ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ROCKLAND, 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/rockland/2023-annual-report
Yearly Traffic Safety Analysis
253 CRASHES IN
ROCKLAND, MA
2023
In 2023, Rockland recorded 253 total traffic crashes, a 6.3% decrease from the 270 crashes in 2022. While the overall number of crashes fell, the most notable year-over-year shift was the registration of one fatal crash in 2023, whereas none were recorded in the prior year. Additionally, the total number of injuries reported increased from 107 to 114.
253
▼ -6.3%was 270
Total Crash Events
1
Persons Killed
114
▲ 6.5%was 107
Persons Injured
8
▲ 14.3%was 7
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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety data for Rockland shows a mixed trend. While the total number of crashes declined by 6.3% from 270 in 2022 to 253 in 2023, key severity metrics moved in the opposite direction. Total injuries rose by 6.5% from 107 to 114, and the city experienced one traffic fatality in 2023 after recording zero in the previous year.
8
Hit-and-Run Crashes — 2023
▲ 14.3% vs prior (7)
Hit-and-run incidents showed a slight upward trend. The total count of hit-and-run crashes increased from 7 in 2022 to 8 in 2023. As a percentage of all crashes, the hit-and-run rate also increased, rising from 2.6% in the prior year to 3.2% in the current year.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
2
Pedestrians Injured
4
Cyclists Injured
108
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 peak day for crashes remained Saturday in both 2022 and 2023, though the number of incidents on that day fell from 53 to 40. The peak hour also held steady at 4 p.m. for both periods, but the crash count during this hour increased from 22 to 27. A notable shift occurred on Sundays, where crashes more than doubled from 19 in 2022 to 39 in 2023.
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 worsened in 2023 compared to 2022. The city recorded one fatal crash resulting in one fatality, a category that had zero incidents in the prior year. The number of serious injury crashes saw a minor decrease from 8 to 7. Despite a drop in total crashes, the number of people injured rose from 107 to 114, and the proportion of crashes resulting in an injury of any kind increased from 30.7% in 2022 to 32.4% 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 leading contributing factors shifted between the two periods. In 2022, 'Inattention' was the top factor with 57 incidents, but this count dropped to 37 in 2023. 'Failed to yield right of way' saw an increase in count from 39 to 43 incidents. The number of crashes where 'No improper driving' was cited as a factor increased from 38 to 50, making it the most frequently cited factor in 2023.
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
The conditions under which crashes occurred saw some changes year-over-year. While crashes on dry roads remained most common, their share of the total decreased from 80.7% in 2022 to 73.9% in 2023. Concurrently, the count of crashes on wet roads increased from 43 to 60. Crashes in dark conditions (both lighted and unlighted) also rose, from 76 incidents in 2022 to 89 incidents in 2023.
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 three vehicle makes involved in crashes were Toyota, Ford, and Chevrolet in both years, with counts for each decreasing slightly in 2023. A significant shift was observed in the age of persons involved; the 65+ age group's involvement increased from 64 individuals in 2022 to 87 in 2023. In contrast, the number of persons in the 16-20 age group involved in crashes fell from 76 to 57.
Top Vehicle Makes (466 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 (548 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
The distribution of crashes across speed zones remained broadly consistent, with 30 mph and 35 mph zones accounting for the most incidents in both years. Crashes in 30 mph zones decreased from 107 to 96, while those in 35 mph zones increased slightly from 73 to 76. The single fatal crash recorded in 2023 occurred in a 25 mph speed zone.
Fatal crashes by zone: 25 mph: 1 of 21 (4.762%)
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: ROCKLAND, MA
- Total crash records analyzed: 253
- Total persons involved: 599
- Total vehicles involved: 466
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). "ROCKLAND, 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/rockland/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