ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · KINGSTON, MA · 2023
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/kingston/2023-annual-report
Yearly Traffic Safety Analysis
260 CRASHES IN
KINGSTON, MA
2023
In 2023, Kingston recorded 260 total traffic crashes, a 3.6% increase from the 251 crashes in 2022. While total crashes rose slightly, the most notable shift was a 25.8% increase in the number of people injured, which grew from 66 to 83. Conversely, the number of fatalities decreased from two in 2022 to one in 2023.
260
▲ 3.6%was 251
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
83
▲ 25.8%was 66
Persons Injured
10
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. 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 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Kingston show a slight increase in volume year-over-year, with total incidents rising by 3.6% from 251 to 260. While fatalities were halved from two to one, the number of persons injured in crashes grew by 25.8%, from 66 to 83. This indicates that while crashes were less frequently fatal, they resulted in more injuries compared to the prior year.
10
Hit-and-Run Crashes — 2023
▼ 0.0% vs prior (10)
The number of hit-and-run crashes in Kingston remained unchanged year-over-year, with 10 incidents recorded in both 2022 and 2023. Due to the slight increase in total crashes, the hit-and-run rate decreased marginally from 4.0% of all crashes in 2022 to 3.8% in 2023. This indicates a stable trend in the absolute count of these incidents.
Vulnerable Road User Casualties
0
Cyclists Killed
1
Motorists Killed
3
Cyclists Injured
80
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. In 2023, the peak day for crashes was Tuesday with 49 incidents, a change from 2022 when Friday was the peak day with 45 crashes. The peak hour for collisions also shifted slightly later in the afternoon, from 3 p.m. in 2022 (23 crashes) to 4 p.m. in 2023 (29 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the total number of fatal crashes decreased from two in 2022 to one in 2023, the composition of injury crashes changed significantly. The count of serious injury crashes fell from six to three, but minor injury crashes increased by 41.2%, from 34 in 2022 to 48 in 2023. Consequently, minor injuries represented 18.5% of all crash outcomes in 2023, up from a 13.5% share in the prior year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent, with 'Inattention' and 'Failed to yield right of way' following 'No improper driving' in both years. However, the count of crashes attributed to 'Inattention' increased from 26 to 36. Conversely, crashes involving a 'Distracted' driver saw a notable decrease in count, from 10 incidents in 2022 to just 2 in 2023. The count for 'Failed to yield right of way' remained stable, changing from 24 to 23.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in 2023 occurred more frequently in adverse weather and road conditions compared to 2022. The number of crashes in the rain more than doubled, from 14 to 33, and collisions on wet road surfaces increased from 36 to 65. There was also an increase in crashes occurring in darkness, with incidents on unlighted roadways rising from 27 to 36 and on lighted roadways from 28 to 34.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes remained largely stable, with Toyota and Ford holding the top two spots in both years. In terms of demographics, the age distribution of persons involved in crashes saw notable changes. The number of individuals aged 0-15 nearly doubled from 20 to 39, and the 35-44 age group saw a 34.5% increase from 55 to 74 persons. Conversely, involvement for the 26-34 age group decreased from 95 to 83 persons.
Top Vehicle Makes (471 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
31 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (523 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
There was a shift in where crashes occurred relative to posted speed limits. Crashes in 30 mph zones increased from 62 in 2022 to 78 in 2023, while crashes in 35 mph zones decreased from 66 to 47. The single fatal crash in 2023 occurred in a 30 mph zone. In 2022, the two fatal crashes were split between a 30 mph zone and a 60 mph zone.
Fatal crashes by zone: 30 mph: 1 of 78 (1.282%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: KINGSTON, MA
- Total crash records analyzed: 260
- Total persons involved: 569
- Total vehicles involved: 471
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). "KINGSTON, MA Crash Intelligence Report: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/kingston/2023-annual-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved