Monthly Traffic Safety Analysis

479 CRASHES IN
BOSTON, MA
JANUARY 2022

All metrics benchmarked againstJanuary 2021

Total crashes in January 2022 were 479, a substantial increase from 247 crashes in January 2021. This represents a 93.9% rise year-over-year. The most notable shift was the significant increase in overall crash volume and associated injuries, with total injuries rising from 66 to 121.

479

93.9%was 247

Total Crash Events

1

Persons Killed

121

83.3%was 66

Persons Injured

57

147.8%was 23

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. 75 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 2022-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash activity in January 2022 significantly increased compared to January 2021, with total crashes rising by 93.9% from 247 to 479. Total injuries also saw a substantial increase of 83.3%, from 66 to 121. Fatalities remained stable at one in both periods.

57

Hit-and-Run Crashes — January 2022

147.8% vs prior (23)

Hit-and-run crashes increased significantly year-over-year, rising from 23 incidents in January 2021 to 57 incidents in January 2022, a 147.8% increase. Concurrently, the hit-and-run rate also increased from 9.3% to 11.9% of all crashes. This indicates an upward trend in hit-and-run incidents.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

0

Other Killed

Prior: 00.0%

4

Pedestrians Injured

Prior: 1300.0%

3

Cyclists Injured

Prior: 1200.0%

109

Motorists Injured

Prior: 6470.3%

5

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Saturday in both periods, with 79 crashes in January 2022 compared to 50 in January 2021. However, the peak hour for crashes shifted from 3 p.m. in January 2021 (21 crashes) to 1 p.m. in January 2022 (33 crashes). This indicates a shift in the timing of peak crash occurrences.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The total number of fatal crashes remained stable at one in both periods, but the fatal crash rate decreased from 0.4% to 0.2% due to the overall increase in crash volume. The proportion of crashes resulting in any injury (A, B, or C severity) slightly decreased from 26.7% in January 2021 to 25.3% in January 2022. While the count of serious injuries increased from 3 to 4, their proportion relative to total crashes decreased from 1.2% to 0.8%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.2%
0.0%prior 1
Serious Injury4serious injury crashes0.8%
33.3%prior 3
Minor Injury58minor injury crashes12.1%
100.0%prior 29
Possible Injury28possible injury crashes5.8%
154.5%prior 11
No Injury313no injury crashes65.3%
108.7%prior 150

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Most severe injury per crash record

Top Contributing Factors

No improper driving remained the leading contributing factor, with its count increasing from 47 to 90, a 91.5% rise. Followed too closely also maintained its second-place ranking, with its count increasing from 45 to 53, a 17.8% increase. Notably, Disregarded traffic signs, signals, road markings saw a substantial count increase from 7 to 20, an 185.7% change, moving from 11th to 4th in ranking.

Officer-Reported Primary Contributing Cause

No improper driving90 (18.8%)91.5%prior 47
Followed too closely53 (11.1%)17.8%prior 45
Exceeded authorized speed limit24 (5%)84.6%prior 13
Disregarded traffic signs, signals, road markings20 (4.2%)185.7%prior 7
Failed to yield right of way20 (4.2%)-13.0%prior 23
Other improper action20 (4.2%)122.2%prior 9
Driving too fast for conditions14 (2.9%)0.0%prior 14
Failure to keep in proper lane or running off road13 (2.7%)18.2%prior 11
Inattention13 (2.7%)62.5%prior 8
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner9 (1.9%)-10.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring on adverse road surfaces significantly increased year-over-year; for example, crashes on wet roads rose from 35 to 77 (a 120% increase), and on snowy roads from 12 to 43 (a 258.3% increase). Crashes on icy roads saw an 800% increase, from 2 to 18. While the proportion of crashes in clear weather increased, the counts for adverse weather and road conditions generally rose.

Weather

Clear313 (69.7%)
122.0%prior 141
Snow41 (9.1%)
241.7%prior 12
Cloudy39 (8.7%)
8.3%prior 36
Rain27 (6.0%)
68.8%prior 16
Cloudy/Rain10 (2.2%)
Cloudy/Snow3 (0.7%)
Sleet, hail (freezing rain or drizzle)3 (0.7%)
Other2 (0.4%)
Blowing sand, snow2 (0.4%)
Fog, smog, smoke2 (0.4%)

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

Lighting

Daylight221 (47.5%)
88.9%prior 117
Dark - lighted roadway209 (44.9%)
86.6%prior 112
Dawn22 (4.7%)
175.0%prior 8
Dark - roadway not lighted6 (1.3%)
Dark - unknown roadway lighting4 (0.9%)
Dusk3 (0.6%)

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

Road Surface

Dry316 (68.8%)
65.4%prior 191
Wet77 (16.8%)
120.0%prior 35
Snow43 (9.4%)
258.3%prior 12
Ice18 (3.9%)
Sand, mud, dirt, oil, gravel4 (0.9%)
Slush1 (0.2%)

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

Vehicles & Demographics

The total number of vehicles involved in crashes nearly doubled, increasing from 477 in January 2021 to 910 in January 2022. The top three vehicle makes involved remained Toyota, Honda, and Ford, with all showing significant increases in counts. The 26-34 age group saw the largest numerical increase in persons involved, rising from 130 to 247.

Top Vehicle Makes (910 vehicles)

1
TOYOTA157 (17.3%)
80.5%prior 87
2
HONDA117 (12.9%)
69.6%prior 69
3
FORD104 (11.4%)
112.2%prior 49
4
NISSAN73 (8%)
65.9%prior 44
5
CHEVROLET50 (5.5%)
72.4%prior 29
6
JEEP46 (5.1%)
187.5%prior 16
7
HYUNDAI29 (3.2%)
163.6%prior 11
8
SUBARU29 (3.2%)
141.7%prior 12
9
ACURA27 (3%)
237.5%prior 8
10
KIA26 (2.9%)
100.0%prior 13

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

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

Sex Distribution (849 persons with recorded sex)

Male536 (63.1%)
69.6%prior 316
Female313 (36.9%)
83.0%prior 171

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone increased substantially from 40 to 163, a 307.5% rise. The single fatal crash in January 2022 occurred in a 55 mph zone, which had no fatalities in the prior period, while the fatal crash in January 2021 occurred in a 25 mph zone. Overall, crashes increased across most speed limit categories.

Fatal crashes by zone: 55 mph: 1 of 67 (1.493%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · 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 2022-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-01-31 (31 days)
  • Geographic scope: BOSTON, MA
  • Total crash records analyzed: 479
  • Total persons involved: 1,142
  • Total vehicles involved: 910

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). "BOSTON, MA Crash Intelligence Report: January 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/boston/january-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

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Boston, MA Crash Report — January 2022 | ThatCarHitMe.com