ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · REVERE, MA · 2024
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/2024-annual-report
Yearly Traffic Safety Analysis
773 CRASHES IN
REVERE, MA
2024
In 2024, Revere recorded 773 total crashes, a 3.6% increase from the 746 crashes reported in 2023. While the number of crashes involving injuries decreased slightly, the most notable year-over-year shift was the tripling of traffic fatalities from one in 2023 to three in 2024.
773
▲ 3.6%was 746
Total Crash Events
3
▲ 200.0%was 1
Persons Killed
293
▼ -3.3%was 303
Persons Injured
60
▲ 62.2%was 37
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 27 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Revere show a slight increase in total incidents year-over-year. Total crashes rose by 3.6%, from 746 in 2023 to 773 in 2024. In contrast, the number of people injured decreased by 3.3% from 303 to 293, while the number of fatalities increased from one to three.
60
Hit-and-Run Crashes — 2024
▲ 62.2% vs prior (37)
Hit-and-run incidents increased substantially in 2024 compared to the prior year. The total count of hit-and-run crashes rose by 62.2%, from 37 in 2023 to 60 in 2024. This trend is reflected in the hit-and-run rate, which climbed from 5.0% of all crashes in 2023 to 7.8% in 2024.
Vulnerable Road User Casualties
2
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
16
Pedestrians Injured
9
Cyclists Injured
255
Motorists Injured
13
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained largely consistent, with Monday being the peak day for crashes in both 2023 (115 crashes) and 2024 (129 crashes). However, the daily peak hour for crashes shifted three hours earlier, moving from 6 p.m. in 2023 (53 crashes) to 3 p.m. in 2024 (64 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes worsened in 2024, with the number of fatal crashes increasing from one to three. This resulted in the fatal crash rate rising from 0.13% in 2023 to 0.39% in 2024. The proportion of all crashes that resulted in an injury of any type (Serious, Minor, or Possible) decreased from 32.6% in 2023 to 29.0% in 2024.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
While 'No improper driving' remained the most common factor listed in both periods, its count fell from 208 to 197. A significant change occurred with crashes attributed to 'Followed too closely,' which saw their count increase by 92.5% from 40 in 2023 to 77 in 2024, moving from the fourth-ranked to the second-ranked factor. Conversely, crashes involving 'Inattention' decreased by 33.3% from 60 to 40, falling from the second to the fourth-ranked position.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
In both periods, the majority of crashes occurred during daylight on dry roads. The proportion of crashes happening in daylight increased from 52.8% in 2023 to 58.5% in 2024. Concurrently, the share of crashes on wet roads decreased from 18.1% of all incidents in 2023 to 14.1% in 2024, indicating a shift toward crashes in more favorable conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—were identical in both periods. An analysis of the age of persons involved in crashes reveals a demographic shift, with the share of individuals in the 26-34 age group increasing from 19.8% to 21.2% year-over-year. Similarly, the 35-44 age group's representation grew from 16.1% to 18.6% of all persons involved.
Top Vehicle Makes (1,471 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
201 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,627 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes became more concentrated in lower speed zones in 2024. The number of incidents in 25 mph zones increased from 274 to 322, while crashes in 55 mph zones decreased from 47 to 35. All three fatal crashes in 2024 occurred in zones posted at 35 mph or less (two in 25 mph zones, one in a 35 mph zone), whereas the single fatality in 2023 occurred in a 35 mph zone.
Fatal crashes by zone: 25 mph: 2 of 322 (0.621%) · 35 mph: 1 of 88 (1.136%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: REVERE, MA
- Total crash records analyzed: 773
- Total persons involved: 1,858
- Total vehicles involved: 1,471
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/revere/2024-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved