ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ROCKPORT, 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/rockport/2022-annual-report
Yearly Traffic Safety Analysis
55 CRASHES IN
ROCKPORT, MA
2022
In 2022, Rockport recorded 55 total crashes, an increase from the 51 crashes reported in 2021, representing a 7.8% year-over-year rise. While the number of people injured in crashes decreased from 19 to 11, the most significant change was the occurrence of one fatal crash in 2022, whereas none were recorded in the prior year. This fatal crash involved a pedestrian.
55
▲ 7.8%was 51
Total Crash Events
1
Persons Killed
11
▼ -42.1%was 19
Persons Injured
1
▼ -75.0%was 4
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. 4 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
The overall crash trend in Rockport shows a slight increase year-over-year, with total collisions rising by 7.8% from 51 in 2021 to 55 in 2022. Despite this increase in total crashes, the number of people injured decreased by 42.1%, from 19 to 11. However, 2022 saw one fatality, compared to zero in the previous year.
1
Hit-and-Run Crashes — 2022
▼ -75.0% vs prior (4)
The number of hit-and-run incidents in Rockport decreased significantly year-over-year. In 2022, there was only 1 reported hit-and-run crash, down from 4 in 2021. This represents a substantial drop in the hit-and-run rate, which fell from 7.8% of all crashes in 2021 to 1.8% in 2022.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
10
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 temporal patterns of crashes in Rockport shifted between the two periods. In 2022, the peak day for crashes was Wednesday with 11 incidents, a change from 2021 when Monday was the peak day with 12 crashes. Similarly, the peak hour for crashes moved from 1 p.m. in 2021 (8 crashes) to 2 p.m. in 2022 (10 crashes).
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 analysis reveals a mixed picture year-over-year. In 2022, Rockport recorded one fatal crash, accounting for 1.8% of all incidents, whereas no fatal crashes occurred in 2021. Conversely, the number of serious injury crashes dropped from three in 2021 to zero in 2022. The proportion of crashes resulting in no injuries increased from a 58.8% share in 2021 to a 72.7% share in 2022.
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
A comparison of contributing factors shows a notable shift in driver behavior. While 'No improper driving' remained the most cited factor in both years, its count decreased from 19 in 2021 to 17 in 2022. The count of crashes attributed to 'Inattention' increased by 83.3%, rising from 6 incidents in 2021 to 11 in 2022, making it the second-most common factor. Conversely, crashes involving an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased from a count of 5 to 2.
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
Crashes in both years predominantly occurred in clear and dry conditions. In 2022, 80% of crashes happened in clear weather, up from a 66.7% share in 2021, and 89.1% occurred on dry roads, compared to an 86.3% share the prior year. Crashes in daylight remained the majority, accounting for 76.4% of incidents in 2022, similar to the 78.4% share in 2021. However, crashes on dark but lighted roadways saw an increase, from 7 incidents in 2021 to 10 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
The demographic profile of persons involved in crashes and the makes of vehicles showed some year-over-year changes. The 65+ age group remained the most represented, growing from 24 individuals in 2021 to 33 in 2022. Regarding vehicle makes, Ford and Toyota were the most common in both years, with 17 vehicles of each make involved in 2022 crashes. Chevrolet's involvement increased from 7 vehicles to 12, while the number of Subarus involved decreased from 10 to 5.
Top Vehicle Makes (102 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
28 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (100 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
Analysis of crashes by posted speed limit shows a concentration in lower-speed zones for both years. The 25 mph zone saw the largest number of crashes in 2022 with 23 incidents, an increase from 18 in 2021. This zone was also the location of the year's only fatal crash. Conversely, crashes in 30 mph zones decreased from 9 in 2021 to 5 in 2022. No fatal crashes were recorded in any speed zone during the prior period.
Fatal crashes by zone: 25 mph: 1 of 23 (4.348%)
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: ROCKPORT, MA
- Total crash records analyzed: 55
- Total persons involved: 127
- Total vehicles involved: 102
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). "ROCKPORT, 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/rockport/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