ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · REVERE, 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/revere/2023-annual-report
Yearly Traffic Safety Analysis
746 CRASHES IN
REVERE, MA
2023
In 2023, Revere recorded 746 vehicle crashes, a 4.2% decrease from the 779 crashes reported in 2022. While overall collisions and resulting injuries saw a modest decline, the number of crashes involving pedestrians decreased more significantly, from 37 in 2022 to 24 in 2023.
746
▼ -4.2%was 779
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
303
▼ -5.6%was 321
Persons Injured
37
▼ -7.5%was 40
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. 25 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 metrics in Revere showed a general improvement from 2022 to 2023. The total number of crashes fell by 4.2%, from 779 to 746. This downward trend was also reflected in the number of people injured, which decreased from 321 to 303, and total fatalities, which dropped from 2 to 1.
37
Hit-and-Run Crashes — 2023
▼ -7.5% vs prior (40)
Hit-and-run incidents saw a slight decline from 2022 to 2023. The total number of hit-and-run crashes decreased from 40 to 37. The hit-and-run rate, which is the percentage of all crashes that were hit-and-runs, also saw a marginal decrease from 5.1% in 2022 to 5.0% in 2023.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
20
Pedestrians Injured
6
Cyclists Injured
273
Motorists Injured
4
Other 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 timing of crashes shifted between the two periods. In 2023, the peak day for crashes was Monday with 115 incidents, a change from 2022 when both Sunday and Friday were the peak days with 128 crashes each. The most common time for a collision moved slightly later in the day, from the 5 p.m. hour in 2022 (52 crashes) to the 6 p.m. hour in 2023 (53 crashes).
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
The overall severity of crashes decreased from 2022 to 2023, with the fatal crash rate dropping from 0.26% to 0.13% of all incidents. The number of crashes resulting in serious injuries fell from 23 to 13, a proportional decrease from 3.0% to 1.7% of all crashes. Conversely, the count of crashes involving possible injuries increased from 89 to 98.
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 top contributing factors cited in crashes remained consistent, with 'No improper driving' being the most common classification in both 2023 (208 incidents) and 2022 (223 incidents). The count of crashes attributed to 'Inattention' increased from 55 to 60. Incidents involving 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased in count from 48 to 41.
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 majority of crashes in both years occurred in clear weather on dry roads. However, there was a notable increase in the proportion of crashes happening on wet road surfaces, which rose from 13.5% of crashes in 2022 to 18.1% in 2023. Correspondingly, the share of crashes occurring during rain increased from 7.8% to 9.7% of the total. The distribution of crashes by lighting conditions remained stable, with approximately 52% occurring in daylight in both periods.
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, Honda, and Ford in both years. While the counts for Toyota and Ford were similar, the number of Hondas involved in collisions decreased from 260 in 2022 to 209 in 2023. An analysis of the ages of all persons involved in crashes shows the number of individuals aged 35-44 decreased from 350 to 280, while the number of people aged 65 and older increased from 99 to 134.
Top Vehicle Makes (1,394 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
170 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,532 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 showed some changes between the two years. Crashes in 25 mph zones, the most frequent location for incidents, decreased from 309 in 2022 to 274 in 2023. In contrast, crashes in 55 mph zones increased from 40 to 47. The single fatal crash recorded in 2023 occurred in a 35 mph zone.
Fatal crashes by zone: 35 mph: 1 of 83 (1.205%)
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: REVERE, MA
- Total crash records analyzed: 746
- Total persons involved: 1,740
- Total vehicles involved: 1,394
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: 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/revere/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