Yearly Traffic Safety Analysis

2,997 CRASHES IN
FALL RIVER, MA
2023

All metrics benchmarked against2022

In 2023, Fall River recorded 2,997 total crashes, a slight increase of approximately 1.0% from the 2,968 crashes recorded in 2022. While overall crash volume remained relatively stable, the number of hit-and-run incidents increased significantly, rising by 79.1% from 191 in 2022 to 342 in 2023. Total injuries also rose by 16.4% year-over-year, while fatalities remained unchanged at 3.

2,997

1.0%was 2,968

Total Crash Events

3

Persons Killed

1,145

16.4%was 984

Persons Injured

342

79.1%was 191

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for Fall River indicates a relatively stable trend in total crash volume, with a marginal increase of just under 1% from 2,968 incidents in 2022 to 2,997 in 2023. However, the number of people injured in these crashes rose by 16.4% year-over-year, from 984 to 1,145. The number of fatalities remained unchanged at 3 for both periods.

342

Hit-and-Run Crashes — 2023

79.1% vs prior (191)

The number of hit-and-run crashes in Fall River increased substantially in 2023 compared to the previous year. The count of hit-and-run incidents rose by 79.1%, from 191 in 2022 to 342 in 2023. This pushed the hit-and-run rate, or the percentage of all crashes that were hit-and-runs, from 6.4% in 2022 to 11.4% in 2023, indicating a significant upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

2

Motorists Killed

Prior: 3-33.3%

1

Other Killed

Prior: 0%

56

Pedestrians Injured

Prior: 66-15.2%

17

Cyclists Injured

Prior: 18-5.6%

1,066

Motorists Injured

Prior: 89718.8%

6

Other Injured

Prior: 3100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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 showed a slight shift between 2022 and 2023. The peak day for crashes moved from Friday (469 incidents) in 2022 to Monday (472 incidents) in 2023. The peak hour for collisions remained consistent at 3 PM in both years, though the number of crashes during this hour increased by 14.3% from 251 to 287.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes in Fall River shifted slightly towards more injuries in 2023 compared to 2022. While the number of fatal crashes remained constant at 3, the proportion of crashes resulting in some form of injury increased. Crashes with minor injuries rose from a 16.6% share of all incidents in 2022 to 19.0% in 2023, and serious injury crashes increased from a 1.3% share to 1.5%. Correspondingly, the share of no-injury crashes decreased from 70.6% to 67.9%.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.1%
0.0%prior 3
Serious Injury45serious injury crashes1.5%
12.5%prior 40
Minor Injury568minor injury crashes19%
15.4%prior 492
Possible Injury198possible injury crashes6.6%
5.3%prior 188
No Injury2,034no injury crashes67.9%
-2.9%prior 2,094

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The primary contributing factors cited in crashes remained consistent between 2022 and 2023, with 'No improper driving,' 'Inattention,' and 'Failed to yield right of way' as the top three in both years. However, the counts for these factors shifted. Crashes attributed to 'Inattention' increased by 12.5% in count (from 343 to 386), while those involving 'Failed to yield right of way' decreased by 11.6% in count (from 328 to 290). The count of crashes related to 'Followed too closely' also saw an 8.0% increase, from 201 to 217 incidents.

Officer-Reported Primary Contributing Cause

No improper driving803 (26.8%)5.1%prior 764
Inattention386 (12.9%)12.5%prior 343
Failed to yield right of way290 (9.7%)-11.6%prior 328
Followed too closely217 (7.2%)8.0%prior 201
Other improper action216 (7.2%)-12.6%prior 247
Failure to keep in proper lane or running off road209 (7%)-4.6%prior 219
Disregarded traffic signs, signals, road markings97 (3.2%)-2.0%prior 99
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner75 (2.5%)-16.7%prior 90
Over-correcting/over-steering56 (1.9%)21.7%prior 46
Driving too fast for conditions52 (1.7%)-10.3%prior 58

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Environmental conditions for crashes in Fall River were largely similar year-over-year, with most incidents occurring in daylight on dry roads. In both 2022 and 2023, approximately 69% of crashes happened during daylight hours. A notable change was observed in crashes related to winter conditions; the number of incidents on snowy or icy road surfaces decreased from 117 in 2022 to just 21 in 2023. Correspondingly, crashes in snowy weather conditions also saw a decrease.

