ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · HULL, MA · 2022
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/hull/2022-annual-report
Yearly Traffic Safety Analysis
150 CRASHES IN
HULL, MA
2022
In 2022, Hull recorded 150 total crashes, a 2% increase from the 147 crashes reported in 2021. While the total number of crashes remained relatively stable, the most significant year-over-year change was the increase in crash severity. After recording zero fatalities in the prior year, there were two traffic-related fatalities in 2022, and the total number of injuries rose by 80% from 20 to 36.
150
▲ 2.0%was 147
Total Crash Events
2
Persons Killed
36
▲ 80.0%was 20
Persons Injured
15
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 20 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash volume in Hull saw a slight increase of 2%, rising from 147 incidents in 2021 to 150 in 2022. However, the severity of these crashes worsened considerably, with total injuries increasing by 80% year-over-year and two fatalities occurring in 2022 compared to none in the previous year.
15
Hit-and-Run Crashes — 2022
▼ 0.0% vs prior (15)
The number of hit-and-run crashes remained unchanged year-over-year, with 15 incidents recorded in both 2021 and 2022. Consequently, the hit-and-run rate was stable, representing 10.2% of all crashes in 2021 and 10.0% in 2022. This indicates no significant trend change in hit-and-run incidents for the period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
2
Pedestrians Injured
7
Cyclists Injured
27
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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 2022, the peak day for crashes was Friday with 36 incidents, a change from 2021 when Saturday was the peak day with 30 crashes. Similarly, the peak hour for collisions moved from 11 a.m. in 2021 (14 crashes) to 3 p.m. in 2022 (18 crashes), suggesting a shift in high-risk times from late morning to the afternoon.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity increased significantly in 2022 compared to 2021. The number of fatal crashes rose from zero to two, representing 1.3% of all crashes in 2022. The proportion of crashes involving any injury grew from 11.6% in 2021 to 20.6% in 2022. Notably, 8 crashes were classified as resulting in 'Serious Injury' in 2022, a severity level not recorded in the prior year's data.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
While 'No improper driving' was the most common factor in both years with a stable count of 40 crashes, the ranking of other contributing factors shifted. The count of crashes attributed to 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased from 7 to 11. Conversely, crashes involving 'Inattention' saw a slight decrease in count from 18 to 16, and 'Over-correcting/over-steering' dropped from being the third-most cited factor with 9 crashes in 2021 to just 1 crash in 2022.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The majority of crashes in both years occurred in clear weather on dry roads during daylight hours. In 2022, the proportion of crashes happening in daylight was 69.3% (104 crashes), similar to 67.3% (99 crashes) in 2021. Crashes on dry road surfaces accounted for 76.7% of incidents in 2022, a slight decrease from 81% in the prior year. The share of crashes during clear weather increased from 52.4% in 2021 to 60.7% in 2022.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
Toyota and Ford remained the top two vehicle makes involved in crashes for both years, with Toyota's involvement increasing from 32 to 47 vehicles. In 2022, Honda (25 vehicles) replaced Jeep as the third most common make. Regarding demographics of persons involved, the 65+ age group was the largest in both periods, increasing from 46 individuals in 2021 to 53 in 2022. The 45-54 age group also saw its representation double, from 17 people involved in 2021 to 34 in 2022.
Top Vehicle Makes (262 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
48 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (263 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
The vast majority of crashes in both years occurred in 30 mph zones, though the count in this zone decreased from 110 in 2021 to 103 in 2022. Conversely, crashes in 35 mph zones nearly tripled, rising from 7 to 20 incidents. The two fatal crashes recorded in 2022 occurred in lower speed zones: one in a 25 mph zone and one in a 30 mph zone.
Fatal crashes by zone: 25 mph: 1 of 11 (9.091%) · 30 mph: 1 of 103 (0.971%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: HULL, MA
- Total crash records analyzed: 150
- Total persons involved: 316
- Total vehicles involved: 262
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). "HULL, MA Crash Intelligence Report: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hull/2022-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: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved