Monthly Traffic Safety Analysis

464 CRASHES IN
BOSTON, MA
NOVEMBER 2024

All metrics benchmarked againstNovember 2023

In November 2024, Boston experienced 464 total crashes, a decrease of 15.48% from the 549 crashes recorded in November 2023. While overall crashes declined, fatal crashes increased by 100%, rising from 1 fatal crash in the prior period to 2 fatal crashes in the current period. Total injuries also saw an increase of 6.67%, from 180 to 192.

464

-15.5%was 549

Total Crash Events

2

Persons Killed

192

6.7%was 180

Persons Injured

65

-21.7%was 83

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. 29 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Boston showed a declining trend, with total crashes decreasing by 15.48% from 549 in November 2023 to 464 in November 2024. Despite this reduction in total crashes, the number of fatal crashes doubled, increasing from 1 to 2, and total injuries rose by 6.67% year-over-year.

65

Hit-and-Run Crashes — November 2024

-21.7% vs prior (83)

The number of hit-and-run crashes decreased by 18 incidents, falling from 83 in November 2023 to 65 in November 2024. This represents a 21.69% reduction in hit-and-run crashes. The hit-and-run rate also decreased from 15.1% in the prior period to 14% in the current period, indicating a downward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 10.0%

1

Other Killed

Prior: 0%

17

Pedestrians Injured

Prior: 166.3%

9

Cyclists Injured

Prior: 3200.0%

163

Motorists Injured

Prior: 1611.2%

3

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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 Wednesday with 103 crashes in November 2023 to Saturday with 91 crashes in November 2024. The peak hour for crashes also changed, moving from 5 p.m. with 36 crashes in the prior period to 12 p.m. with 34 crashes in the current period. These shifts indicate a change in the temporal distribution of crash occurrences.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes increased by 100%, rising from 1 crash in November 2023 to 2 crashes in November 2024, leading to a fatal crash rate increase from 0.18% to 0.43%. Serious injury crashes saw a significant increase of 185.71%, from 7 crashes in the prior period to 20 crashes in the current period. Conversely, minor injury crashes decreased by 6.38%, from 94 to 88, and no injury crashes decreased by 22.99%, from 374 to 288.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.4%
100.0%prior 1
Serious Injury20serious injury crashes4.3%
185.7%prior 7
Minor Injury88minor injury crashes19%
-6.4%prior 94
Possible Injury37possible injury crashes8%
-15.9%prior 44
No Injury288no injury crashes62.1%
-23.0%prior 374

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw notable changes in crash counts year-over-year. Crashes attributed to 'No improper driving' decreased by 33 incidents, from 109 to 76, a 30.28% reduction. Crashes due to 'Inattention' also significantly decreased by 21 incidents, from 34 to 13, a 61.76% change. Conversely, 'Driving too fast for conditions' increased by 8 incidents, from 12 to 20, representing a 66.67% rise, and 'Failure to keep in proper lane or running off road' increased by 5 incidents, from 22 to 27, a 22.73% change.

Officer-Reported Primary Contributing Cause

No improper driving76 (16.4%)-30.3%prior 109
Followed too closely53 (11.4%)-17.2%prior 64
Failed to yield right of way35 (7.5%)-14.6%prior 41
Failure to keep in proper lane or running off road27 (5.8%)22.7%prior 22
Disregarded traffic signs, signals, road markings23 (5%)-30.3%prior 33
Driving too fast for conditions20 (4.3%)66.7%prior 12
Made an improper turn15 (3.2%)-16.7%prior 18
Inattention13 (2.8%)-61.8%prior 34
Other improper action11 (2.4%)-50.0%prior 22
Exceeded authorized speed limit9 (1.9%)-43.8%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased by 82 incidents, from 416 in November 2023 to 334 in November 2024. Crashes on 'Dry' road surfaces also saw a decrease of 93 incidents, falling from 416 to 323. In contrast, crashes during 'Rain' conditions increased by 16 incidents, from 54 to 70, a 29.6% change, and crashes on 'Wet' road surfaces increased by 5 incidents, from 63 to 68.

Weather

Clear223 (52.1%)
-46.4%prior 416
Clear/Clear111 (25.9%)
Rain45 (10.5%)
4.7%prior 43
Cloudy15 (3.5%)
-46.4%prior 28
Rain/Rain13 (3.0%)
Rain/Cloudy9 (2.1%)
Cloudy/Rain3 (0.7%)
-72.7%prior 11
Other3 (0.7%)
Cloudy/Cloudy2 (0.5%)
Unknown/Unknown1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Weather condition at time of crash

Lighting

Daylight197 (45.6%)
-16.2%prior 235
Dark - lighted roadway190 (44.0%)
-19.8%prior 237
Dusk14 (3.2%)
27.3%prior 11
Dawn11 (2.5%)
-26.7%prior 15
Other10 (2.3%)
Dark - roadway not lighted8 (1.9%)
-27.3%prior 11
Dark - unknown roadway lighting2 (0.5%)
-66.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Lighting condition field

Road Surface

Dry323 (82.4%)
-22.4%prior 416
Wet68 (17.3%)
7.9%prior 63
Water (standing, moving)1 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased by 16.35%, from 1095 in November 2023 to 916 in November 2024. The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—all saw decreases in their involvement, with Toyota down by 51 vehicles, Honda by 16, and Ford by 17. The age group 26-34 saw a decrease of 71 persons involved in crashes, from 293 to 222, while the 65+ age group also saw a decrease of 18 persons, from 84 to 66.

Top Vehicle Makes (916 vehicles)

1
TOYOTA160 (17.5%)
-24.2%prior 211
2
HONDA137 (15%)
-10.5%prior 153
3
FORD94 (10.3%)
-15.3%prior 111
4
NISSAN54 (5.9%)
-14.3%prior 63
5
CHEVROLET48 (5.2%)
-12.7%prior 55
6
HYUNDAI40 (4.4%)
-7.0%prior 43
7
JEEP35 (3.8%)
-18.6%prior 43
8
SUBARU33 (3.6%)
3.1%prior 32
9
KIA23 (2.5%)
4.5%prior 22
10
LEXUS23 (2.5%)
-8.0%prior 25

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Vehicle unit records

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

Sex Distribution (897 persons with recorded sex)

Male578 (64.4%)
-17.4%prior 700
Female318 (35.5%)
-20.9%prior 402
X / Unspecified1 (0.1%)
0.0%prior 1

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph speed zones decreased by 55 incidents, from 204 in November 2023 to 149 in November 2024. However, the number of fatal crashes in 25 mph zones increased from 1 to 2, raising the fatal crash rate in this zone from 0.49% to 1.342%. Crashes in 55 mph zones decreased by 27 incidents, falling from 61 to 34.

Fatal crashes by zone: 25 mph: 2 of 149 (1.342%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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: 2024-11-01 through 2024-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-11-01 through 2024-11-30 (30 days)
  • Geographic scope: BOSTON, MA
  • Total crash records analyzed: 464
  • Total persons involved: 1,097
  • Total vehicles involved: 916

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: November 2024." Published June 21, 2026. Reporting period: 2024-11-01 to 2024-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/boston/november-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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