Monthly Traffic Safety Analysis

509 CRASHES IN
BOSTON, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

Total crashes in Boston decreased from 524 in December 2023 to 509 in December 2024, representing a 2.9% reduction year-over-year. Despite this overall decrease, pedestrian fatalities increased by 200%, rising from 1 to 3 during the same period.

509

-2.9%was 524

Total Crash Events

4

Persons Killed

183

-2.7%was 188

Persons Injured

66

1.5%was 65

Hit-and-Run Crashes

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 19 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a slight decrease in crash incidents, with total crashes falling by 15 from 524 to 509. This represents a 2.9% reduction year-over-year. Total fatalities remained stable at 4, while total injuries saw a minor decrease from 188 to 183.

66

Hit-and-Run Crashes — December 2024

1.5% vs prior (65)

The number of hit-and-run crashes slightly increased from 65 in December 2023 to 66 in December 2024. The hit-and-run rate also saw a minor increase from 12.4% to 13% of all crashes year-over-year, indicating a slight upward trend in the proportion of these incidents.

Vulnerable Road User Casualties

3

Pedestrians Killed

Prior: 1200.0%

1

Cyclists Killed

Prior: 10.0%

0

Motorists Killed

Prior: 2-100.0%

0

Other Killed

Prior: 00.0%

16

Pedestrians Injured

Prior: 1233.3%

4

Cyclists Injured

Prior: 333.3%

160

Motorists Injured

Prior: 171-6.4%

3

Other Injured

Prior: 250.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Friday in December 2023, with 98 crashes, to Thursday in December 2024, with 89 crashes. The peak hour remained consistent at 5 PM in both periods, with 37 crashes in December 2023 and 38 crashes in December 2024. Overall crash counts decreased across most days of the week, with Monday and Friday showing the largest reductions of 4 and 23 crashes respectively.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of fatal crashes remained constant at 4 in both periods, leading to a slight increase in the fatal crash rate from 0.76% to 0.79% due to fewer total crashes. Serious injuries (Severity A) increased from 9 to 10, while minor injuries (Severity B) increased from 77 to 84. Possible injuries (Severity C) also increased slightly from 49 to 51.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.8%
0.0%prior 4
Serious Injury10serious injury crashes2%
11.1%prior 9
Minor Injury84minor injury crashes16.5%
9.1%prior 77
Possible Injury51possible injury crashes10%
4.1%prior 49
No Injury341no injury crashes67%
-5.5%prior 361

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw changes in count year-over-year. 'No improper driving' decreased by 18 crashes, from 96 to 78, a 18.8% reduction in count. 'Failed to yield right of way' decreased by 11 crashes (from 51 to 40), a 21.6% reduction in count. Conversely, 'Driving too fast for conditions' increased by 3 crashes (from 18 to 21), a 16.7% increase in count, and 'Other improper action' increased by 3 crashes (from 20 to 23), a 15% increase in count.

Officer-Reported Primary Contributing Cause

No improper driving78 (15.3%)-18.8%prior 96
Followed too closely57 (11.2%)-9.5%prior 63
Failed to yield right of way40 (7.9%)-21.6%prior 51
Other improper action23 (4.5%)15.0%prior 20
Failure to keep in proper lane or running off road22 (4.3%)10.0%prior 20
Driving too fast for conditions21 (4.1%)16.7%prior 18
Disregarded traffic signs, signals, road markings20 (3.9%)-31.0%prior 29
Inattention16 (3.1%)-20.0%prior 20
Exceeded authorized speed limit14 (2.8%)-26.3%prior 19
Made an improper turn9 (1.8%)-40.0%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions, including 'Clear' and 'Clear/Clear' categories, decreased from 326 (62.2% share) in December 2023 to 308 (60.5% share) in December 2024. Crashes during rainy conditions (including 'Rain', 'Rain/Rain', 'Rain/Cloudy', 'Cloudy/Rain', 'Rain/Snow', 'Snow/Rain', 'Rain/Fog, smog, smoke', 'Rain/Severe crosswinds') decreased from 109 (20.8% share) to 70 (13.8% share). A notable increase was observed in crashes during snowy or icy road conditions, which rose from 3 (0.6% share) to 34 (6.7% share) year-over-year.

Weather

Clear211 (45.3%)
-35.3%prior 326
Clear/Clear97 (20.8%)
Rain48 (10.3%)
-46.1%prior 89
Cloudy28 (6.0%)
-20.0%prior 35
Snow15 (3.2%)
Rain/Rain14 (3.0%)
Cloudy/Cloudy10 (2.1%)
Other7 (1.5%)
Snow/Snow5 (1.1%)
Rain/Cloudy5 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Dark - lighted roadway221 (46.6%)
-12.0%prior 251
Daylight214 (45.1%)
13.8%prior 188
Dusk15 (3.2%)
36.4%prior 11
Dark - unknown roadway lighting8 (1.7%)
33.3%prior 6
Dark - roadway not lighted7 (1.5%)
-22.2%prior 9
Dawn7 (1.5%)
-50.0%prior 14
Other2 (0.4%)
-71.4%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry279 (67.2%)
-16.2%prior 333
Wet101 (24.3%)
-14.4%prior 118
Snow19 (4.6%)
Ice11 (2.7%)
Slush4 (1.0%)
Other1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes decreased from 1253 to 1181. Toyota remained the most frequently involved vehicle make with 202 vehicles in both periods, while Honda saw a decrease from 147 to 127 vehicles. The age group 16-20 years old experienced a decrease in representation from 66 persons (5.3% share) to 43 persons (3.6% share), and the 21-25 age group also decreased from 175 persons (14.0% share) to 139 persons (11.8% share). Conversely, the 35-44 age group saw an increase in representation from 200 persons (16.0% share) to 207 persons (17.5% share).

Top Vehicle Makes (997 vehicles)

1
TOYOTA202 (20.3%)
0.0%prior 202
2
HONDA127 (12.7%)
-13.6%prior 147
3
FORD106 (10.6%)
2.9%prior 103
4
NISSAN65 (6.5%)
-5.8%prior 69
5
JEEP43 (4.3%)
10.3%prior 39
6
SUBARU34 (3.4%)
21.4%prior 28
7
HYUNDAI34 (3.4%)
13.3%prior 30
8
CHEVROLET33 (3.3%)
-37.7%prior 53
9
VOLKSWAGEN20 (2%)
0.0%prior 20
10
KIA19 (1.9%)
-13.6%prior 22

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (989 persons with recorded sex)

Male651 (65.8%)
-0.8%prior 656
Female338 (34.2%)
-16.3%prior 404

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph speed zones decreased from 188 to 152, a 19.15% reduction in count. Despite this decrease in crash count, the fatal rate within 25 mph zones increased from 2.128% in December 2023 to 2.632% in December 2024. Crashes in 30 mph zones decreased by 16 (from 40 to 24), a 40% reduction in count, and crashes in 35 mph zones decreased by 14 (from 54 to 40), a 25.9% reduction in count.

Fatal crashes by zone: 25 mph: 4 of 152 (2.632%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 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: 2024-12-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-12-01 through 2024-12-31 (31 days)
  • Geographic scope: BOSTON, MA
  • Total crash records analyzed: 509
  • Total persons involved: 1,181
  • Total vehicles involved: 997

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: December 2024." Published June 21, 2026. Reporting period: 2024-12-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/boston/december-2024-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 — December 2024 | ThatCarHitMe.com