Weather

Clear1,863 (62.8%)
-2.6%prior 1,912
Clear/Cloudy425 (14.3%)
2.7%prior 414
Rain203 (6.8%)
10.9%prior 183
Cloudy138 (4.7%)
-3.5%prior 143
Cloudy/Rain75 (2.5%)
36.4%prior 55
Clear/Unknown71 (2.4%)
91.9%prior 37
Clear/Other55 (1.9%)
27.9%prior 43
Rain/Cloudy30 (1.0%)
36.4%prior 22
Cloudy/Clear18 (0.6%)
63.6%prior 11
Snow16 (0.5%)
-50.0%prior 32

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight2,083 (70.1%)
1.2%prior 2,058
Dark - lighted roadway615 (20.7%)
-2.7%prior 632
Dusk96 (3.2%)
37.1%prior 70
Dark - roadway not lighted79 (2.7%)
-33.6%prior 119
Dawn57 (1.9%)
21.3%prior 47
Dark - unknown roadway lighting40 (1.3%)
122.2%prior 18
Other2 (0.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry2,499 (84.0%)
3.6%prior 2,411
Wet449 (15.1%)
13.4%prior 396
Ice11 (0.4%)
-73.8%prior 42
Snow10 (0.3%)
-86.7%prior 75
Water (standing, moving)6 (0.2%)
-14.3%prior 7
Other1 (0.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained unchanged in rank and saw very similar involvement counts between 2022 and 2023. Analysis of the age of persons involved in crashes reveals a notable shift. The number of individuals in the 16-20 age group increased by 22.8%, from 501 in 2022 to 615 in 2023. Conversely, the 26-34 age group, which was the largest in both years, saw a 3.3% decrease in involvement from 1,231 to 1,190 persons.

Top Vehicle Makes (5,840 vehicles)

1
TOYOTA882 (15.1%)
1.1%prior 872
2
HONDA688 (11.8%)
10.3%prior 624
3
FORD605 (10.4%)
0.2%prior 604
4
CHEVROLET453 (7.8%)
6.1%prior 427
5
NISSAN447 (7.7%)
-5.7%prior 474
6
HYUNDAI331 (5.7%)
-5.7%prior 351
7
KIA252 (4.3%)
21.7%prior 207
8
JEEP229 (3.9%)
-2.6%prior 235
9
GMC158 (2.7%)
24.4%prior 127
10
DODGE149 (2.6%)
-15.8%prior 177

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

1,238 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (5,810 persons with recorded sex)

Male3,089 (53.2%)
0.1%prior 3,085
Female2,720 (46.8%)
1.5%prior 2,681
X / Unspecified1 (0.0%)
0.0%prior 1

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

There was a significant redistribution of crashes across different speed zones between the two years. Crashes in 25 mph zones increased by 74.8%, from 548 incidents in 2022 to 958 in 2023. Concurrently, crashes in 30 mph zones decreased by 22.1%, from 1,690 to 1,316. The location of fatal crashes also shifted; in 2022, two of the three fatalities occurred in 30 mph zones, whereas in 2023, all three fatalities occurred in zones with speed limits of 55 mph or higher.

Fatal crashes by zone: 55 mph: 1 of 105 (0.952%) · 65 mph: 2 of 180 (1.111%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: FALL RIVER, MA
  • Total crash records analyzed: 2,997
  • Total persons involved: 7,352
  • Total vehicles involved: 5,840

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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fall-river/2023-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

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Fall River, MA Crash Report — 2023 | ThatCarHitMe.com