Yearly Traffic Safety Analysis

779 CRASHES IN
REVERE, MA
2022

All metrics benchmarked against2021

In Revere, total traffic crashes decreased by 4.5% from 816 in 2021 to 779 in 2022. While overall crashes and injuries declined, the most notable year-over-year shift was a 54% increase in pedestrian-involved crashes, which rose from 24 to 37 incidents.

779

-4.5%was 816

Total Crash Events

2

Persons Killed

321

-8.5%was 351

Persons Injured

40

-9.1%was 44

Hit-and-Run Crashes

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 34 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 trend in traffic collisions in Revere shows a decrease between 2021 and 2022. Total crashes fell by 4.5% from 816 to 779, and the number of people injured decreased by 8.5% from 351 to 321. The number of fatalities remained unchanged, with two recorded in both years.

40

Hit-and-Run Crashes — 2022

-9.1% vs prior (44)

Hit-and-run incidents showed a downward trend between the two periods. The total number of hit-and-run crashes decreased from 44 in 2021 to 40 in 2022. The hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, also declined slightly from 5.4% to 5.1%.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

2

Motorists Killed

Prior: 20.0%

0

Other Killed

Prior: 00.0%

34

Pedestrians Injured

Prior: 2070.0%

6

Cyclists Injured

Prior: 8-25.0%

279

Motorists Injured

Prior: 322-13.4%

2

Other Injured

Prior: 1100.0%

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 remained broadly consistent year-over-year. The peak hour for collisions was 5 PM in both 2021 and 2022, although the number of crashes during that hour fell from 65 to 52. In 2021, Sunday was the single busiest day for crashes with 135 incidents, while in 2022, Friday and Sunday were tied for the most crashes at 128 each.

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

The severity profile of crashes showed minor changes between the two periods. The number of fatal crashes was stable at two for both years, with the fatal crash rate remaining nearly flat at 0.25% in 2021 and 0.26% in 2022. The share of crashes resulting in serious injuries decreased from 3.8% (31 crashes) to 3.0% (23 crashes), and minor injury crashes also saw their share fall from 18.4% to 16.9%.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.3%
0.0%prior 2
Serious Injury23serious injury crashes3%
-25.8%prior 31
Minor Injury132minor injury crashes16.9%
-12.0%prior 150
Possible Injury89possible injury crashes11.4%
3.5%prior 86
No Injury499no injury crashes64.1%
-2.7%prior 513

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

The leading contributing factors for crashes were consistent across both years, with "No improper driving" being the most cited factor, followed by "Inattention" and "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner." The count of crashes attributed to "Inattention" decreased from 68 in 2021 to 55 in 2022. In contrast, crashes involving "Followed too closely" increased in count from 31 to 44.

Officer-Reported Primary Contributing Cause

No improper driving223 (28.6%)-7.9%prior 242
Inattention55 (7.1%)-19.1%prior 68
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner48 (6.2%)-12.7%prior 55
Followed too closely44 (5.6%)41.9%prior 31
Failed to yield right of way28 (3.6%)3.7%prior 27
Other improper action26 (3.3%)-7.1%prior 28
Exceeded authorized speed limit21 (2.7%)0.0%prior 21
Driving too fast for conditions21 (2.7%)-19.2%prior 26
Disregarded traffic signs, signals, road markings20 (2.6%)-4.8%prior 21
Distracted19 (2.4%)26.7%prior 15

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 weather and on dry road surfaces. The number of crashes during clear weather was nearly identical, with 571 in 2021 and 570 in 2022. Crashes on wet roads saw a notable decrease, falling from 143 incidents in 2021 to 105 in 2022. Collisions in daylight conditions also decreased from 448 to 405, while crashes in dark, lighted roadway conditions were unchanged at 319.

Weather

Clear570 (76.0%)
-0.2%prior 571
Rain61 (8.1%)
-32.2%prior 90
Cloudy31 (4.1%)
-35.4%prior 48
Clear/Unknown21 (2.8%)
-12.5%prior 24
Cloudy/Rain16 (2.1%)
-11.1%prior 18
Snow15 (2.0%)
-11.8%prior 17
Clear/Cloudy8 (1.1%)
14.3%prior 7
Clear/Other6 (0.8%)
-25.0%prior 8
Rain/Cloudy5 (0.7%)
0.0%prior 5
Clear/Snow3 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight405 (52.1%)
-9.6%prior 448
Dark - lighted roadway319 (41.1%)
0.0%prior 319
Dawn21 (2.7%)
90.9%prior 11
Dusk16 (2.1%)
-5.9%prior 17
Dark - roadway not lighted11 (1.4%)
-21.4%prior 14
Dark - unknown roadway lighting5 (0.6%)
-16.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry646 (83.0%)
0.3%prior 644
Wet105 (13.5%)
-26.6%prior 143
Snow19 (2.4%)
35.7%prior 14
Ice7 (0.9%)
-30.0%prior 10
Slush1 (0.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained similar, with Toyota and Honda leading in both years. While the count of Toyotas involved decreased from 277 to 266, the count of Hondas increased from 212 to 260. The 26-34 age group represented the largest number of persons involved in crashes in both periods. However, the number of persons in the 21-25 age group decreased from 251 to 194, while those in the 35-44 age group increased from 315 to 350.

Top Vehicle Makes (1,475 vehicles)

1
TOYOTA266 (18%)
-4.0%prior 277
2
HONDA260 (17.6%)
22.6%prior 212
3
FORD128 (8.7%)
-19.0%prior 158
4
NISSAN111 (7.5%)
-7.5%prior 120
5
CHEVROLET99 (6.7%)
-14.7%prior 116
6
JEEP74 (5%)
37.0%prior 54
7
HYUNDAI50 (3.4%)
13.6%prior 44
8
MERCEDES-BENZ37 (2.5%)
-11.9%prior 42
9
BMW31 (2.1%)
3.3%prior 30
10
SUBARU30 (2%)
-25.0%prior 40

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

229 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (1,587 persons with recorded sex)

Male978 (61.6%)
-0.3%prior 981
Female609 (38.4%)
-7.2%prior 656

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

In both 2021 and 2022, the highest number of crashes occurred in 25 mph speed zones, with counts of 299 and 309, respectively. A notable shift occurred in the location of fatal crashes; in 2021, one fatal crash was recorded in a 40 mph zone and another in a 55 mph zone. In 2022, neither of the two fatal crashes occurred in a zone with a recorded speed limit according to the provided data.

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: REVERE, MA
  • Total crash records analyzed: 779
  • Total persons involved: 1,850
  • Total vehicles involved: 1,475

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: 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/revere/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

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Revere, MA Crash Report — 2022 | ThatCarHitMe.com