Monthly Traffic Safety Analysis

139 CRASHES IN
CAMBRIDGE, MA
FEBRUARY 2024

All metrics benchmarked againstFebruary 2023

Total crashes in February 2024 increased to 139, up from 126 crashes in February 2023, representing a 10.32% rise. The most notable shift was a 300% increase in DUI crashes, rising from 1 in the prior period to 4 in the current period.

139

10.3%was 126

Total Crash Events

0

Persons Killed

42

5.0%was 40

Persons Injured

51

30.8%was 39

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 35 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in February 2024 show an upward trend compared to February 2023. The total number of crashes increased by 13, from 126 to 139, reflecting a 10.32% increase year-over-year.

51

Hit-and-Run Crashes — February 2024

30.8% vs prior (39)

Hit-and-run crashes increased from 39 in February 2023 to 51 in February 2024, a 30.77% increase. The hit-and-run rate also rose from 31% to 36.7% of all crashes, indicating an upward trend in the proportion of crashes involving a hit-and-run.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

7

Pedestrians Injured

Prior: 616.7%

5

Cyclists Injured

Prior: 7-28.6%

28

Motorists Injured

Prior: 2416.7%

2

Other Injured

Prior: 3-33.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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 Thursday in both periods, with crashes on Thursdays increasing from 20 in February 2023 to 30 in February 2024. The peak crash hour shifted from 9a (14 crashes) in the prior period to 3p (15 crashes) in the current period. Additionally, crashes on Wednesday increased from 14 to 21, a 50% rise, while Sunday crashes decreased from 19 to 15, a 21.05% drop.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both February 2023 and February 2024. Total injuries saw a slight increase from 40 to 42. Serious injury crashes remained constant at 2 in both periods, while minor injury crashes decreased from 21 to 18, and possible injury crashes increased from 10 to 16.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes1.4%
0.0%prior 2
Minor Injury18minor injury crashes12.9%
-14.3%prior 21
Possible Injury16possible injury crashes11.5%
60.0%prior 10
No Injury68no injury crashes48.9%
-9.3%prior 75

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Most severe injury per crash record

Top Contributing Factors

The number of crashes where 'No improper driving' was cited decreased from 38 to 23, a 39.47% reduction in count. Conversely, 'Failed to yield right of way' crashes increased significantly from 13 to 22, a 69.23% increase in count. 'Inattention' also saw a 50% reduction in count, decreasing from 8 crashes to 4 crashes.

Officer-Reported Primary Contributing Cause

No improper driving23 (16.5%)-39.5%prior 38
Failed to yield right of way22 (15.8%)69.2%prior 13
Failure to keep in proper lane or running off road8 (5.8%)
Followed too closely6 (4.3%)
Other improper action5 (3.6%)
Made an improper turn5 (3.6%)
Inattention4 (2.9%)-50.0%prior 8
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (2.2%)
Disregarded traffic signs, signals, road markings2 (1.4%)
Glare2 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 66 to 89, while those in 'Dark - lighted roadway' conditions rose from 34 to 43, a 26.47% increase. Crashes on 'Dry' road surfaces increased from 84 to 106, whereas crashes on 'Wet' surfaces decreased from 15 to 11. Notably, crashes in 'Snow' and 'Ice' conditions, present in the prior period, were significantly reduced or absent in the current period.

Weather

Clear89 (68.5%)
34.8%prior 66
Clear/Clear16 (12.3%)
100.0%prior 8
Cloudy14 (10.8%)
-12.5%prior 16
Unknown/Unknown5 (3.8%)
0.0%prior 5
Rain3 (2.3%)
Snow1 (0.8%)
Unknown/Clear1 (0.8%)
Clear/Unknown1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Weather condition at time of crash

Lighting

Daylight75 (60.5%)
-1.3%prior 76
Dark - lighted roadway43 (34.7%)
26.5%prior 34
Dawn4 (3.2%)
Dark - roadway not lighted1 (0.8%)
Dusk1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Lighting condition field

Road Surface

Dry106 (90.6%)
26.2%prior 84
Wet11 (9.4%)
-26.7%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Road surface condition field

Vehicles & Demographics

The number of Toyota vehicles involved in crashes increased from 36 to 51, and Honda vehicles increased from 33 to 36. In terms of persons involved, the 16-20 age group saw an increase from 10 to 17, while the 35-44 age group decreased from 49 to 36. The 55-64 age group increased from 18 to 24 persons involved.

Top Vehicle Makes (244 vehicles)

1
TOYOTA51 (20.9%)
41.7%prior 36
2
HONDA36 (14.8%)
9.1%prior 33
3
SUBARU16 (6.6%)
33.3%prior 12
4
FORD15 (6.1%)
-48.3%prior 29
5
NISSAN11 (4.5%)
22.2%prior 9
6
HYUNDAI8 (3.3%)
33.3%prior 6
7
AUDI7 (2.9%)
0.0%prior 7
8
CHEVROLET7 (2.9%)
-30.0%prior 10
9
MERCEDES-BENZ7 (2.9%)
10
BMW6 (2.5%)
20.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Vehicle unit records

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

Sex Distribution (214 persons with recorded sex)

Male116 (54.2%)
-20.5%prior 146
Female98 (45.8%)
27.3%prior 77

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone increased from 82 to 107, representing a 30.49% rise. Conversely, crashes in the 20 mph zone decreased from 23 to 17, a 26.09% drop. There were no fatal crashes reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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: 2024-02-01 through 2024-02-29
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-02-01 through 2024-02-29 (29 days)
  • Geographic scope: CAMBRIDGE, MA
  • Total crash records analyzed: 139
  • Total persons involved: 297
  • Total vehicles involved: 244

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). "CAMBRIDGE, MA Crash Intelligence Report: February 2024." Published June 21, 2026. Reporting period: 2024-02-01 to 2024-02-29. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/cambridge/february-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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Cambridge, MA Crash Report — February 2024 | ThatCarHitMe.com