ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · REVERE, MA · MAY 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/revere/may-2022-report
Monthly Traffic Safety Analysis
68 CRASHES IN
REVERE, MA
MAY 2022
In May 2022, Revere, MA recorded 68 total crashes, a decrease from 70 crashes in May 2021. Despite this slight reduction in overall crashes, total injuries increased by 57.1% from 28 to 44 during the same period. This indicates a notable shift towards more injury-involved crashes year-over-year.
68
▼ -2.9%was 70
Total Crash Events
0
Persons Killed
44
▲ 57.1%was 28
Persons Injured
6
▲ 20.0%was 5
Hit-and-Run Crashes
Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 3 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The total number of crashes in Revere, MA decreased slightly by 2 crashes, from 70 in May 2021 to 68 in May 2022. However, the total number of injuries rose significantly by 16, from 28 to 44, representing a 57.1% increase year-over-year. Fatalities remained at zero in both periods.
6
Hit-and-Run Crashes — May 2022
▲ 20.0% vs prior (5)
The number of hit-and-run crashes increased from 5 in May 2021 to 6 in May 2022. The hit-and-run crash rate also increased from 7.1% of all crashes in May 2021 to 8.8% in May 2022. This indicates an upward trend in hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
3
Pedestrians Injured
1
Cyclists Injured
40
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Saturday in May 2021 (14 crashes) to Tuesday in May 2022 (14 crashes). Crashes on Thursdays decreased from 12 to 2, while crashes on Tuesdays increased from 6 to 14. The peak hour also shifted from 6 PM in May 2021 (6 crashes) to 4 PM in May 2022 (7 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either period. The number of crashes resulting in serious injury decreased from 2 in May 2021 to 1 in May 2022. Crashes with minor injuries increased from 14 to 15, and crashes with possible injuries significantly increased from 6 to 13. The proportion of crashes resulting in any injury (serious, minor, or possible) increased from 31.4% in May 2021 to 42.6% in May 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Most severe injury per crash record
Top Contributing Factors
The count of crashes attributed to 'No improper driving' decreased from 25 in May 2021 to 17 in May 2022, a 32% reduction. Conversely, crashes due to 'Followed too closely' increased by 150%, from 2 to 5, and 'Failed to yield right of way' crashes increased by 400%, from 1 to 5. Crashes involving 'Distracted' driving decreased from 4 to 1, a 75% reduction in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring under clear weather conditions remained consistent at 53 in both periods, while crashes in rainy conditions decreased from 9 in May 2021 to 5 in May 2022. Crashes on dry road surfaces increased from 59 to 61, while those on wet road surfaces decreased from 10 to 7. The number of crashes occurring in daylight decreased slightly from 45 to 42, while crashes in dark conditions (lighted or unlighted roadway) remained at 23 in both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 138 in May 2021 to 131 in May 2022. Toyota remained the top vehicle make, with its involvement increasing from 18 to 24. Jeep involvement saw a significant increase from 6 to 12, while Chevrolet involvement decreased from 16 to 3. There was a notable increase in crashes involving persons aged 0-15 (from 5 to 10) and 26-34 (from 32 to 39), while involvement of persons aged 21-25 decreased from 24 to 14.
Top Vehicle Makes (131 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Vehicle unit records
21 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (130 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Person-level records linked to crash events
Speed Limit Zones
There were no fatal crashes reported across any speed limit zone in either period. Crashes in 25 mph zones slightly decreased from 27 to 26, and those in 50 mph zones decreased from 8 to 4. Conversely, crashes in 45 mph zones increased from 2 to 4, and 55 mph zones increased from 2 to 3. Overall, there was no clear shift towards higher or lower speed zones.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · 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: 2022-05-01 through 2022-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-05-01 through 2022-05-31 (31 days)
- Geographic scope: REVERE, MA
- Total crash records analyzed: 68
- Total persons involved: 164
- Total vehicles involved: 131
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). "REVERE, MA Crash Intelligence Report: May 2022." Published June 21, 2026. Reporting period: 2022-05-01 to 2022-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/revere/may-2022-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: 2022-05-01 – 2022-05-31
Generated: June 21, 2026 · All rights reserved