Monthly Traffic Safety Analysis

198 CRASHES IN
TAUNTON, MA
OCTOBER 2023

All metrics benchmarked againstOctober 2022

October 2023 saw 198 crashes in TAUNTON, MA, representing an 8.3% decrease from the 216 crashes recorded in October 2022. Despite this reduction in total incidents, the number of persons injured increased by 20.5%, rising from 44 to 53 year-over-year.

198

-8.3%was 216

Total Crash Events

0

Persons Killed

53

20.5%was 44

Persons Injured

25

13.6%was 22

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes decreased by 8.3% in October 2023 compared to the same month in the prior year, falling from 216 to 198 crashes. This indicates a downward trend in crash frequency for the period.

25

Hit-and-Run Crashes — October 2023

13.6% vs prior (22)

Hit-and-run crashes increased from 22 in October 2022 to 25 in October 2023. This resulted in an increase in the hit-and-run rate from 10.2% to 12.6% year-over-year, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 10.0%

52

Motorists Injured

Prior: 4320.9%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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 October 2022, which had 34 crashes, to Tuesday in October 2023, which recorded 48 crashes. The peak crash hour also moved from 4 PM with 21 crashes in the prior period to 6 PM with 19 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total fatalities remained at 0 in both October 2022 and October 2023. However, total injuries increased by 20.5%, from 44 in the prior period to 53 in the current period. Serious injuries (Severity A) doubled from 1 to 2, and minor injuries (Severity B) increased from 24 to 29.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes1%
100.0%prior 1
Minor Injury29minor injury crashes14.6%
20.8%prior 24
Possible Injury9possible injury crashes4.5%
0.0%prior 9
No Injury144no injury crashes72.7%
-13.8%prior 167

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "Inattention" increased by 5, from 28 in October 2022 to 33 in October 2023. Conversely, "Failed to yield right of way" crashes decreased by 4, from 35 to 31. "No improper driving" remained the most frequent contributing factor, decreasing from 44 to 40 crashes.

Officer-Reported Primary Contributing Cause

No improper driving40 (20.2%)-9.1%prior 44
Inattention33 (16.7%)17.9%prior 28
Failed to yield right of way31 (15.7%)-11.4%prior 35
Followed too closely15 (7.6%)-11.8%prior 17
Failure to keep in proper lane or running off road11 (5.6%)0.0%prior 11
Disregarded traffic signs, signals, road markings7 (3.5%)40.0%prior 5
Distracted5 (2.5%)-16.7%prior 6
Other improper action5 (2.5%)-37.5%prior 8
Visibility obstructed5 (2.5%)
Made an improper turn4 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in "Clear" or "Clear/Clear" weather conditions collectively decreased from 165 in October 2022 to 155 in October 2023. Crashes on "Dry" road surfaces decreased from 176 to 168, while those on "Wet" surfaces also decreased from 38 to 28. Crashes during "Daylight" hours decreased from 142 to 117.

Weather

Clear/Clear79 (40.9%)
12.9%prior 70
Clear76 (39.4%)
-20.0%prior 95
Rain12 (6.2%)
-25.0%prior 16
Cloudy9 (4.7%)
28.6%prior 7
Rain/Rain5 (2.6%)
-58.3%prior 12
Cloudy/Rain4 (2.1%)
Cloudy/Cloudy3 (1.6%)
Clear/Cloudy3 (1.6%)
Clear/Other1 (0.5%)
Clear/Fog, smog, smoke1 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash

Lighting

Daylight117 (59.7%)
-17.6%prior 142
Dark - lighted roadway48 (24.5%)
-7.7%prior 52
Dark - roadway not lighted12 (6.1%)
71.4%prior 7
Dawn11 (5.6%)
120.0%prior 5
Dusk8 (4.1%)
33.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field

Road Surface

Dry168 (85.7%)
-4.5%prior 176
Wet28 (14.3%)
-26.3%prior 38

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 386 in October 2022 to 357 in October 2023. Toyota remained the most frequently involved make, though its count decreased from 66 to 51, while Honda and Ford saw increases in involvement. The number of persons involved aged 16-20 decreased from 52 to 37, while the 21-25 age group saw a slight increase from 47 to 49.

Top Vehicle Makes (357 vehicles)

1
TOYOTA51 (14.3%)
-22.7%prior 66
2
HONDA42 (11.8%)
10.5%prior 38
3
FORD42 (11.8%)
35.5%prior 31
4
CHEVROLET36 (10.1%)
0.0%prior 36
5
NISSAN26 (7.3%)
-33.3%prior 39
6
HYUNDAI17 (4.8%)
-39.3%prior 28
7
SUBARU13 (3.6%)
116.7%prior 6
8
KIA11 (3.1%)
22.2%prior 9
9
JEEP10 (2.8%)
-50.0%prior 20
10
DODGE9 (2.5%)
-18.2%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records

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

Sex Distribution (377 persons with recorded sex)

Male207 (54.9%)
-5.5%prior 219
Female170 (45.1%)
-20.6%prior 214

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 mph speed zones increased from 69 in October 2022 to 90 in October 2023. Conversely, crashes in 65 mph zones slightly decreased from 16 to 15. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-10-01 through 2023-10-31 (31 days)
  • Geographic scope: TAUNTON, MA
  • Total crash records analyzed: 198
  • Total persons involved: 423
  • Total vehicles involved: 357

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). "TAUNTON, MA Crash Intelligence Report: October 2023." Published June 21, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/taunton/october-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

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