Monthly Traffic Safety Analysis

524 CRASHES IN
BOSTON, MA
MARCH 2024

All metrics benchmarked againstMarch 2023

In March 2024, Boston experienced 524 total crashes, an increase of 7.82% compared to the 486 crashes reported in March 2023. While overall crashes rose, total fatalities saw a significant decrease, falling from 3 in March 2023 to 1 in March 2024. Total injuries also declined by 11.47%, from 218 to 193.

524

7.8%was 486

Total Crash Events

1

-66.7%was 3

Persons Killed

193

-11.5%was 218

Persons Injured

73

12.3%was 65

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the number of crashes in Boston increased by 7.82% year-over-year, rising from 486 to 524. Despite this increase in crash volume, total fatalities decreased by 66.67%, and total injuries declined by 11.47% during the same period.

73

Hit-and-Run Crashes — March 2024

12.3% vs prior (65)

Hit-and-run crashes increased from 65 in March 2023 to 73 in March 2024, an increase of 8 incidents. Concurrently, the hit-and-run rate slightly rose from 13.4% of total crashes to 13.9% of total crashes year-over-year. This indicates a minor upward trend in both the number and proportion of hit-and-run incidents.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 2-50.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 1-100.0%

0

Other Killed

Prior: 00.0%

18

Pedestrians Injured

Prior: 1428.6%

6

Cyclists Injured

Prior: 520.0%

165

Motorists Injured

Prior: 198-16.7%

4

Other Injured

Prior: 1300.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · 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 Saturday, with 85 crashes in March 2023, to Sunday, with 105 crashes in March 2024. The peak hour also changed, moving from 4 p.m. (39 crashes) in March 2023 to 1 p.m. (34 crashes) in March 2024, indicating a shift in crash patterns to earlier in the day and to Sundays.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The proportion of fatal crashes decreased from 0.6% (3 crashes) in March 2023 to 0.2% (1 crash) in March 2024. Crashes resulting in serious injuries decreased from 2.3% (11 crashes) to 1.7% (9 crashes), and minor injuries decreased from 16.7% (81 crashes) to 14.1% (74 crashes). Conversely, the share of 'No Injury' crashes increased from 62.3% to 70.4% year-over-year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.2%
-66.7%prior 3
Serious Injury9serious injury crashes1.7%
-18.2%prior 11
Minor Injury74minor injury crashes14.1%
-8.6%prior 81
Possible Injury60possible injury crashes11.5%
-14.3%prior 70
No Injury369no injury crashes70.4%
21.8%prior 303

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor shifted from 'No improper driving' (100 crashes) in March 2023 to 'Followed too closely' (84 crashes) in March 2024, a 50% increase in count for the latter. 'Driving too fast for conditions' saw a substantial increase of 170% in count, rising from 10 crashes to 27 crashes. 'No improper driving' decreased by 25% in count, from 100 to 75 crashes.

Officer-Reported Primary Contributing Cause

Followed too closely84 (16%)50.0%prior 56
No improper driving75 (14.3%)-25.0%prior 100
Failed to yield right of way41 (7.8%)-2.4%prior 42
Inattention29 (5.5%)11.5%prior 26
Driving too fast for conditions27 (5.2%)170.0%prior 10
Disregarded traffic signs, signals, road markings23 (4.4%)15.0%prior 20
Failure to keep in proper lane or running off road23 (4.4%)4.5%prior 22
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner16 (3.1%)77.8%prior 9
Exceeded authorized speed limit16 (3.1%)33.3%prior 12
Other improper action12 (2.3%)20.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in 'Rain' conditions increased from 9.5% (46 crashes) in March 2023 to 19.3% (101 crashes) in March 2024. Similarly, crashes on 'Wet' road surfaces increased from 14.8% (72 crashes) to 22.9% (120 crashes). Meanwhile, crashes in 'Clear' weather conditions decreased from 67.5% (328 crashes) to 56.1% (294 crashes).

Weather

Clear294 (62.7%)
-10.4%prior 328
Rain101 (21.5%)
119.6%prior 46
Cloudy49 (10.4%)
28.9%prior 38
Cloudy/Rain17 (3.6%)
Clear/Cloudy2 (0.4%)
Other1 (0.2%)
Cloudy/Fog, smog, smoke1 (0.2%)
Rain/Cloudy1 (0.2%)
Severe crosswinds/Rain1 (0.2%)
Clear/Clear1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Weather condition at time of crash

Lighting

Daylight256 (53.2%)
2.0%prior 251
Dark - lighted roadway181 (37.6%)
5.2%prior 172
Dawn19 (4.0%)
72.7%prior 11
Dusk9 (1.9%)
-25.0%prior 12
Dark - roadway not lighted8 (1.7%)
Dark - unknown roadway lighting5 (1.0%)
0.0%prior 5
Other3 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Lighting condition field

Road Surface

Dry328 (72.4%)
-6.6%prior 351
Wet120 (26.5%)
66.7%prior 72
Ice4 (0.9%)
Sand, mud, dirt, oil, gravel1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes increased from 1,195 to 1,271 year-over-year. The 0-15 age group saw a decrease in involvement from 23 to 11 persons, while the 26-34 age group experienced an increase from 254 to 298 persons. Toyota remained the top vehicle make involved, with its count increasing from 178 to 183, and Ford vehicles involved increased from 83 to 103.

Top Vehicle Makes (1,019 vehicles)

1
TOYOTA183 (18%)
2.8%prior 178
2
HONDA138 (13.5%)
-12.1%prior 157
3
FORD103 (10.1%)
24.1%prior 83
4
NISSAN69 (6.8%)
16.9%prior 59
5
CHEVROLET54 (5.3%)
-12.9%prior 62
6
JEEP50 (4.9%)
-15.3%prior 59
7
SUBARU31 (3%)
34.8%prior 23
8
KIA29 (2.8%)
45.0%prior 20
9
BMW27 (2.6%)
-3.6%prior 28
10
HYUNDAI26 (2.6%)
-21.2%prior 33

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Vehicle unit records

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

Sex Distribution (1,087 persons with recorded sex)

Male701 (64.5%)
12.3%prior 624
Female386 (35.5%)
-4.7%prior 405

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones increased from 169 to 179, with the fatal crash rate in this zone remaining stable at approximately 0.5%. Crashes in 55 mph zones increased from 50 to 66, and crashes in 45 mph zones increased from 59 to 63, with no fatalities reported in 45 mph zones in March 2024 compared to one in March 2023.

Fatal crashes by zone: 25 mph: 1 of 179 (0.559%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · 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: 2024-03-01 through 2024-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-03-01 through 2024-03-31 (31 days)
  • Geographic scope: BOSTON, MA
  • Total crash records analyzed: 524
  • Total persons involved: 1,271
  • Total vehicles involved: 1,019

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: March 2024." Published June 21, 2026. Reporting period: 2024-03-01 to 2024-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/boston/march-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 — March 2024 | ThatCarHitMe.com