Monthly Traffic Safety Analysis

47 CRASHES IN
BILLERICA, MA
MAY 2023

All metrics benchmarked againstMay 2022

In May 2023, Billerica experienced 47 crashes, marking a 14.63% increase from the 41 crashes recorded in May 2022. A significant positive shift was the absence of fatalities in May 2023, compared to one fatality in May 2022.

47

14.6%was 41

Total Crash Events

0

-100.0%was 1

Persons Killed

17

-22.7%was 22

Persons Injured

1

-50.0%was 2

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates an increase in crash incidents in Billerica, with 47 crashes reported in May 2023 compared to 41 in May 2022. This represents a 14.63% rise in total crashes year-over-year.

1

Hit-and-Run Crashes — May 2023

-50.0% vs prior (2)

Hit-and-run crashes decreased from 2 incidents in May 2022 to 1 incident in May 2023. This resulted in the hit-and-run crash rate falling from 4.9% to 2.1% year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

17

Motorists Injured

Prior: 22-22.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Friday, with 10 crashes in May 2023 compared to 7 crashes in May 2022. The peak hour shifted from 2 PM with 6 crashes in May 2022 to 4 PM with 11 crashes in May 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There was a notable decrease in crash severity, with zero fatalities reported in May 2023 compared to one fatality in May 2022. Total injuries also decreased from 22 in May 2022 to 17 in May 2023. While minor injury crashes increased from 4 to 9, possible injury crashes decreased from 9 to 5 year-over-year.

Outcome by Severity (Crash Events)

Minor Injury9minor injury crashes19.1%
125.0%prior 4
Possible Injury5possible injury crashes10.6%
-44.4%prior 9
No Injury32no injury crashes68.1%
18.5%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record

Top Contributing Factors

A significant shift was observed in contributing factors, with 'Inattention' crashes increasing from 3 in May 2022 to 11 in May 2023. Conversely, crashes attributed to 'No improper driving' decreased from 13 to 9. 'Failed to yield right of way' incidents saw a slight decrease from 7 to 6 crashes, while 'Disregarded traffic signs, signals, road markings' increased from 1 to 3 crashes.

Officer-Reported Primary Contributing Cause

Inattention11 (23.4%)
No improper driving9 (19.1%)-30.8%prior 13
Failed to yield right of way6 (12.8%)-14.3%prior 7
Disregarded traffic signs, signals, road markings3 (6.4%)
Failure to keep in proper lane or running off road3 (6.4%)-40.0%prior 5
Followed too closely2 (4.3%)
Other improper action2 (4.3%)
Illness1 (2.1%)
Driving too fast for conditions1 (2.1%)
Distracted1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 34 in May 2022 to 40 in May 2023. Crashes on dry road surfaces also rose from 37 to 42 year-over-year. Incidents during daylight hours increased from 30 to 38, while crashes in dark conditions slightly decreased from 10 to 9.

Weather

Clear34 (72.3%)
47.8%prior 23
Clear/Clear6 (12.8%)
-45.5%prior 11
Cloudy4 (8.5%)
Rain2 (4.3%)
Rain/Cloudy1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash

Lighting

Daylight38 (80.9%)
26.7%prior 30
Dark - lighted roadway7 (14.9%)
-12.5%prior 8
Dark - roadway not lighted2 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field

Road Surface

Dry42 (89.4%)
13.5%prior 37
Wet5 (10.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 76 in May 2022 to 85 in May 2023. A notable shift in age distribution shows a significant increase in persons aged 0-15 (from 5 to 47) and 16-20 (from 8 to 24) involved in crashes. In terms of vehicle makes, Toyota decreased from 17 to 10, while Ford increased from 4 to 11, and Nissan increased from 3 to 8.

Top Vehicle Makes (85 vehicles)

1
HONDA12 (14.1%)
9.1%prior 11
2
FORD11 (12.9%)
3
TOYOTA10 (11.8%)
-41.2%prior 17
4
CHEVROLET9 (10.6%)
0.0%prior 9
5
NISSAN8 (9.4%)
6
KIA3 (3.5%)
7
LEXUS3 (3.5%)
8
BMW3 (3.5%)
9
GMC2 (2.4%)
10
JEEP2 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records

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

Sex Distribution (150 persons with recorded sex)

Male76 (50.7%)
43.4%prior 53
Female74 (49.3%)
89.7%prior 39

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased from 14 in May 2022 to 9 in May 2023, and crashes in 35 mph zones also decreased from 13 to 7. Conversely, crashes in 25 mph zones increased from 1 to 3. There were no fatalities recorded in any speed zone in May 2023, compared to one fatality in a 30 mph zone in May 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-05-01 through 2023-05-31 (31 days)
  • Geographic scope: BILLERICA, MA
  • Total crash records analyzed: 47
  • Total persons involved: 154
  • Total vehicles involved: 85

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). "BILLERICA, MA Crash Intelligence Report: May 2023." Published June 21, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/billerica/may-2023-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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Billerica, MA Crash Report — May 2023 | ThatCarHitMe.com