Monthly Traffic Safety Analysis

177 CRASHES IN
LAWRENCE, MA
MARCH 2023

All metrics benchmarked againstMarch 2022

Total crashes in LAWRENCE, MA for March 2023 increased by 18.8% year-over-year, rising from 149 crashes in March 2022 to 177 crashes. Despite this increase in overall incidents, the number of serious injuries decreased from 5 to 2. This suggests a shift in crash outcomes, with fewer severe injuries reported even as crash frequency rose.

177

18.8%was 149

Total Crash Events

0

Persons Killed

54

-5.3%was 57

Persons Injured

4

100.0%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 · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates an increase in crashes year-over-year, with total crashes rising by 18.8% from 149 in March 2022 to 177 in March 2023. This represents an increase of 28 crashes. Total injuries decreased by 5.3%, from 57 to 54.

4

Hit-and-Run Crashes — March 2023

100.0% vs prior (2)

Hit-and-run crashes increased by 2, from 2 incidents in March 2022 to 4 incidents in March 2023. This resulted in an increase in the hit-and-run rate, rising from 1.3% of total crashes in the prior period to 2.3% in the current period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

4

Pedestrians Injured

Prior: 40.0%

50

Motorists Injured

Prior: 53-5.7%

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 Monday in both periods, with 28 crashes in March 2022 and 29 crashes in March 2023. The peak hour for crashes shifted from 5 PM in March 2022 to 3 PM in March 2023, both recording 19 crashes. This indicates a slight shift in the most crash-prone time of day.

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

There were no fatal crashes or fatalities reported in either March 2022 or March 2023. Serious injuries (Severity A) decreased from 5 in March 2022 to 2 in March 2023. Minor injuries (Severity B) increased from 21 in March 2022 to 27 in March 2023, while possible injuries (Severity C) remained at 8 for both periods.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes1.1%
-60.0%prior 5
Minor Injury27minor injury crashes15.3%
28.6%prior 21
Possible Injury8possible injury crashes4.5%
0.0%prior 8
No Injury139no injury crashes78.5%
20.9%prior 115

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 number of crashes attributed to 'No improper driving' increased by 4, from 47 in March 2022 to 51 in March 2023. Crashes due to 'Inattention' decreased significantly by 13, from 24 to 11. 'Failed to yield right of way' crashes increased by 5, from 12 to 17, and 'Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway' also increased by 5, from 1 to 6.

Officer-Reported Primary Contributing Cause

No improper driving51 (28.8%)8.5%prior 47
Failed to yield right of way17 (9.6%)41.7%prior 12
Inattention11 (6.2%)-54.2%prior 24
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway6 (3.4%)
Disregarded traffic signs, signals, road markings6 (3.4%)-25.0%prior 8
Other improper action5 (2.8%)0.0%prior 5
Distracted5 (2.8%)
Fatigued/asleep3 (1.7%)
Failure to keep in proper lane or running off road3 (1.7%)
Driving too fast for conditions2 (1.1%)

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 increased by 18, from 91 in March 2022 to 109 in March 2023. Incidents during 'Snow' conditions saw an increase of 9, rising from 4 to 13. Conversely, crashes in 'Rain' conditions decreased by 8, from 12 to 4. Road surface conditions reflected these weather changes, with 'Dry' surface crashes increasing by 13 and 'Snow' surface crashes increasing by 10.

Weather

Clear109 (61.6%)
19.8%prior 91
Cloudy14 (7.9%)
100.0%prior 7
Snow13 (7.3%)
Clear/Clear12 (6.8%)
-36.8%prior 19
Snow/Sleet, hail (freezing rain or drizzle)5 (2.8%)
Rain4 (2.3%)
-66.7%prior 12
Rain/Cloudy3 (1.7%)
Rain/Rain2 (1.1%)
Cloudy/Rain2 (1.1%)
Cloudy/Snow1 (0.6%)

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

Lighting

Daylight125 (71.0%)
23.8%prior 101
Dark - lighted roadway47 (26.7%)
42.4%prior 33
Dark - roadway not lighted2 (1.1%)
Dark - unknown roadway lighting1 (0.6%)
Dawn1 (0.6%)
-80.0%prior 5

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

Road Surface

Dry124 (70.1%)
11.7%prior 111
Wet28 (15.8%)
-12.5%prior 32
Snow13 (7.3%)
Slush7 (4.0%)
Ice4 (2.3%)
Sand, mud, dirt, oil, gravel1 (0.6%)

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

Vehicles & Demographics

The number of persons aged 0-15 involved in crashes increased by 16, from 23 in March 2022 to 39 in March 2023. Conversely, persons aged 16-20 saw a decrease of 10, from 54 to 44. Honda vehicles remained the most frequently involved make, with their count increasing from 92 in March 2022 to 112 in March 2023.

Top Vehicle Makes (355 vehicles)

1
HONDA112 (31.5%)
21.7%prior 92
2
TOYOTA50 (14.1%)
8.7%prior 46
3
FORD27 (7.6%)
0.0%prior 27
4
CHEVROLET22 (6.2%)
57.1%prior 14
5
NISSAN16 (4.5%)
14.3%prior 14
6
ACURA16 (4.5%)
-5.9%prior 17
7
JEEP10 (2.8%)
-16.7%prior 12
8
BMW10 (2.8%)
25.0%prior 8
9
GMC10 (2.8%)
42.9%prior 7
10
HYUNDAI10 (2.8%)

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

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

Sex Distribution (430 persons with recorded sex)

Male248 (57.7%)
18.1%prior 210
Female182 (42.3%)
1.1%prior 180

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 occurring in 30 mph speed zones increased by 23, from 123 in March 2022 to 146 in March 2023. Conversely, crashes in 25 mph speed zones decreased by 13, from 18 to 5. There were no fatal crashes reported 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: LAWRENCE, MA
  • Total crash records analyzed: 177
  • Total persons involved: 565
  • Total vehicles involved: 355

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). "LAWRENCE, 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/lawrence/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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Lawrence, MA Crash Report — March 2023 | ThatCarHitMe.com