Monthly Traffic Safety Analysis

37 CRASHES IN
LEXINGTON, MA
FEBRUARY 2024

All metrics benchmarked againstFebruary 2023

LEXINGTON experienced a slight increase in total crashes, rising from 34 in February 2023 to 37 in February 2024, an 8.8% increase. Despite this, total injuries decreased by 45.5%, from 11 to 6. The most notable year-over-year shift was a 300% increase in hit-and-run crashes, which rose from 1 to 4 incidents.

37

8.8%was 34

Total Crash Events

0

Persons Killed

6

-45.5%was 11

Persons Injured

4

300.0%was 1

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.

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, the number of crashes in LEXINGTON showed a slight upward trend, increasing by 8.8% from 34 crashes in February 2023 to 37 crashes in February 2024. Conversely, the total number of injuries decreased significantly by 45.5%, falling from 11 to 6 during the same period.

4

Hit-and-Run Crashes — February 2024

300.0% vs prior (1)

Hit-and-run crashes increased significantly from 1 in February 2023 to 4 in February 2024. This resulted in the hit-and-run rate rising from 2.9% of total crashes in the prior period to 10.8% in the current period, indicating an upward trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

6

Motorists Injured

Prior: 10-40.0%

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 shifted from Friday with 11 crashes in February 2023 to Thursday with 9 crashes in February 2024. The peak hour also changed, moving from 3 PM with 4 crashes in the prior period to 7 AM with 7 crashes in the current period.

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

There were no fatal crashes in either February 2023 or February 2024. Total injuries decreased from 11 in the prior period to 6 in the current period. The proportion of crashes with minor injuries slightly decreased from 8.8% to 8.1%, and serious injury crashes (1) reported in the prior period were not present in the current period.

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes8.1%
0.0%prior 3
Possible Injury1possible injury crashes2.7%
No Injury33no injury crashes89.2%
17.9%prior 28

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 top contributing factor, 'Followed too closely,' saw a significant increase in count from 4 in February 2023 to 10 in February 2024. Conversely, 'No improper driving' decreased from 11 crashes to 4 crashes. 'Driving too fast for conditions' also decreased from 4 crashes to 1 crash year-over-year.

Officer-Reported Primary Contributing Cause

Followed too closely10 (27%)
No improper driving4 (10.8%)-63.6%prior 11
Failure to keep in proper lane or running off road4 (10.8%)
Made an improper turn4 (10.8%)
Inattention4 (10.8%)
Disregarded traffic signs, signals, road markings3 (8.1%)
Failed to yield right of way3 (8.1%)
Exceeded authorized speed limit1 (2.7%)
Emotional1 (2.7%)
Driving too fast for conditions1 (2.7%)

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 18 to 24, while those in 'Snow' conditions decreased from 4 to 1. Crashes on 'Dry' road surfaces increased from 19 to 31, and crashes on 'Ice' surfaces, which accounted for 6 incidents in the prior period, were absent in the current period.

Weather

Clear24 (64.9%)
33.3%prior 18
Cloudy4 (10.8%)
Clear/Clear3 (8.1%)
Cloudy/Rain2 (5.4%)
Clear/Cloudy1 (2.7%)
Rain1 (2.7%)
Snow1 (2.7%)
Unknown/Unknown1 (2.7%)

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

Lighting

Daylight26 (70.3%)
30.0%prior 20
Dark - roadway not lighted6 (16.2%)
20.0%prior 5
Dark - lighted roadway4 (10.8%)
-55.6%prior 9
Dusk1 (2.7%)

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

Road Surface

Dry31 (86.1%)
63.2%prior 19
Wet5 (13.9%)
-16.7%prior 6

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

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 61 to 70. Toyota remained the top make, increasing its count from 10 to 14 vehicles. There was a notable shift in age distribution, with persons aged 45-54 involved in crashes increasing from 11 to 19, while those aged 0-15 decreased from 8 to 2.

Top Vehicle Makes (70 vehicles)

1
TOYOTA14 (20%)
40.0%prior 10
2
VOLKSWAGEN6 (8.6%)
3
FORD6 (8.6%)
0.0%prior 6
4
CHEVROLET5 (7.1%)
5
SUBARU5 (7.1%)
0.0%prior 5
6
LEXUS4 (5.7%)
7
HONDA4 (5.7%)
-50.0%prior 8
8
JEEP2 (2.9%)
9
HYUNDAI2 (2.9%)
10
INTL2 (2.9%)

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

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

Sex Distribution (67 persons with recorded sex)

Male35 (52.2%)
-5.4%prior 37
Female32 (47.8%)
10.3%prior 29

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 30 mph speed zone more than doubled, increasing from 3 in February 2023 to 7 in February 2024. Conversely, crashes in the 55 mph speed zone decreased from 17 to 14. 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: LEXINGTON, MA
  • Total crash records analyzed: 37
  • Total persons involved: 75
  • Total vehicles involved: 70

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). "LEXINGTON, 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/lexington/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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Lexington, MA Crash Report — February 2024 | ThatCarHitMe.com