ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · TAUNTON, MA · MAY 2024
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/taunton/may-2024-report
Monthly Traffic Safety Analysis
215 CRASHES IN
TAUNTON, MA
MAY 2024
In May 2024, Taunton experienced a notable increase in total crashes, rising to 215 from 184 in May 2023, representing a 16.85% increase. The most significant year-over-year shift was the emergence of a fatal crash and one fatality in May 2024, compared to zero in May 2023. Total injuries also saw an increase, climbing from 45 to 57.
215
▲ 16.8%was 184
Total Crash Events
1
Persons Killed
57
▲ 26.7%was 45
Persons Injured
25
▲ 47.1%was 17
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. 8 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for May 2024 indicates an upward trend in traffic incidents compared to May 2023. Total crashes increased by 16.85%, from 184 to 215, while total fatalities rose from 0 to 1. Injuries also increased by 26.67%, from 45 to 57, suggesting a worsening safety trend.
25
Hit-and-Run Crashes — May 2024
▲ 47.1% vs prior (17)
Hit-and-run crashes increased significantly, rising from 17 incidents in May 2023 to 25 in May 2024, a 47.06% increase. Correspondingly, the hit-and-run rate also trended upward, from 9.2% of total crashes to 11.6%.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
55
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted year-over-year, with the peak day moving from Monday in May 2023 (37 crashes) to Friday in May 2024 (40 crashes). The peak hour also changed from 4 PM with 27 crashes in May 2023 to 2 PM with 32 crashes in May 2024. This indicates a shift in the busiest times for crashes within the month.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution changed significantly, with one fatal crash occurring in May 2024 (0.47% fatal rate) compared to zero in May 2023. Serious injury crashes increased by 100%, from 1 to 2, while minor injury crashes rose by 47.37%, from 19 to 28. Conversely, possible injury crashes decreased slightly from 13 to 12.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'No improper driving' saw the largest increase, rising from 21 crashes in May 2023 to 50 in May 2024, a 138.1% increase in count. 'Inattention' increased by 6.06% in count, from 33 to 35 crashes, and 'Failed to yield right of way' increased by 3.45% in count, from 29 to 30 crashes. 'Followed too closely' also saw a 5% increase in count, from 20 to 21 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Clear weather conditions remained the most common factor, with crashes in 'Clear' conditions increasing from 89 to 115, and crashes in 'Rain' conditions doubling from 7 to 14. Daylight continued to be the predominant lighting condition for crashes, increasing from 154 to 174. Similarly, crashes on 'Dry' road surfaces increased from 167 to 185.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 19.64%, from 336 to 402, and total persons involved rose by 34.76%, from 397 to 535. Toyota remained the top vehicle make involved, increasing from 44 to 64, while Honda and Chevrolet also saw increases. The 35-44 age group experienced a 100% increase in persons involved, rising from 64 to 128, and the 16-20 age group saw a 116.67% increase, from 30 to 65 persons.
Top Vehicle Makes (402 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Vehicle unit records
40 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (489 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph speed zones remained the most frequent, increasing from 85 in May 2023 to 93 in May 2024. Notably, a fatal crash occurred in a 25 mph zone in May 2024, where no fatalities were recorded in May 2023. Crashes in 65 mph zones also increased from 11 to 16.
Fatal crashes by zone: 25 mph: 1 of 19 (5.263%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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: 2024-05-01 through 2024-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-05-01 through 2024-05-31 (31 days)
- Geographic scope: TAUNTON, MA
- Total crash records analyzed: 215
- Total persons involved: 535
- Total vehicles involved: 402
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: May 2024." Published June 21, 2026. Reporting period: 2024-05-01 to 2024-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/taunton/may-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-05-01 – 2024-05-31
Generated: June 21, 2026 · All rights reserved