIVER, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

In December 2024, Fall River experienced 287 crashes, a slight increase from 282 crashes in December 2023, representing a 1.77% rise. The most significant year-over-year shift was the increase in total fatalities from 0 in the prior period to 1 in the current period.

287

1.8%was 282

Total Crash Events

1

Persons Killed

99

12.5%was 88

Persons Injured

35

-5.4%was 37

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. 17 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for Fall River shows a slight upward trend, with total crashes increasing from 282 to 287, a 1.77% rise. This period also saw a notable increase in total fatalities from 0 to 1, and total injuries increased by 12.5% from 88 to 99.

35

Hit-and-Run Crashes — December 2024

-5.4% vs prior (37)

The number of hit-and-run crashes decreased from 37 in December 2023 to 35 in December 2024. Correspondingly, the hit-and-run rate saw a slight decrease from 13.1% to 12.2% year-over-year, indicating a downward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

9

Pedestrians Injured

Prior: 650.0%

90

Motorists Injured

Prior: 8012.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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 Friday, with 52 crashes in December 2023, to Tuesday, also with 52 crashes, in December 2024. The peak crash hour also moved from 12 PM (24 crashes) in the prior year to 5 PM (31 crashes) in the current period, indicating a shift in high-incidence times.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total fatalities increased from 0 in December 2023 to 1 in December 2024, resulting in a fatal crash rate of 0.35% for the current period. Overall injuries rose by 12.5% from 88 to 99, with minor injuries increasing by 20% from 45 to 54, while possible injuries decreased by 42.1% from 19 to 11.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
Serious Injury4serious injury crashes1.4%
0.0%prior 4
Minor Injury54minor injury crashes18.8%
20.0%prior 45
Possible Injury11possible injury crashes3.8%
-42.1%prior 19
No Injury200no injury crashes69.7%
0.0%prior 200

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'Failed to yield right of way' increased by 10%, from 30 in December 2023 to 33 in December 2024. 'Disregarded traffic signs, signals, road markings' saw a significant increase of 133.3% in count, rising from 9 to 21 crashes. Conversely, 'Inattention' related crashes decreased by 6.25%, from 32 to 30.

Officer-Reported Primary Contributing Cause

No improper driving92 (32.1%)0.0%prior 92
Failed to yield right of way33 (11.5%)10.0%prior 30
Inattention30 (10.5%)-6.3%prior 32
Disregarded traffic signs, signals, road markings21 (7.3%)133.3%prior 9
Followed too closely18 (6.3%)28.6%prior 14
Failure to keep in proper lane or running off road17 (5.9%)-19.0%prior 21
Other improper action10 (3.5%)25.0%prior 8
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner9 (3.1%)
Driving too fast for conditions7 (2.4%)-22.2%prior 9
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway7 (2.4%)0.0%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 181 to 156 year-over-year, while those on wet road surfaces increased from 49 to 61. Conversely, crashes on dry road surfaces decreased from 231 to 216. Crashes in daylight conditions also saw a slight decrease from 160 to 157.

Weather

Clear156 (54.7%)
-13.8%prior 181
Clear/Cloudy31 (10.9%)
14.8%prior 27
Clear/Clear21 (7.4%)
Rain19 (6.7%)
-9.5%prior 21
Rain/Rain11 (3.9%)
Clear/Unknown9 (3.2%)
80.0%prior 5
Rain/Cloudy7 (2.5%)
Clear/Other5 (1.8%)
-16.7%prior 6
Cloudy/Rain5 (1.8%)
-44.4%prior 9
Rain/Unknown4 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight157 (55.3%)
-1.9%prior 160
Dark - lighted roadway77 (27.1%)
-6.1%prior 82
Dark - roadway not lighted20 (7.0%)
122.2%prior 9
Dusk14 (4.9%)
0.0%prior 14
Dark - unknown roadway lighting9 (3.2%)
80.0%prior 5
Dawn6 (2.1%)
-25.0%prior 8
Other1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry216 (75.3%)
-6.5%prior 231
Wet61 (21.3%)
24.5%prior 49
Ice7 (2.4%)
Snow3 (1.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 535 to 556 year-over-year. Toyota vehicles showed a notable increase in involvement from 81 to 106, while Ford vehicles decreased from 66 to 46. The 26-34 age group continued to represent the highest number of persons involved, increasing from 98 to 110.

Top Vehicle Makes (556 vehicles)

1
TOYOTA106 (19.1%)
30.9%prior 81
2
HONDA63 (11.3%)
70.3%prior 37
3
CHEVROLET47 (8.5%)
11.9%prior 42
4
FORD46 (8.3%)
-30.3%prior 66
5
NISSAN43 (7.7%)
-25.9%prior 58
6
HYUNDAI30 (5.4%)
3.4%prior 29
7
KIA24 (4.3%)
-4.0%prior 25
8
SUBARU23 (4.1%)
155.6%prior 9
9
GMC20 (3.6%)
25.0%prior 16
10
JEEP19 (3.4%)
18.8%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Vehicle unit records

119 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (570 persons with recorded sex)

Male320 (56.1%)
14.3%prior 280
Female250 (43.9%)
7.8%prior 232

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone increased from 107 in December 2023 to 132 in December 2024, making it the zone with the most crashes in the current period. Conversely, crashes in the 30 mph zone decreased significantly from 115 to 77. Crashes in the 65 mph zone nearly doubled from 12 to 22.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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: 2024-12-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-12-01 through 2024-12-31 (31 days)
  • Geographic scope: FALL RIVER, MA
  • Total crash records analyzed: 287
  • Total persons involved: 711
  • Total vehicles involved: 556

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: December 2024." Published June 21, 2026. Reporting period: 2024-12-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fall-river/december-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

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Fall River, MA Crash Report — December 2024 | ThatCarHitMe.com