Monthly Traffic Safety Analysis

15 CRASHES IN
BEDFORD, MA
FEBRUARY 2024

All metrics benchmarked againstFebruary 2023

In February 2024, Bedford experienced 15 crashes, marking a 36.4% increase from the 11 crashes recorded in February 2023. Despite this rise in crash incidents, total injuries decreased by 60%, from 5 injuries in the prior period to 2 in the current period. A notable shift was the 200% increase in crashes attributed to "Failed to yield right of way," which became the leading contributing factor.

15

36.4%was 11

Total Crash Events

0

Persons Killed

2

-60.0%was 5

Persons Injured

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, crash incidents in Bedford showed an upward trend, increasing by 36.4% from 11 crashes in February 2023 to 15 crashes in February 2024. Conversely, the total number of injuries decreased significantly by 60%, from 5 injuries to 2 injuries year-over-year. Fatal crashes remained at zero in both periods.

1

Hit-and-Run Crashes — February 2024

6.7% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 5-60.0%

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 Tuesday in February 2023, with 4 incidents, to Wednesday in February 2024, with 5 incidents. Crashes on Wednesdays saw a substantial increase from 1 to 5, while Tuesday crashes decreased from 4 to 1. The peak hour for crashes shifted from 6 PM to 5 PM, with both periods recording 2 crashes during their respective peak hours.

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

Fatal crashes remained at zero in both February 2023 and February 2024. The total number of injuries decreased by 60%, from 5 injuries in the prior period to 2 injuries in the current period. The proportion of crashes resulting in any injury also decreased, from 27.3% (3 minor injury crashes) in February 2023 to 13.3% (2 possible injury crashes) in February 2024.

Outcome by Severity (Crash Events)

Possible Injury2possible injury crashes13.3%
No Injury13no injury crashes86.7%
62.5%prior 8

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 leading contributing factor shifted from 'Inattention' in February 2023 to 'Failed to yield right of way' in February 2024. Crashes attributed to 'Failed to yield right of way' increased by 200% in count, from 2 to 6 incidents, while 'Inattention' crashes decreased by 66.7% in count, from 3 to 1 incident. Additionally, 'Followed too closely' and 'No improper driving' each accounted for 3 crashes in the current period, representing a 20% share of crashes, neither of which were among the top factors in the prior period.

Officer-Reported Primary Contributing Cause

Failed to yield right of way6 (40%)
Followed too closely3 (20%)
No improper driving3 (20%)
Failure to keep in proper lane or running off road1 (6.7%)
Inattention1 (6.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (6.7%)

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

February 2024 saw a higher concentration of crashes under clear weather conditions, with 14 incidents (12 Clear, 2 Clear/Clear), compared to 4 in February 2023. Crashes under cloudy weather decreased from 5 to 1, and snowy conditions, which accounted for 2 crashes in the prior period, were absent in the current period. Similarly, dry road surface crashes increased from 8 to 13, while snowy road surface crashes, present in the prior period, were not observed in the current period.

Weather

Clear12 (80.0%)
Clear/Clear2 (13.3%)
Cloudy1 (6.7%)
-80.0%prior 5

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

Lighting

Daylight10 (66.7%)
42.9%prior 7
Dark - lighted roadway2 (13.3%)
Dusk2 (13.3%)
Dark - roadway not lighted1 (6.7%)

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

Road Surface

Dry13 (92.9%)
62.5%prior 8
Wet1 (7.1%)

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

Vehicles & Demographics

Top Vehicle Makes (29 vehicles)

1
TOYOTA6 (20.7%)
0.0%prior 6
2
HONDA4 (13.8%)
3
HYUNDAI3 (10.3%)
4
SUBARU3 (10.3%)
5
KIA3 (10.3%)
6
JEEP2 (6.9%)
7
BMW1 (3.4%)
8
VOLKSWAGEN1 (3.4%)
9
CHRYSLER1 (3.4%)
10
FORD1 (3.4%)

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

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

Sex Distribution (41 persons with recorded sex)

Male21 (51.2%)
110.0%prior 10
Female20 (48.8%)
53.8%prior 13

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

There was a notable shift in the distribution of crashes across speed zones year-over-year, with no fatal crashes reported in any zone during either period. Crashes occurring in 25 mph zones increased from zero to 5, and 55 mph zones, which had no crashes in February 2023, recorded 4 crashes in February 2024. Conversely, crashes in 30 mph zones decreased from 4 to 3, and 40 mph zones saw a reduction from 4 crashes to 1.

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: BEDFORD, MA
  • Total crash records analyzed: 15
  • Total persons involved: 44
  • Total vehicles involved: 29

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). "BEDFORD, 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/bedford/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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Bedford, MA Crash Report — February 2024 | ThatCarHitMe.com