ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · HANSON, 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/hanson/2023-annual-report
Yearly Traffic Safety Analysis
163 CRASHES IN
HANSON, MA
2023
In 2023, Hanson recorded 163 total traffic crashes, an 18.1% increase from the 138 crashes reported in 2022. While the total number of reported injuries decreased, the most significant year-over-year change was the occurrence of one fatal crash in 2023, compared to zero in the prior year.
163
▲ 18.1%was 138
Total Crash Events
1
Persons Killed
30
▼ -26.8%was 41
Persons Injured
11
▲ 120.0%was 5
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 traffic crash trends in Hanson show a notable increase year-over-year, with total incidents rising by 18.1% from 138 in 2022 to 163 in 2023. Despite the higher volume of crashes, the total number of injuries reported decreased by 26.8%, from 41 to 30. The year 2023 also recorded one fatality, whereas 2022 had none.
11
Hit-and-Run Crashes — 2023
▲ 120.0% vs prior (5)
The incidence of hit-and-run crashes in Hanson showed a significant upward trend. The number of hit-and-run incidents more than doubled, increasing from 5 in 2022 to 11 in 2023. Consequently, the hit-and-run rate, which measures the percentage of total crashes that are hit-and-runs, rose from 3.6% to 6.7% over the same period.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Motorists Killed
0
Other Killed
0
Pedestrians Injured
29
Motorists Injured
1
Other 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 temporal patterns of crashes shifted slightly between the two periods. In 2023, the peak day for crashes was Friday with 28 incidents, moving from Saturday (26 incidents) in 2022. Similarly, the peak hour for crashes shifted an hour earlier to 3 p.m. in 2023, which saw 18 crashes, compared to the 4 p.m. peak in 2022 with 14 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
Crash severity saw a mixed change year-over-year. The most significant shift was the registration of one fatal crash in 2023, resulting in a fatal rate of 0.61 per 100 crashes, up from zero in 2022. Conversely, the proportion of crashes resulting in injuries decreased; serious injury crashes fell from 2.2% to 1.2% of all incidents, and minor injury crashes dropped from 12.3% to 8.6%. Consequently, the share of no-injury crashes grew from 73.9% in 2022 to 81.6% in 2023.
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 top contributing factors cited in crashes remained consistent in their ranking year-over-year, with 'No improper driving,' 'Inattention,' and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' as the top three in both periods. However, the counts for several key factors increased notably in 2023. Crashes attributed to 'Inattention' rose by count from 17 to 22, and those involving an 'erratic, reckless, careless, negligent or aggressive manner' increased by count from 8 to 15. Additionally, crashes involving 'Followed too closely' increased from 4 to 9.
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
While the majority of crashes in both years occurred in clear weather on dry roads, there was a notable increase in crashes under adverse conditions in 2023. The proportion of crashes on wet road surfaces grew from 12.3% in 2022 to 17.8% in 2023. Similarly, crashes occurring in the dark on lighted roadways increased from 24 incidents (17.4% of total) in 2022 to 42 incidents (25.8% of total) in 2023. The share of crashes happening during rainy or snowy weather also increased from 5.8% to 11.7% year-over-year.
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 vehicle makes most frequently involved in crashes saw a shift in rankings between 2022 and 2023. Toyota became the most common make in 2023 with 39 vehicles involved, up from 24 the prior year, while Ford dropped from first to third place. In terms of persons involved, there was an increase in representation from younger and middle-aged groups; the number of persons in the 16-20 age group grew from 39 to 51, and the 35-44 age group increased from 34 to 53.
Top Vehicle Makes (264 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
24 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (284 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
Crashes remained concentrated in similar speed zones year-over-year, with the 35 mph zone accounting for the largest number of incidents in both periods (62 in 2022, 88 in 2023). The number of crashes also increased in the 30 mph zone, rising from 26 to 34. The single fatal crash recorded in 2023 occurred in a 10 mph speed zone; no fatal crashes were reported in any speed zone during the prior year.
Fatal crashes by zone: 10 mph: 1 of 2 (50%)
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: HANSON, MA
- Total crash records analyzed: 163
- Total persons involved: 315
- Total vehicles involved: 264
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). "HANSON, 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/hanson/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