Monthly Traffic Safety Analysis

177 CRASHES IN
TAUNTON, MA
JANUARY 2023

All metrics benchmarked againstJanuary 2022

Total crashes in January 2023 were 177, a slight increase from the 171 crashes recorded in January 2022, representing a 3.5% rise. Despite the overall increase in crashes, total injuries decreased by 19.0%, from 42 to 34. The most notable year-over-year shift was in hit-and-run incidents, which saw a substantial increase from 2 crashes in January 2022 to 16 crashes in January 2023.

177

3.5%was 171

Total Crash Events

0

Persons Killed

34

-19.0%was 42

Persons Injured

16

700.0%was 2

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. 7 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 2023-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the number of crashes in January 2023 increased by 3.5% compared to January 2022, rising from 171 to 177. Conversely, total injuries decreased by 19.0%, from 42 in January 2022 to 34 in January 2023. Fatalities remained at zero in both periods, indicating a stable trend for the most severe outcomes.

16

Hit-and-Run Crashes — January 2023

700.0% vs prior (2)

Hit-and-run crashes increased dramatically from 2 incidents in January 2022 to 16 incidents in January 2023, representing a 700% increase. The hit-and-run rate consequently rose from 1.2% of all crashes in January 2022 to 9% in January 2023, indicating a significant upward trend in these types of incidents.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 10.0%

33

Motorists Injured

Prior: 40-17.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Friday in both periods, though the count on Fridays decreased from 32 in January 2022 to 30 in January 2023. The peak hour for crashes remained 3 PM, with the count increasing from 19 crashes in January 2022 to 21 crashes in January 2023. Monday also emerged as a peak day in January 2023, matching Friday's count of 30 crashes.

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

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

Crash Severity Breakdown

The fatal crash rate remained at 0% in both January 2022 and January 2023. Crashes resulting in serious injuries (Severity A) saw a slight increase from 3 (1.8% share) to 4 (2.3% share). Minor injury crashes (Severity B) decreased from 23 (13.5% share) to 21 (11.9% share), while possible injury crashes (Severity C) decreased significantly from 10 (5.8% share) to 4 (2.3% share).

Outcome by Severity (Crash Events)

Serious Injury4serious injury crashes2.3%
33.3%prior 3
Minor Injury21minor injury crashes11.9%
-8.7%prior 23
Possible Injury4possible injury crashes2.3%
-60.0%prior 10
No Injury141no injury crashes79.7%
10.2%prior 128

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

The leading contributing factor, 'No improper driving,' decreased from 41 crashes in January 2022 to 34 crashes in January 2023, a 17.1% decrease in count, with its share dropping from 24% to 19.2%. 'Failed to yield right of way' increased from 24 to 29 crashes, a 20.8% increase in count, and 'Inattention' rose from 21 to 26 crashes, a 23.8% increase in count. Notably, 'Followed too closely' saw a substantial 75% increase in count, rising from 12 crashes in January 2022 to 21 crashes in January 2023, with its share increasing from 7% to 11.9%.

Officer-Reported Primary Contributing Cause

No improper driving34 (19.2%)-17.1%prior 41
Failed to yield right of way29 (16.4%)20.8%prior 24
Inattention26 (14.7%)23.8%prior 21
Followed too closely21 (11.9%)75.0%prior 12
Failure to keep in proper lane or running off road7 (4%)-22.2%prior 9
Driving too fast for conditions6 (3.4%)20.0%prior 5
Exceeded authorized speed limit4 (2.3%)
Visibility obstructed4 (2.3%)
Distracted4 (2.3%)-42.9%prior 7
Disregarded traffic signs, signals, road markings3 (1.7%)

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

Road & Environmental Conditions

Crashes occurring in clear weather conditions (including 'Clear' and 'Clear/Clear') decreased from 122 in January 2022 to 85 in January 2023. Conversely, crashes during rain conditions increased from 7 to 21, and snow-related crashes decreased from 15 to 7. Regarding road surface conditions, crashes on wet roads significantly increased from 25 to 64, while crashes on dry roads decreased from 102 to 94, and snow-covered roads saw a decrease from 32 to 8 crashes.

Weather

Clear44 (25.3%)
-63.9%prior 122
Clear/Clear41 (23.6%)
Rain21 (12.1%)
200.0%prior 7
Cloudy21 (12.1%)
23.5%prior 17
Rain/Cloudy11 (6.3%)
Snow7 (4.0%)
-53.3%prior 15
Rain/Rain7 (4.0%)
Cloudy/Rain5 (2.9%)
Snow/Cloudy3 (1.7%)
Cloudy/Snow2 (1.1%)

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

Lighting

Daylight93 (53.1%)
-5.1%prior 98
Dark - lighted roadway56 (32.0%)
14.3%prior 49
Dusk12 (6.9%)
33.3%prior 9
Dark - roadway not lighted8 (4.6%)
-20.0%prior 10
Dawn5 (2.9%)
0.0%prior 5
Dark - unknown roadway lighting1 (0.6%)

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

Road Surface

Dry94 (54.3%)
-7.8%prior 102
Wet64 (37.0%)
156.0%prior 25
Snow8 (4.6%)
-75.0%prior 32
Ice5 (2.9%)
-50.0%prior 10
Other1 (0.6%)
Sand, mud, dirt, oil, gravel1 (0.6%)

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

Vehicles & Demographics

Toyota remained the top vehicle make involved in crashes, increasing from 37 vehicles in January 2022 to 41 in January 2023. Honda also saw an increase from 30 to 36 vehicles, and Ford increased from 31 to 33 vehicles. The age group of persons aged 16-20 involved in crashes saw a notable increase of 84.6%, from 26 in January 2022 to 48 in January 2023. Similarly, persons aged 65 and older involved in crashes increased by 77.8%, from 18 to 32.

Top Vehicle Makes (310 vehicles)

1
TOYOTA41 (13.2%)
10.8%prior 37
2
HONDA36 (11.6%)
20.0%prior 30
3
FORD33 (10.6%)
6.5%prior 31
4
CHEVROLET28 (9%)
7.7%prior 26
5
NISSAN25 (8.1%)
-10.7%prior 28
6
HYUNDAI20 (6.5%)
25.0%prior 16
7
DODGE18 (5.8%)
157.1%prior 7
8
JEEP16 (5.2%)
60.0%prior 10
9
KIA9 (2.9%)
50.0%prior 6
10
ACURA8 (2.6%)
33.3%prior 6

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

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

Sex Distribution (340 persons with recorded sex)

Male175 (51.5%)
-7.9%prior 190
Female165 (48.5%)
55.7%prior 106

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

Speed Limit Zones

Crashes in 30 mph speed zones increased from 67 in January 2022 to 71 in January 2023. However, crashes in 35 mph zones decreased from 33 to 13. Crashes in 65 mph zones saw an increase from 14 to 17. There were no fatal crashes reported in any speed zone for either period.

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

Data Coverage

  • Reporting period: 2023-01-01 through 2023-01-31 (31 days)
  • Geographic scope: TAUNTON, MA
  • Total crash records analyzed: 177
  • Total persons involved: 374
  • Total vehicles involved: 310

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

ThatCarHitMe.com · An Injuria.ai Company

Taunton, MA Crash Report — January 2023 | ThatCarHitMe.com