ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · TAUNTON, MA · JULY 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/july-2024-report
Monthly Traffic Safety Analysis
170 CRASHES IN
TAUNTON, MA
JULY 2024
In July 2024, Taunton experienced 170 total crashes, a decrease of 12.82% compared to the 195 crashes reported in July 2023. The most significant year-over-year shift was the absence of fatalities in the current period, down from 2 fatalities in the prior year.
170
▼ -12.8%was 195
Total Crash Events
0
▼ -100.0%was 2
Persons Killed
43
▼ -44.9%was 78
Persons Injured
18
▼ -14.3%was 21
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. 9 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a decrease in crash incidents, with total crashes falling from 195 in July 2023 to 170 in July 2024. This represents a reduction of 25 crashes, or 12.82%, year-over-year.
18
Hit-and-Run Crashes — July 2024
▼ -14.3% vs prior (21)
Hit-and-run crashes decreased from 21 in July 2023 to 18 in July 2024. The hit-and-run rate slightly decreased from 10.8% to 10.6% year-over-year, indicating a minor downward trend in the proportion of crashes involving a hit-and-run.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
2
Pedestrians Injured
1
Cyclists Injured
40
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · 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 Friday in July 2023, which had 34 crashes, to Tuesday in July 2024, with 29 crashes. Similarly, the peak crash hour moved from 5 PM in July 2023, recording 19 crashes, to 1 PM in July 2024, with 17 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities saw a positive change, decreasing from 2 in July 2023 to 0 in July 2024, and fatal crashes also dropped from 2 to 0. Total injuries decreased from 78 to 43, while serious injuries (code A) decreased from 5 (2.6% of crashes) to 1 (0.6% of crashes). Minor injuries (code B) also saw a reduction from 36 (18.5% of crashes) to 19 (11.2% of crashes).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor, 'Failed to yield right of way,' increased by 6 crashes, from 24 in July 2023 to 30 in July 2024, representing a 25% count-based increase. Conversely, 'Inattention' decreased by 8 crashes, from 37 to 29, a 21.6% count-based decrease, while 'No improper driving' decreased by 12 crashes, from 38 to 26, a 31.6% count-based decrease. 'Failed to yield right of way' became the most frequent factor in the current period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions decreased from 94 to 83, and 'Clear/Clear' conditions decreased from 78 to 67. The number of crashes during 'Daylight' conditions slightly decreased from 143 to 136, while crashes in 'Dark - lighted roadway' conditions decreased from 37 to 25. The count of crashes on 'Dry' road surfaces decreased from 178 to 158, though 'Wet' surface crashes remained stable at 12.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 362 in July 2023 to 308 in July 2024. Toyota remained the most frequently involved vehicle make, though its count decreased from 59 to 53, while Honda vehicles decreased from 41 to 37. Regarding persons involved, the number of male persons decreased from 246 to 176, and the 26-34 age group saw a significant reduction from 100 to 62 persons involved.
Top Vehicle Makes (308 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Vehicle unit records
33 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (333 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph zones decreased significantly from 99 to 62, and fatal crashes in this zone dropped from 1 to 0. Crashes in 65 mph zones also decreased from 15 to 8, with fatalities in this zone falling from 1 to 0. Conversely, crashes in 35 mph zones increased from 19 to 29.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · 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: 2024-07-01 through 2024-07-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-07-01 through 2024-07-31 (31 days)
- Geographic scope: TAUNTON, MA
- Total crash records analyzed: 170
- Total persons involved: 375
- Total vehicles involved: 308
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: July 2024." Published June 21, 2026. Reporting period: 2024-07-01 to 2024-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/taunton/july-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: 2024-07-01 – 2024-07-31
Generated: June 21, 2026 · All rights reserved