Monthly Traffic Safety Analysis

23 CRASHES IN
LITTLETON, MA
MARCH 2023

All metrics benchmarked againstMarch 2022

Total crashes in Littleton increased by 21.1% year-over-year, rising from 19 in March 2022 to 23 in March 2023. This period also saw a substantial increase in total injuries, which rose from 1 to 11. DUI-related crashes also increased from 1 to 3, and speeding-related crashes increased from 2 to 6.

23

21.1%was 19

Total Crash Events

0

Persons Killed

11

1000.0%was 1

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 · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates an increase in crash activity year-over-year in Littleton. Total crashes rose by 4, representing a 21.1% increase from 19 crashes in March 2022 to 23 crashes in March 2023. Concurrently, total injuries saw a significant rise from 1 to 11.

1

Hit-and-Run Crashes — March 2023

4.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

11

Motorists Injured

Prior: 11000.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Thursday in both periods, increasing slightly from 5 crashes in March 2022 to 6 crashes in March 2023. However, the peak hour shifted from 5 p.m. with 5 crashes in the prior period to 2 p.m. with 3 crashes in the current period. Notably, Sunday crashes increased from 0 in March 2022 to 5 in March 2023, while Monday crashes decreased from 2 to 0.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at 0 in both March 2022 and March 2023. Total injuries, however, increased substantially from 1 in the prior period to 11 in the current period. Minor injuries increased from 1 crash (5.3% of total crashes) to 4 crashes (17.4% of total crashes), and possible injuries, which were absent in the prior period, accounted for 2 crashes (8.7% of total crashes) in the current period.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes17.4%
300.0%prior 1
Possible Injury2possible injury crashes8.7%
No Injury17no injury crashes73.9%
-5.6%prior 18

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Driving too fast for conditions' saw the largest increase, rising from 1 crash in March 2022 to 6 crashes in March 2023, a 500% increase in count. 'No improper driving' decreased from 7 crashes to 6 crashes, while its share of total crashes decreased from 36.8% to 26.1%. 'Followed too closely' also decreased from 5 crashes to 3 crashes, with its share dropping from 26.3% to 13%.

Officer-Reported Primary Contributing Cause

No improper driving6 (26.1%)-14.3%prior 7
Driving too fast for conditions6 (26.1%)
Other improper action3 (13%)
Followed too closely3 (13%)-40.0%prior 5
Failed to yield right of way1 (4.3%)
Inattention1 (4.3%)
Failure to keep in proper lane or running off road1 (4.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (4.3%)
Fatigued/asleep1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 15 in March 2022 to 14 in March 2023, despite an overall increase in total crashes. There was an increase in crashes during adverse weather, with snow conditions accounting for 3 crashes in March 2023 compared to none in the prior period, and wet road surface crashes increasing from 2 to 4. Crashes during daylight hours increased from 11 to 16, while crashes during dusk decreased from 2 to 1.

Weather

Clear14 (60.9%)
-6.7%prior 15
Snow3 (13.0%)
Cloudy2 (8.7%)
Rain2 (8.7%)
Rain/Cloudy1 (4.3%)
Sleet, hail (freezing rain or drizzle)1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash

Lighting

Daylight16 (69.6%)
45.5%prior 11
Dark - lighted roadway4 (17.4%)
Dark - roadway not lighted2 (8.7%)
Dusk1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field

Road Surface

Dry16 (69.6%)
0.0%prior 16
Wet4 (17.4%)
Snow3 (13.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (40 vehicles)

1
TOYOTA7 (17.5%)
2
HONDA4 (10%)
3
NISSAN4 (10%)
4
CHEVROLET3 (7.5%)
5
FREIGHTLINER3 (7.5%)
6
HYUNDAI2 (5%)
7
MAZDA2 (5%)
8
SUBARU2 (5%)
9
DODGE2 (5%)
10
KIA2 (5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records

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

Sex Distribution (41 persons with recorded sex)

Male23 (56.1%)
0.0%prior 23
Female18 (43.9%)
63.6%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone increased from 2 in March 2022 to 5 in March 2023. The 35 mph zone, which had no crashes in the prior period, recorded 3 crashes in the current period. Conversely, crashes in the 45 mph zone decreased from 3 to 1. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-03-01 through 2023-03-31 (31 days)
  • Geographic scope: LITTLETON, MA
  • Total crash records analyzed: 23
  • Total persons involved: 50
  • Total vehicles involved: 40

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). "LITTLETON, MA Crash Intelligence Report: March 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/littleton/march-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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Littleton, MA Crash Report — March 2023 | ThatCarHitMe.com