Yearly Traffic Safety Analysis

888 CRASHES IN
CHELSEA, MA
2022

All metrics benchmarked against2021

In 2022, Chelsea recorded 888 total vehicle crashes, a 16.2% increase from the 764 crashes reported in 2021. The number of fatalities doubled from one in 2021 to two in 2022, and total injuries rose by 17.4% from 282 to 331. The most notable year-over-year shift was the overall increase in crash volume, with a corresponding rise in nearly all severity categories.

888

16.2%was 764

Total Crash Events

2

100.0%was 1

Persons Killed

331

17.4%was 282

Persons Injured

32

14.3%was 28

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. 61 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

Crash data for Chelsea indicates a rising trend in collisions year-over-year. Total crashes increased from 764 in 2021 to 888 in 2022, representing a 16.2% rise. This upward trend was also reflected in the number of people injured, which grew by 17.4% from 282 to 331, and fatalities, which increased from one to two.

32

Hit-and-Run Crashes — 2022

14.3% vs prior (28)

The number of hit-and-run crashes increased from 28 in 2021 to 32 in 2022. However, due to the larger increase in overall crashes, the hit-and-run rate as a percentage of all incidents saw a slight decrease. The rate trended down from 3.7% in 2021 to 3.6% in 2022.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Cyclists Killed

Prior: 00.0%

2

Motorists Killed

Prior: 0%

0

Other Killed

Prior: 00.0%

39

Pedestrians Injured

Prior: 2650.0%

9

Cyclists Injured

Prior: 728.6%

282

Motorists Injured

Prior: 24913.3%

1

Other Injured

Prior: 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

Temporal crash patterns showed a shift in the most common day for incidents. In 2022, Monday was the peak day with 147 crashes, a change from 2021 when Friday was the peak day with 123 crashes. The peak hour for collisions remained consistent at 4 p.m. in both periods, though the number of crashes during that hour increased from 57 in 2021 to 63 in 2022.

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 of crashes worsened slightly between the two periods. The number of fatal crashes doubled from one in 2021 to two in 2022, and the fatal crash rate increased from 0.13% to 0.23%. The count of serious injury crashes also rose from 21 to 24, though their share of total crashes remained stable at 2.7%. While the share of minor injury crashes decreased from 14.3% to 12.7%, the proportion of possible injury crashes increased from 9.8% to 10.4%.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.2%
100.0%prior 1
Serious Injury24serious injury crashes2.7%
14.3%prior 21
Minor Injury113minor injury crashes12.7%
3.7%prior 109
Possible Injury92possible injury crashes10.4%
22.7%prior 75
No Injury596no injury crashes67.1%
16.9%prior 510

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

While "No improper driving" remained the most cited factor in both years, its count increased by 35.8% from 215 in 2021 to 292 in 2022. The rankings of other top factors shifted; crashes attributed to "Inattention" decreased in count by 41.2% from 34 to 20, and those involving "Failed to yield right of way" dropped by 22.6% from 31 to 24. The count for crashes involving an "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" was unchanged at 24 for both periods.

Officer-Reported Primary Contributing Cause

No improper driving292 (32.9%)35.8%prior 215
Failed to yield right of way24 (2.7%)-22.6%prior 31
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner24 (2.7%)0.0%prior 24
Other improper action22 (2.5%)0.0%prior 22
Inattention20 (2.3%)-41.2%prior 34
Followed too closely18 (2%)-14.3%prior 21
Failure to keep in proper lane or running off road14 (1.6%)40.0%prior 10
Disregarded traffic signs, signals, road markings13 (1.5%)-7.1%prior 14
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway12 (1.4%)0.0%prior 12
Distracted11 (1.2%)-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

Crash conditions remained largely consistent year-over-year, with the majority of incidents in both periods occurring in clear weather and during daylight hours on dry roads. In 2022, 76.2% of crashes happened in clear weather, compared to 76.4% in 2021. Crashes on dry surfaces accounted for 78.4% of the total in 2022, a slight decrease from 81.4% in 2021, while crashes on wet surfaces saw a corresponding proportional increase from 14.1% to 15.3%.

Weather

Clear677 (77.1%)
15.9%prior 584
Rain57 (6.5%)
5.6%prior 54
Cloudy49 (5.6%)
6.5%prior 46
Snow20 (2.3%)
81.8%prior 11
Cloudy/Rain14 (1.6%)
7.7%prior 13
Clear/Cloudy13 (1.5%)
8.3%prior 12
Rain/Cloudy11 (1.3%)
37.5%prior 8
Clear/Other6 (0.7%)
Snow/Sleet, hail (freezing rain or drizzle)5 (0.6%)
Clear/Unknown5 (0.6%)
-28.6%prior 7

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

Lighting

Daylight524 (59.3%)
13.9%prior 460
Dark - lighted roadway296 (33.5%)
15.6%prior 256
Dawn22 (2.5%)
46.7%prior 15
Dusk19 (2.2%)
5.6%prior 18
Dark - roadway not lighted10 (1.1%)
25.0%prior 8
Dark - unknown roadway lighting7 (0.8%)
40.0%prior 5
Other5 (0.6%)

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

Road Surface

Dry696 (78.7%)
11.9%prior 622
Wet136 (15.4%)
25.9%prior 108
Snow28 (3.2%)
27.3%prior 22
Ice13 (1.5%)
44.4%prior 9
Slush7 (0.8%)
Sand, mud, dirt, oil, gravel4 (0.5%)

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 three vehicle makes involved in crashes—Toyota, Honda, and Ford—were the same in both 2022 and 2021, with the count for each increasing in line with the overall rise in collisions. The age distribution of persons involved in crashes also remained largely stable. The 26-34 age group was the largest cohort in both years, representing 20.6% of persons in 2022 and 20.5% in 2021. There was a minor proportional increase in the 65+ age group, which grew from 5.0% of persons involved in 2021 to 6.0% in 2022.

Top Vehicle Makes (1,734 vehicles)

1
TOYOTA376 (21.7%)
18.6%prior 317
2
HONDA356 (20.5%)
34.3%prior 265
3
FORD180 (10.4%)
15.4%prior 156
4
NISSAN109 (6.3%)
-4.4%prior 114
5
CHEVROLET91 (5.2%)
-7.1%prior 98
6
JEEP79 (4.6%)
33.9%prior 59
7
MERCEDES-BENZ40 (2.3%)
2.6%prior 39
8
ACURA33 (1.9%)
-2.9%prior 34
9
HYUNDAI33 (1.9%)
-13.2%prior 38
10
FRHT30 (1.7%)
150.0%prior 12

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

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

Sex Distribution (1,900 persons with recorded sex)

Male1,240 (65.3%)
21.9%prior 1,017
Female660 (34.7%)
20.9%prior 546

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

Crashes remained concentrated in lower speed zones across both periods, with the 25 mph zone seeing the largest increase in incidents, from 535 in 2021 to 649 in 2022. This zone accounted for 70% of crashes in 2021 and 73% in 2022. One fatal crash occurred in a 25 mph zone in both years. In 2022, a second fatal crash occurred in a 55 mph zone, where 22 total crashes were recorded, compared to zero fatalities among 9 crashes in that zone the prior year.

Fatal crashes by zone: 25 mph: 1 of 649 (0.154%) · 55 mph: 1 of 22 (4.545%)

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: CHELSEA, MA
  • Total crash records analyzed: 888
  • Total persons involved: 2,166
  • Total vehicles involved: 1,734

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). "CHELSEA, 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/chelsea/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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Chelsea, MA Crash Report — 2022 | ThatCarHitMe.com