Monthly Traffic Safety Analysis

204 CRASHES IN
TAUNTON, MA
SEPTEMBER 2024

All metrics benchmarked againstSeptember 2023

In September 2024, Taunton experienced 204 crashes, a decrease of 5.12% from the 215 crashes recorded in September 2023. The most significant year-over-year shift was in fatalities, which increased from 0 in September 2023 to 3 in September 2024. Total injuries saw a slight increase, rising from 57 to 59.

204

-5.1%was 215

Total Crash Events

3

Persons Killed

59

3.5%was 57

Persons Injured

23

4.5%was 22

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes in Taunton decreased by 5.12%, from 215 in September 2023 to 204 in September 2024. Despite this reduction in overall incidents, total fatalities rose sharply from 0 to 3, representing a significant negative trend. Total injuries increased slightly by 3.51%, from 57 to 59.

23

Hit-and-Run Crashes — September 2024

4.5% vs prior (22)

Hit-and-run crashes increased slightly from 22 in September 2023 to 23 in September 2024, representing a 4.55% increase in count. The hit-and-run rate also saw an upward trend, rising from 10.2% of total crashes in the prior period to 11.3% in the current period.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

3

Motorists Killed

Prior: 0%

3

Cyclists Injured

Prior: 250.0%

56

Motorists Injured

Prior: 543.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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 in September 2023, with 37 incidents, to Thursday in September 2024, with 36 incidents. The peak hour remained consistent at 4 PM for both periods, though the count decreased slightly from 23 crashes in the prior period to 22 crashes in the current period. Crashes on Mondays and Wednesdays increased from 33 and 30 respectively in the prior period to 36 each in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes increased from 0 in September 2023 to 3 in September 2024, resulting in a fatal crash rate of 1.47% in the current period compared to 0% previously. Serious injury crashes decreased from 4 (1.9% of total crashes) in September 2023 to 1 (0.5% of total crashes) in September 2024. Minor injury crashes saw a slight increase from 27 (12.6% of total crashes) to 28 (13.7% of total crashes), while possible injury crashes remained constant at 12 for both periods.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1.5%
Serious Injury1serious injury crashes0.5%
-75.0%prior 4
Minor Injury28minor injury crashes13.7%
3.7%prior 27
Possible Injury12possible injury crashes5.9%
0.0%prior 12
No Injury147no injury crashes72.1%
-7.5%prior 159

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Inattention' increased by 13 crashes (39.39%), rising from 33 in September 2023 to 46 in September 2024, becoming the leading factor. 'Followed too closely' decreased by 8 crashes (25.81%), from 31 to 23. 'No improper driving' also decreased by 5 crashes (15.15%), from 33 to 28, indicating a shift towards more identified improper driving actions.

Officer-Reported Primary Contributing Cause

Inattention46 (22.5%)39.4%prior 33
No improper driving28 (13.7%)-15.2%prior 33
Failed to yield right of way28 (13.7%)-3.4%prior 29
Followed too closely23 (11.3%)-25.8%prior 31
Failure to keep in proper lane or running off road13 (6.4%)-13.3%prior 15
Distracted7 (3.4%)-12.5%prior 8
Other improper action5 (2.5%)-16.7%prior 6
Disregarded traffic signs, signals, road markings5 (2.5%)-28.6%prior 7
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway3 (1.5%)
Over-correcting/over-steering3 (1.5%)-50.0%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Clear weather conditions remained dominant, with 'Clear' or 'Clear/Clear' accounting for 162 crashes in September 2024, a slight increase from 146 in September 2023. Crashes occurring in rainy conditions significantly decreased, with 'Rain' or 'Rain/Rain' incidents dropping from 44 in the prior period to 10 in the current period. Daylight continued to be the predominant lighting condition, though daylight crashes decreased from 168 to 149, while crashes in 'Dark - lighted roadway' remained stable at 29-30 incidents. Wet road surface crashes saw a notable decrease from 55 in September 2023 to 16 in September 2024.

Weather

Clear95 (47.3%)
0.0%prior 95
Clear/Clear67 (33.3%)
31.4%prior 51
Cloudy17 (8.5%)
70.0%prior 10
Unknown/Unknown5 (2.5%)
Rain5 (2.5%)
-82.1%prior 28
Rain/Rain5 (2.5%)
-68.8%prior 16
Fog, smog, smoke/Fog, smog, smoke1 (0.5%)
Unknown/Clear1 (0.5%)
Rain/Cloudy1 (0.5%)
Clear/Cloudy1 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash

Lighting

Daylight149 (74.9%)
-11.3%prior 168
Dark - lighted roadway29 (14.6%)
-3.3%prior 30
Dusk8 (4.0%)
Dawn5 (2.5%)
0.0%prior 5
Dark - roadway not lighted5 (2.5%)
-28.6%prior 7
Dark - unknown roadway lighting3 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field

Road Surface

Dry178 (91.8%)
13.4%prior 157
Wet16 (8.2%)
-70.9%prior 55

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased by 25 (6.3%), from 397 in September 2023 to 372 in September 2024. TOYOTA remained the top vehicle make involved, though its count decreased from 62 to 53. The 35-44 age group saw a substantial increase in persons involved, rising from 93 in September 2023 to 121 in September 2024.

Top Vehicle Makes (372 vehicles)

1
TOYOTA53 (14.2%)
-14.5%prior 62
2
FORD49 (13.2%)
8.9%prior 45
3
HONDA42 (11.3%)
0.0%prior 42
4
CHEVROLET36 (9.7%)
-5.3%prior 38
5
NISSAN32 (8.6%)
0.0%prior 32
6
JEEP20 (5.4%)
-16.7%prior 24
7
HYUNDAI17 (4.6%)
30.8%prior 13
8
MAZDA11 (3%)
9
KIA10 (2.7%)
0.0%prior 10
10
SUBARU9 (2.4%)
-10.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records

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

Sex Distribution (442 persons with recorded sex)

Female228 (51.6%)
18.8%prior 192
Male214 (48.4%)
-8.9%prior 235

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones increased from 73 in September 2023 to 96 in September 2024, with 1 fatal crash occurring in this zone in the current period, compared to 0 in the prior period. Crashes in 25 mph zones decreased from 19 to 14, with 1 fatal crash in the current period. A fatal crash also occurred in a 50 mph zone in September 2024, where there were 6 crashes compared to 5 in the prior period, which had no fatalities.

Fatal crashes by zone: 25 mph: 1 of 14 (7.143%) · 30 mph: 1 of 96 (1.042%) · 50 mph: 1 of 6 (16.667%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-09-01 through 2024-09-30 (30 days)
  • Geographic scope: TAUNTON, MA
  • Total crash records analyzed: 204
  • Total persons involved: 499
  • Total vehicles involved: 372

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: September 2024." Published June 21, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/taunton/september-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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Taunton, MA Crash Report — September 2024 | ThatCarHitMe.com