Monthly Traffic Safety Analysis

164 CRASHES IN
LAWRENCE, MA
OCTOBER 2022

All metrics benchmarked againstOctober 2021

Total crashes in October 2022 were 164, a decrease of 4.1% compared to 171 crashes in October 2021. A notable shift was the absence of crash fatalities in October 2022, down from one fatality in October 2021.

164

-4.1%was 171

Total Crash Events

0

-100.0%was 1

Persons Killed

61

1.7%was 60

Persons Injured

6

-14.3%was 7

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 · 2022-10-01 to 2022-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in October 2022 decreased by 4.1% to 164 incidents, down from 171 crashes in October 2021. This indicates a slight downward trend in the total number of reported crashes year-over-year.

6

Hit-and-Run Crashes — October 2022

-14.3% vs prior (7)

Hit-and-run crashes decreased from 7 incidents in October 2021 to 6 incidents in October 2022. Consequently, the hit-and-run rate slightly decreased from 4.1% in the prior period to 3.7% in the current period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

4

Pedestrians Injured

Prior: 5-20.0%

1

Cyclists Injured

Prior: 0%

56

Motorists Injured

Prior: 551.8%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Sunday in October 2021 (28 crashes) to Saturday in October 2022 (27 crashes). The peak crash hour also changed significantly, moving from 8 AM (15 crashes) in October 2021 to 3 PM (17 crashes) in October 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities decreased from 1 in October 2021 to 0 in October 2022. Total injuries remained relatively stable, with 60 injuries in October 2021 and 61 in October 2022. The proportion of minor injury crashes increased from 15.8% (27 crashes) in the prior period to 20.7% (34 crashes) in the current period, while possible injury crashes decreased from 7% (12 crashes) to 4.3% (7 crashes).

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes1.2%
0.0%prior 2
Minor Injury34minor injury crashes20.7%
25.9%prior 27
Possible Injury7possible injury crashes4.3%
-41.7%prior 12
No Injury121no injury crashes73.8%
-4.0%prior 126

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "Failed to yield right of way" increased by 8, from 12 in October 2021 to 20 in October 2022. "Distracted" driving crashes also saw an increase of 6, rising from 3 to 9 incidents. Conversely, "No improper driving" decreased by 8 crashes, from 40 in the prior period to 32 in the current period.

Officer-Reported Primary Contributing Cause

No improper driving32 (19.5%)-20.0%prior 40
Failed to yield right of way20 (12.2%)66.7%prior 12
Inattention15 (9.1%)-6.3%prior 16
Distracted9 (5.5%)
Followed too closely8 (4.9%)-27.3%prior 11
Disregarded traffic signs, signals, road markings4 (2.4%)-42.9%prior 7
Other improper action4 (2.4%)-42.9%prior 7
Over-correcting/over-steering3 (1.8%)
Visibility obstructed3 (1.8%)
Failure to keep in proper lane or running off road3 (1.8%)-50.0%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in rainy conditions decreased from 34 in October 2021 to 21 in October 2022. The number of crashes on wet road surfaces also saw a decrease, falling from 39 to 30. There was a slight increase in crashes during "Dark - lighted roadway" conditions, rising from 43 to 45.

Weather

Clear103 (63.2%)
7.3%prior 96
Clear/Clear16 (9.8%)
-38.5%prior 26
Cloudy15 (9.2%)
50.0%prior 10
Rain14 (8.6%)
-17.6%prior 17
Rain/Cloudy4 (2.5%)
Cloudy/Rain3 (1.8%)
-57.1%prior 7
Sleet, hail (freezing rain or drizzle)3 (1.8%)
Fog, smog, smoke2 (1.2%)
Unknown/Clear1 (0.6%)
Cloudy/Cloudy1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Weather condition at time of crash

Lighting

Daylight111 (67.7%)
-0.9%prior 112
Dark - lighted roadway45 (27.4%)
4.7%prior 43
Dark - roadway not lighted7 (4.3%)
16.7%prior 6
Dawn1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Lighting condition field

Road Surface

Dry133 (81.6%)
1.5%prior 131
Wet30 (18.4%)
-23.1%prior 39

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 345 in October 2021 to 332 in October 2022. Honda vehicles involved in crashes increased by 20, from 90 to 110, while Toyota vehicles decreased by 8, from 44 to 36. The 26-34 age group saw a slight decrease in persons involved, from 84 to 80.

Top Vehicle Makes (332 vehicles)

1
HONDA110 (33.1%)
22.2%prior 90
2
TOYOTA36 (10.8%)
-18.2%prior 44
3
FORD32 (9.6%)
3.2%prior 31
4
ACURA25 (7.5%)
25.0%prior 20
5
CHEVROLET20 (6%)
17.6%prior 17
6
NISSAN17 (5.1%)
-29.2%prior 24
7
JEEP10 (3%)
-28.6%prior 14
8
SUBARU7 (2.1%)
-41.7%prior 12
9
BMW7 (2.1%)
10
KIA4 (1.2%)
-50.0%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Vehicle unit records

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

Sex Distribution (414 persons with recorded sex)

Male230 (55.6%)
6.0%prior 217
Female184 (44.4%)
-2.6%prior 189

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 mph speed zones increased by 12, from 123 in October 2021 to 135 in October 2022. The single fatality in the prior period occurred in a 30 mph speed zone, while no fatalities were recorded in any speed zone in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · 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: 2022-10-01 through 2022-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-10-01 through 2022-10-31 (31 days)
  • Geographic scope: LAWRENCE, MA
  • Total crash records analyzed: 164
  • Total persons involved: 451
  • Total vehicles involved: 332

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: October 2022." Published June 21, 2026. Reporting period: 2022-10-01 to 2022-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lawrence/october-2022-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 — October 2022 | ThatCarHitMe.com